Final Program - Society for Clinical Trials

Transcription

Welcome
Dear Colleagues,
2012 Program Committee
Welcome, newcomers and old friends alike, to Miami and the 33rd annual meeting of
the Society for Clinical Trials. I am delighted to present this interesting, diverse, and
compelling program for your delectation. The Program Committee, ably led by Mithat
Gonen, has put together an enjoyable and informative series of twenty-nine invited
sessions, one hundred contributed talks, and a large number of posters. Their topics
range from policy to methodology to ethics to data management to trial conduct. I’m
very appreciative of all their hard work. The Sunday workshops also run the gamut of
member interests and include half-day sessions on trial management, biomarkers,
and other topics along with a reprise of last year’s not-even-standing room invited
session on missing data. We will continue to have our traditional full day introduction to the basics of clinical trials. I thank Chris Coffey and his Education Committee
for all their hard work in organizing these. Last but not least, we have three plenary
sessions. The first, which opens the main part of our meeting, adheres to its theme
of clinical trials in vulnerable populations. I am proud that Dr. Wafaa El-Sadr of
Columbia University has agreed to give the Meinert lecture by speaking on one of
the most important public health issues of our time, AIDS/HIV prevention trials. She
has worked in both the third world and American inner cities, and has a compelling
story to tell. On Tuesday afternoon you will hear the Trial of the Year announced and
a presentation from the winner. As of this writing I don’t know who this will be, but
I’m looking forward to finding out. The third plenary session will end the meeting on
Wednesday morning with the famous and controversial (google “ioannidis atlantic
monthly” for an article containing a bombshell or two) Dr. John Ioannidis of Stanford
presenting the Founder’s Lecture on finding truth in clinical trial results.
Although sun-starved northerners like myself may want to sample the pleasures of
Miami, it will be tough finding a slack time to do so: I will leave that to be your challenge. However, the Society hasn’t stinted in providing a start. First, there is the
also famous but not so controversial (no arrests so far, to my knowledge) Society
reception on Monday evening. There and at peak times next to our registration
desk you will find a table of enthusiastic Welcome Committee volunteers to tell
you how to have fun in Miami (should you need to know). There is also the rumor
that Professor Dale Williams, a Society founder and Chair of its first two meetings’
Program Committees, will leave copies of rare artifacts and mementos at this table
for public perusal. Next, on Tuesday night just after the Trial of the Year award we
continue our tradition of having small receptions for affinity groups of members
involved in information technology; in industry or the FDA; those practicing in Europe;
clinical research associates; and MD trialists. If you belong to one of these groups
you are welcome to attend. And for all attendees, don’t forget the prepaid lunches
on Monday and Tuesday.
All these activities, along with coffee breaks and informal hallway conversations,
allow for networking and the exchange of ideas which our meetings seem to so amply
inspire. Enjoy yourselves!
Rick Chappell, Ph.D.
SCT President, 2011 - 2012
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Robert Annechiarico
Rick Chappell
Li Chen
Ken Cheung
Christopher Coffey
William Elgie
Dean Fergusson
Elizabeth Garrett Meyer
Susan Halabi
Jonathan Kimmelman
Beverly Koski
J. Athene Lane
Anne S. Lindblad
Wendy L. McBee
Alison McDonald
Kristine M. Nelson
Wendy Parulekar
Tim Ramsay
Dominic Reda
Yves Rosenberg
John Speakman
Chair: Mithat Gönen
2012 Education Committee
Kristel Aman
Carol Baker
Michael Benatar
Marie Benavente
Jeff Blume
Li Chen
Jodi DeStefano
Janice Flegg
Marta Gilson
Susan Halabi
Devin Hunt
Jingyee Kou
Oscar Moreno
Tom Moritz
Wendy Parulekar
Roberta Scherer
Emily VanMeter
Paul Wakim
Julie Weston
David Wright
Chair: Christopher Coffey
Annual Meeting Registration
The Society for Clinical Trials, Inc.
Officers and Board of Directors
Officers
Rick Chappell, PhD
President
University of Wisconsin, Department of Biostatistics, Madison, WI
Anne S. Lindblad, PhD
President-elect
The EMMES Corporation, Rockville, MD
Robert P. Byington, PhD
Past President
Wake Forest University School of Medicine, Winston-Salem, NC
Theodore Karrison, PhD
Secretary
University of Chicago, Chicago, IL
Joseph Collins, PhD
Treasurer
Cooperative Studies Program Coordinator Center, Perry Point, MD
Board of Directors
Gerald J. Beck (2013) – Cleveland Clinic Foundation, Cleveland, OH
Ivan Chan (2014) – Merck & Co., Inc., North Wales, PA
Theodore Colton (2014) – Boston University, Boston, MA
Nicole Close (2013) – EmpiriStat, Inc., Mt. Airy, MD
Susan Halabi (2014) – Duke University Medical Center, Durham, NC
Beverly Koski (2012) – Independent Consultant, Kingston, Ontario Canada
Heidi Krause-Steinrauf (2013) – The George Washington University Biostatistics Center, Rockville, MD
Sara L. Pressel (2014) – University of Texas School of Public Health, Houston, TX
Yves D. Rosenberg (2012) – National Institutes of Health, Bethesda, MD
Scott Rushing (2014) – Wake Forest University Health Sciences, Winston-Salem, NC
David L. Sackett (2012) – Kilgore Trout Research & Education Centre, Markdale, Ontario Canada
Christoph M. Seiler (2014) – CHIR-Net Heidelberg, University Hospital Heidelberg, Heidelberg, Germany
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SCT Committees
Committee Chairs
CRA Affinity Group
Beverly Koski
Nominating Committee
Dennis O. Dixon
Development Committee
Ivan Chan
Physicians Affinity Group
Yves D. Rosenberg
Education Committee
Christopher Coffey
Program Committee
Mithat Gönen
Fellows Committee
John M. Lachin
Student Scholarship Committee
James J. Dignam
Industry-FDA Affinity Group
José Pinheiro
Trialists Practicing in Europe Affinity Group
Athene Lane
IT Affinity Group
William E. Elgie
Web Oversight Committee
Scott Rushing
Membership Committee
Robert Annechiarico
2012 Class of Fellows
The Board of Directors for the Society for Clinical Trials invites all meeting attendees to join in saluting the
2012 Fellows during the opening session on Monday, May 21 at 8:45 AM in the Tuttle/Monroe/Flagler
Room.
Colin B. Begg
Mark A. Espeland
Domenic J. Reda
Marie Diener-West
KyungMann Kim
Daniel J. Sargent
Simon Day
Eleanor McFadden
Contributed Paper Session Moderators
Emily Anderson
Valerie Durkalski
Scott Rushing
Lauren Billot
Alexia Iasonos
Susan Shortreed
Li Chen
John Kairalla
Milena Silverman
Ying Qing Chen
Masha Kocherginsky
Michele Straus
Nicole Close
Robert Lindblad
Monica Taljaard
Meenakshi Devidas
Carmen Rosa
Elizabeth Thom
Yves Rosenberg
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Exhibitor List
The caBIG® Clinical Trials Management
Systems Knowledge Center
OpenClinica
Precision Vision, Inc.
The CITI Program at the University of Miami
SAS Institute Inc., JMP Division
CRC Press – Taylor & Francis
SAGE
Booth 1 - SAS Institute Inc., JMP Division
JMP® Clinical software from SAS provides a built-in comprehensive view of drug safety not provided in any other software.
Monitors and reviewers can explore highly visual summary dashboards for preclinical, clinical and post-marketing studies.
At the click of a button, users can drill down on subjects of interest to create patient profiles and patient narratives.
Booth 2 – SAGE
SAGE is a leading international publisher of journals, books, and electronic media for academic, educational, and professional markets. Since 1965, SAGE has helped educate a global community spanning a wide range of subject areas including
business, humanities, social sciences, and science, technology, and medicine. Visit us at www.sagepub.com.
Booth 3 – OpenClinica
OpenClinica is professional open source clinical research software for electronic data capture and clinical data management.
Used in thousands of clinical trials worldwide, OpenClinica provides freedoms and flexibility that makes clinical research
more effective. Learn more at www.openclinica.com.
Booth 4 – The CITI Program at the University of Miami
The Collaborative Institutional Training Initiative (The CITI Program) at the University of Miami provides web-based research
ethics training in Human Subjects Research, Good Clinical Practice, Information Privacy and Security, Animal Care and Usage,
Biosafety and Biosecurity, Responsible Conduct of Research, and U.S. Export Control Regulations. Visit www.citiprogram.org
Booth 5 – CRC Press - Taylor & Francis
Chapman & Hall/CRC – Taylor & Francis Group is a premier books and journals publisher, as well as a publishing partner
with the ASA for its journals. Visit our booth to browse our newest books at a discount of up to 50% or to pick up a journal.
Booth 6 – The caBIG® Clinical Trials Management Systems Knowledge Center
The caBIG® Clinical Trials Management Systems Knowledge Center is an NCI-supported entity led by the Duke Cancer
Institute, with Northwestern’s Lurie Comprehensive Cancer Center, The Alliance for Clinical Trials in Oncology, and
SemanticBits. The Center provides a centralized repository of information and web-based support facilitating the deployment/development of caBIG® tools, standards, and infrastructure.
Booth 7 – SCT information Booth
Booth 8 – Precision Vision, Inc.
Precision Vision is a leading producer of vision testing and visual acuity products worldwide. Their benchmark products
including the ETDRS Illuminator cabinet, visual acuity and contrast sensitivity charts are approved for use in clinical trials.
They are a manufacturer with capability of consolidating other items for clinical trial needs and worldwide distribution.
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Exhibitor Map
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SCT Corporate Sponsors &
Member Contributors
Thank you to our generous SCT Corporate Sponsors for the period May 2011 – April 2012
Abbott
Amgen
Aptiv Solutions
EMMES Corporation
GW Biostatistics Center
Janssen Research & Development, LLC
Merck & Co., Inc
Statistics Collaborative
Member Contributors to SCT
We encourage members to consider making a tax deductable gift to support the non-profit activities sponsored
by the Society. Your generous contributions help to fund the following programs:
Mary Karpers-Burke Member Sponsorship: Involves sponsoring one year of membership for a new member, in
honor of Mary Burke, who served the Society as Coordinator for over 20 years.
General Fund: Allows the Society to use your gift flexibly to support various important activities.
Sylvan Green Scholarship Program: Provides funds for a physician clinical trialist to attend our annual meeting
and present a paper.
Curtis Meinert Honorary Keynote Address: Supports the travel and honorarium for a prominent keynote speaker.
Thank you to those members who contributed to the Society for 2012.
Susan A. Anderson
David Fitts
Yves D. Rosenberg
Stanley Azen
Mithat Gonen
Anne Ryan
Abraham Samuel Babu
Mae Gordon
David L. Sackett
Chris Barker
Joel Greenhouse
Stanley H. Shapiro
Colleen Barnette
Susan Halabi
Steven Snapinn
Colin B. Begg
Susan Hilsenbeck
Barbara Snyder Hawkins
Christine Blasey
Bo Hu
Martin R. Stockler
Robert P. Byington
Ruth Kirby
Vicki Stover Hertzberg
Rick Chappell
Kuang-Kuo Lan
Shayne P. Taback
Janet Darbyshire
Xue Li
Barbara Tilley
Kay Dickersin
Anne S. Lindblad
Miguel Villarreal
Marie Diener-West
Wendy Mack
Dennis Wallace
James J. Dignam
Sumithra J. Mandrekar
Roseann M. White
Dennis O. Dixon
Kimberly McDowell
O. Dale Williams
Deborah Donnell
Timothy M. Morgan
Elizabeth C. Wright
Lynda Marie Emel
Sara L. Pressel
Qiang Zhang
Marian Fisher
Carol K. Redmond
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Schedule of Events
All meeting rooms are located on the Terrace Level unless otherwise indicated.
Sunday, May 20, 2012
7:00 AM – 5:00 PM
Registration – Lower Promenade
Pre-Meeting Workshops
8:00 AM – 5:00 PM (Break 9:45 AM – 10:15 AM & 2:45 PM – 3:15 PM – Monroe/Flagler)
Workshop P1 (Full day)
Essentials of Randomized Clinical Trials – Tuttle Center
8:00 AM – 12:00 PM (Break 9:45 AM – 10:15 AM)
Workshop P2
Trial and Site
Management for
Multi-Center Trials
Workshop P3
Practical Statistical
Reasoning in Clinical
Trials for Non-Statisticians
Workshop P4
Adaptive Clinical Trials
–
Tuttle North
–
Brickell North
–
Tuttle South
12:00 PM – 1:00 PM
Workshop P5
Biomarkers in Clinical
Trials: General Principles
for Study Design and
Statistical Evaluation with
Case Studies
–
Brickell South
Lunch on your own
1:00 PM – 5:00 PM (Break 2:45 PM – 3:15 PM – Monroe/Flagler)
Workshop P6
Workshop P7
Workshop P8
Challenges and
CDISC: How to Adapt to Statistical Procedures for
Strategies of Clinical Data the Standards and How Interim Analysis in Clinical
to Handle Data that Does
Trials
Management
Not Easily Fit into the
Standards
–
–
–
Brickell North
Tuttle North
Brickell South
5:30 PM – 6:30 PM
Education Committee Meeting – Azalea
5:30 PM – 7:30 PM
SCT Board of Directors Meeting – Hibiscus A
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Workshop P9
The Prevention and
Treatment of Missing
Data in Clinical Trials
–
Tuttle South
Schedule of Events
All meeting rooms are located on the Terrace Level unless otherwise indicated.
Monday, May 21, 2012
7:00 AM – 5:00 PM Registration – Lower Promenade
8:00 AM – 5:30 PM
Exhibits – Upper & Lower Promenade
8:30 AM – 8:45 AM
Welcome – Tuttle, Monroe & Flagler
SCT President, Rick Chappell
University of Wisconsin, Madison, WI
8:45 AM – 9:00 AM
Presentation of Class of 2012 Fellows
9:00 AM – 10:15 AMCurtis Meinert Lecture – Tuttle, Monroe & Flagler
Wafaa El-Sadr – “Global HIV Prevention Trials”
Director of the International Center for AIDS Care and Treatment Programs at
Columbia University
10:15 AM – 10:45 AM
Break/Exhibits/Posters – Upper & Lower Promenade
10:45 AM – 12:15 PM Invited Sessions I
Session 1
Session 2
Session 3
Cancer Screening
Clinical Site
Multiplicity Issues in
RCTs: From Start to
Monitoring – The
Confirmatory Clinical
Finish
Real World of Data
Trials for Drug
Quality and Limited
Development
Resources
–
–
–
Riverfront South
Hibiscus
Orchid BCD
(Lobby Level)
M, TM
IS/DM, TM
ST
Session 4
Assessing
Biosimilarity and
Interchangeability of
Follow-on Biologics
–
Jasmine
M, ST
Session 5
Design and Conduct
of Trials in Critically
ill Patients –
Challenges and
Solutions
–
Brickell
M, TM
12:15 PM – 1:30 PM
Lunch – Included with Meeting Registration – Riverfront Central (Lobby Level)
1:30 PM – 3:00 PM Contributed Paper Session I
CPS 1A
Management of
Multicenter Trials
and Dissemination of
Findings
–
Orchid BCD
M, TM
3:00 PM – 3:30 PM
CPS 1B
Dose Finding Trials
CPS 1C
Randomized Trials
CPS 1D
Information
Technology
CPS 1E
Trial Monitoring
–
Riverfront South
(Lobby Level)
ST
–
Jasmine
ST
–
Brickell
IS/DM
–
Hibiscus
ST, TM
*All information/scheduling subject to change.
Track Key
IS/DM = Information Systems/Data Management; M = Medical; ST = Statistical; TM = Trial Management
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Schedule of Events
Invited Sessions II
3:30 PM – 5:00 PM Session 6
Session 7
Confusions and
Electronic Data
Controversies Around Capture (eDC): One
Pragmatic Trials
Size Does Not Fit All
–
Riverfront South
(Lobby Level)
M, ST
–
Jasmine
IS/DM
Session 8
Methodological
Challenges and
Solutions for LateStage Clinical Trials
–
Brickell
TM, ST
Session 9
Phase II Oncology
Trials: Recent
Considerations in
Trial Design and
Endpoint Selection
–
Hibiscus
ST
Session 10
Common Data
Elements in Clinical
Research in
Neurology
–
Orchid BCD
IS/DM
5:00 PM – 6:30 PM
SCT Program Committee Meeting – Azalea
6:30 PM – 8:00 PM Reception – Included with Meeting Registration – Riverwalk (Outdoor Terrace)
Tuesday, May 22, 2012
7:00 AM – 5:00 PM
8:00 AM – 5:00 PM
Exhibits – Upper & Lower Promenade
7:50 AM – 8:50 AM Contributed Paper Session II
CPS 2A
Cancer Clinical Trials
–
Riverfront South
(Lobby Level)
ST, TM
9:00 AM – 10:30 AM
CPS 2B
Data Standards and
Data Exchange
–
Brickell
IS/DM
CPS 2D
Safety Analysis
CPS 2E
Trial Conduct
–
Jasmine
ST
–
Orchid BCD
IS/DM
Invited Sessions III
Session 11
Session 12
Update from the
Developing
Clinical Trials
Evidence-based
Transformation
Multistage Treatment
Initiative: Rethinking Policies from Clinical
Approaches to
Trials Data
Clinical Trial
Oversight and
Premarket Safety
Management
–
–
Jasmine
Brickell
TM
M, ST
10:30 AM – 11:00 AM
CPS 2C
Ethics of Clinical
Trials
–
Hibiscus
M
Session 13
Open Source
Statistical
Software in Drug
Development:
Challenges and
Opportunities
–
Riverfront South
(Lobby Level)
IS/DM, ST
Session 14
Session 15
Ethical, Regulatory Student Scholarship
and Recruitment
Presentations
Issues in Vulnerable
Populations:
Substance Use Trials
as a Case Study
–
Hibiscus
M, TM
–
Orchid BCD
ST
Track Key
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Schedule of Events
11:00 AM – 12:30 PM Invited Sessions IV
Session 16
Guidelines for the
Ethical Conduct and
Ethics Review of
Cluster Randomized
Trials: Statement
from an International
Consensus Meeting
–
Jasmine
M, TM
Session 17
Mastering the
Challenges:
Academic
Infrastructures for
Clinical Trials in
Europe
–
Brickell
IS/DM, TM
Session 18
Data and Safety
Monitoring Board
(DSMB) Roles in
Adaptive Design
Trials
–
Riverfront South
(Lobby Level)
M, ST
Session 19
Session 20
A Centennial
Randomized Trials in
Celebration of
Pregnant Women
Jerome Cornfield and
His Contributions to
Clinical Trials
–
Hibiscus
ST
12:30 PM – 1:50 PM Lunch/SCT Business Meeting – Tuttle, Monroe & Flagler
Included with Meeting Registration
1:50 PM – 2:50 PM Contributed Paper Session III
CPS 3A
Biomarkers
–
Riverfront South
(Lobby Level)
ST
CPS 3B
Patient Recruitment,
Enrollment and
Retention
–
Jasmine
TM
CPS 3C
Reporting of Clinical
Trials
CPS 3D
Statistical Methods
and Trial Design
CPS 3E
Vulnerable
Populations
–
Hibiscus
TM, M
–
Brickell
ST
–
Orchid BCD
M, TM
2:50 PM – 3:20 PM
3:20 PM – 4:50 PM Invited Sessions V
Session 21
Translational
Behavioral Science:
A Framework
to Guide the
Development of
Health-related
Behavioral
Interventions
–
Orchid BCD
M
Session 22
Registration and
Reporting of
Clinical Trials: Key
Informatics Issues
and Approaches
–
Riverfront South
(Lobby Level)
IS/DM
–
Orchid BCD
M
Session 23
Increasing Clinical
Program Success
with Modeling and
Simulation
Session 24
Safety Evaluation
with Clinical Trial
Information and
Postmarketing Data
Session 25
Coordination and
Conduct of Phase
III Emergency
Treatment Trials
–
Jasmine
ST
–
Hibiscus
M, ST
–
Brickell
TM
5:00 PM – 6:20 PM Plenary Session – Tuttle, Monroe & Flagler
In Memory of Paul Meier – Theodore Karrison, SCT Secretary
University of Chicago
Trial of the Year
Track Key
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Schedule of Events
6:30 PM – 7:30 PM
Information
Technology
–
Orchid D
Affinity Group Receptions – Included with Meeting Registration
Clinical Research
Associates
–
Orchid C
MD Clinical Trialists
Trialists Practicing in Members of Industry
Europe
or FDA
–
–
Orchid B
Orchid A
–
Orchid C
Wednesday, May 23, 2012
7:00 AM – 11:00 AM
8:00 AM – 9:30 AM
Invited Sessions VI
Session 27
Session 28
A Real-time Electronic
Response-Adaptive
Remote Data Capture and
Treatment Allocation in
Therapeutic Risk Group
Clinical Trials: The Costs
Communication System:
and Benefits
From Central Laboratories
to Individual Patient
Treatment in Pediatric
Cancer Clinical Trials
–
Riverfront South
(Lobby Level)
IS/DM, M, ST
9:45 AM – 11:15 AM –
Brickell
ST
Session 29
Emerging Issues and
Their Solutions in the
Implementation of
Adaptive Designs in
Clinical Trials
Session 30
Dealing with Treatment
Compliance in Clinical
Trials on Inherently Lowcompliant Populations:
What to do at the Design,
Monitoring and Analysis
Stages
–
Jasmine
ST, TM
–
Hibiscus
M, TM
Contributed Paper Sessions IV
CPS 4A
Clinical Epidemiology
CPS 4B
Data Management
–
Brickell
M, ST
–
Hibiscus
IS/DM
CPS 4C
New Opportunities in
Data Capture
–
Riverfront South
(Lobby Level)
IS/DM
CPS 4D
Statistical Methods
CPS 4E
Recent Trends in
Trial Design
–
Orchid BCD
ST
–
Jasmine
ST
11:15 AM – 11:30 AM
Break – Ballrom Foyer
11:30 AM – 12:15 PM
Founders Lecture – Tuttle, Monroe & Flagler
John P.A. Ioannidis
“Designing and Dissecting the Geometry of Randomized Evidence”
Director of the Stanford Prevention Research Center
Track Key
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May 20, 2012
Full Day Workshop
Workshop P1
8:00 AM – 5:00 PM
Essentials of Randomized Clinical Trials
This full-day pre-meeting workshop is an overview of some essential concepts related to the design, conduct and
analysis of clinical trials. The workshop is intended for those with little previous experience or formal training
in clinical trials as well as those who have some basic clinical trial experience but desire a better fundamental
understanding of the methodological principles and concepts involved in clinical trials. No prior knowledge of
biostatistics is needed. The first half of the workshop will introduce participants to some key principles associated
with the design and conduct of clinical trials. Topics to be covered include the rationale for randomized clinical
trials, key design and methodological issues, such as choice of eligibility criteria, control group, randomization
and blinding-related issues, and how to define objectives and end-points for a trial. This first part of the
workshop will cover basic principles of data collection, reporting, and quality control as well as principles of
project management. The second half of the workshop will provide an overview of statistical principles and
methodologies commonly utilized in clinical trials. Topics to be covered include choice of endpoints, sample size
computation, methods for treatment allocation and stratification, intent to treat, procedures on how to monitor
a trial, and how to analyze the results from randomized clinical trials.
Attendees should be able to describe the essential elements of a clinical trial, essential principles of project
management of a multicenter clinical trial, describe key statistical concepts and their application to the validity
and interpretation of clinical trial results, and use this knowledge to contribute as a researcher or collaborator
in the successful conduct of a clinical trial. In addition, attendees should be able to read clinical trials literature
critically.
Faculty: Dixie J. Ecklund, University of Iowa
Susan Halabi, Duke University
Laura Lovato, Wake Forest University
Michele Melia, Jaeb Center for Health Research
Yves Rosenberg, National Heart, Lung, and Blood Institute/National Institutes of Health
Workshop Organizer: Yves Rosenberg, National Heart, Lung, and Blood Institute/National Institutes of Health
Half Day Workshops – Morning
Workshop P2
8:00 AM – 12:00 Noon
Trial and Site Management for Multi-Center Trials
Effective trial and site management is critical to the successful and timely completion of multi-center clinical
trials. This workshop will present information on how this can be achieved. Practical examples will be presented
for each topic and discussion with workshop participants will be encouraged.
Our international workshop faculty members have experience in coordinating national and international publicly
funded and industry trials, as well as recruiting patients and managing activities at clinical centers. They have
worked in a variety of settings and will bring their varied experiences to this workshop.
Participants will leave with a practical overview of trial and site management, tools, resources and ideas for
effective trial implementation.
Topics to be covered include:
• Feasibility and site selection
• Study start-up considerations, including paperwork required from sites to participate
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May 20, 2012
• Handling payments to the sites, including different types of contracts
• Establishing study procedures
• Staffing requirements at the coordinating centre
• Training and continuing education of staff at the clinical sites, including information the coordinating centre
should provide
• Techniques for interacting effectively with clinical sites and study partners
• Staff motivation at clinical sites
• Patient recruitment and retention strategies
• Data collection systems and techniques to ensure timely reporting
• Quality assurance
• Tracking study metrics
• Study record keeping suggestions
• Study close down process
• Publication arrangements and policies with clinical sites
Faculty: Marie-France Benavente, University of British Columbia
Lauren McGurk, Rho, Inc.
Beverly Koski, Independent Consultant
Alison McDonald, University of Aberdeen
Workshop Organizer:
Alison McDonald, University of Aberdeen
Workshop P3 8:00 AM – 12:00 Noon
Practical Statistical Reasoning in Clinical Trials for Non-Statisticians
This workshop is not an introduction to clinical trials. In fact, it assumes knowledge of and experience in clinical
trials. Nor is it an introduction to biostatistics. It does not teach how to perform statistical tasks; there are no
formulas and no proofs. Instead, it explains why these statistical tasks are performed and what they mean once
they are performed.
This workshop walks you through the clinical trial cycle from beginning to end, and addresses statistical issues
discussed between the non-statistician and the biostatistician during that cycle. It starts with the research
question and ends with the publication of results. Intermediate topics include:
• Trial design, e.g. basic types of design, primary outcome measure(s), sample size calculation and power
analysis.
• Analysis plan, e.g. simple vs. complex statistical models, the use of covariates, longitudinal (repeated
measures) models, handling missing data.
• Trial monitoring and Data and Safety Monitoring Board reports, e.g. interim analyses, sample size
re-calculation.
• Final analysis, e.g. what do “reject H0” and “do not reject H0” mean? What does the “p-value” mean? Why
“correct” for multiple tests? What does “site-by-treatment interaction” mean?
• Subgroup analyses.
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May 20, 2012
Objectives:
(1) To put in plain English the reasoning and intuition behind basic statistical concepts used in clinical trials.
(2) To improve communication between non-statisticians involved in clinical trials and their biostatisticians.
Target Audience: Non-statisticians with experience in clinical trials who seek a better understanding of statistical
concepts encountered throughout the cycle of a clinical trial.
Faculty: Paul Wakim, National Institute on Drug Abuse/National Institutes of Health
Workshop Organizer:
Paul Wakim, National Institute on Drug Abuse/National Institutes of Health
Workshop P4
Adaptive Clinical Trials
8:00 AM – 12:00 Noon
Adaptive clinical trials—trials in which key design parameters are modified according to pre-specified decision
rules during the course of the trial in response to accumulating data from the trial—may be more efficient,
ethically acceptable and, if properly designed and executed, accurate than traditional designs. However, the
design of such trials is inherently more complex than traditional approaches and must precisely define the planned
adaptations a priori. In addition, simulation has an important role in evaluating the operating characteristics
of adaptive trials. The implementation of adaptive trials introduces additional complexities in logistics, data
availability, randomization, drug supply, and interactions with the sponsor and independent data and safety
monitoring boards (DSMBs). The rapid proliferation of adaptive designs, and inconsistent use of terminology, has
created confusion about the similarities and, more importantly, the differences among the techniques. In this
session, the presenters with a broad range of experience in the conduct of these trials will address conceptual,
statistical, and logistical issues in the design, implementation, and analysis of adaptive clinical trials.
First Dr. Lewis will discuss logistical and practical issues in composition, function, and interactions with all
participants in the trial’s design and execution and provide an example from a Phase 2 drug trial. He will describe
the information flow necessary for an efficient trial and rapid and timely adaptations but also to ensure blinding.
Then he will describe a case where a DMC used pre-specified rules developed in conjunction with the sponsor
to drop an arm during a dose-finding trial. Dr. Pinheiro will focus on adaptive dose-ranging designs and analysis
methods, discussing their motivation and key elements, and describing some of the most common approaches
used in practice. He will conclude by discussing the key results and recommendations from the PhRMA Adaptive
Dose-Ranging Studies working group. Then Dr. Connor will describe a dual endpoint (efficacy and safety) adaptive
Bayesian design of a medical device. This trial design will be used to illustrate how interim data and a Bayesian
longitudinal model can be used to calculate predictive probabilities that are used to identify the optimal trial size
during the course of the trial.
Attendees should be conversant in the fundamentals of clinical trial design and methodology, but no foundational
knowledge of Bayesian statistics or adaptive designs is required. The expected audience is statisticians,
clinicians involved in trials, and other clinical trialists interested in adaptive designs. After the course, attendees
will understand the role of adaptive trials and possess the foundation for their design, implementation, and
interpretation.
Faculty: Jason Connor, Berry Consultants
Roger J. Lewis, Harbor-UCLA Medical Center
José Pinheiro, Janssen R+D
Workshop Organizer:
14
May 20, 2012
Workshop P5
8:00 AM – 12:00 Noon
Biomarkers in Clinical Trials: General Principles for Study
Design and Statistical Evaluation with Case Studies
Despite some publicized setbacks, biomarkers continue to have the potential to greatly improve healthcare, e.g.,
in drug development, surrogate endpoint evaluation, risk assessment, and early detection. Biomarkers come
in many varieties, such as genomic, molecular, or clinical. The utility of a biomarker is context dependent. Its
credibility depends on the evidential level observed for its intended use. For candidate biomarkers measured
by a medical device (e.g., in vitro diagnostic assay), quality of device measurement can be crucial in assessing
biomarker utility. Moreover, when a drug relies on a companion diagnostic device to classify patients for drug
eligibility, regulatory acceptance of both the drug and device are needed for joint licensure. This half-day short
course will provide an overview ranging from types of biomarkers as drug development tools to the need for in
vitro diagnostic device development and validation. The course outline includes:
• Literature overview of biomarker research
• General principles and practical aspects for development of a biomarker as a classifier, a diagnostic, or a
surrogate, etc.
• Study designs including merits and limitations
• Statistical analysis issues for drug development versus for device development and validation
• Formal assessment in clinical trials of the clinical utility of a biomarker as predictive, prognostic or adding
benefit
• Prospectively planned retrospective analysis in ongoing or completed trials, including when incomplete
genomic samples are collected
• Multiplicity issues
• Misclassification issues in randomized controlled trials
• Single-trial and meta-analytic validation
• Appropriate handling of confounding factors
• Handling of missing test results
• Analytical and clinical validation of the diagnostic device
• Bridging from one companion diagnostic to another for the same intended use
• Regulatory considerations for drug versus for device evaluation
• Examples from a variety of clinical areas
The short course consists of four focused presentations:
Session
Session
Session
Session
1:
2:
3:
4:
Overview of biomarkers in drug development
Overview of surrogate endpoint evaluation in clinical studies
Overview of biomarkers in device development
Biomarker Trial Designs: Lessons from real trials
Attendees should have an understanding of clinical trials.
Faculty: Sumithra Mandrekar, Mayo Clinic
Geert Molenberghs, University of Hasselt and Katholieke Universiteit Leuven
Gene Pennello, U.S. Food and Drug Administration
Sue-Jane Wang, U.S. Food and Drug Administration
Workshop Organizers: Li Chen, Amgen
Christopher S. Coffey, University of Iowa
15
May 20, 2012
Half Day Workshops – Afternoon
Workshop P6
1:00 PM – 5:00 PM
Challenges and Strategies of Clinical Trial Data Management
This workshop will discuss real-world strategies learned from both industry and academic sectors to solve
common and unique challenges related to collecting and managing clinical trial data. Participants are encouraged
to bring their own experiences to include in the discussion. Taught from the perspective of experienced data
managers and database developers, participants will learn about and discuss problematic areas such as:
• Communication with study team members
• Working with vendors and laboratories
• Choosing the right Data Management System
• Optimizing Case Report Form (CRF) design
• Enhancing clinical trial data quality
• Sharing and submitting information to sponsors, partners, and the FDA
• Data Sharing and access for NIH funded studies
• Regulations surrounding Data Management
This course applies to anyone working in the clinical data management field in pharmaceutical industries,
research institutions as well as universities. This course would also benefit anyone who is involved in the
planning and preparing of a clinical trial, conducting a clinical trial, or has management responsibility (direct or
indirect) for clinical trials.
Faculty: Kristine Nelson, The EMMES Corporation
Wenle Zhao, Medical University of South Carolina
Workshop Organizer:
Devin J. Hunt
16
May 20, 2012
Workshop P7 1:00 PM – 5:00 PM
CDISC: What are the Standards, How Will They Help, and How to Adapt?
Although the FDA does not mandate submissions follow Clinical Data Interchange Standards Consortium (CDISC)
guidelines and standards, it strongly encourages their use. This workshop begins with an overview of CDISC and
the various standards it promotes. It then takes an in-depth look at some of the more difficult aspects of mapping
clinical data to the Study Data Tabulation Model (SDTM) standard. We will also look at some of the challenges
of doing legacy conversions (putting older studies in a more “up-with-times” model).
We will also discuss some of the challenges in creating the Analysis Data Model (ADaM) datasets, especially
the all-important subject-level analysis dataset (ADSL). We will also discuss CDISC implementation strategies in
your organization. Finally, we end the workshop with a panel discussion, focusing on daily “real world” issues
that arise while implementing the CDISC guidelines.
The goal of this workshop is to educate attendees about the ever-evolving CDISC guidelines. Among the groups
that stand to benefit from an understanding of the standards are: study coordinators and PI’s responsible for
collection of the data at the research site; data managers, programmers, and statisticians who standardize,
tabulate, and analyze the data; PI’s and statisticians responsible for traceability between the clinical and analysis
datasets; and, of course, the FDA reviewer. Effective standards implementation by these groups reduces delivery
time and increases product quality throughout the study life cycle.
Faculty: Jeff Abolafia, Rho, Inc.
Carol Baker, Rho, Inc.
Karen Wade, Rho, Inc.
Rob Woolson, Rho, Inc.
Workshop Organizer:
Carol Baker, Rho, Inc.
Workshop P8 1:00 PM – 5:00 PM
Statistical Procedures for Interim Analysis in Clinical Trials
There are two basic statistical procedures in monitoring clinical trials: conditional power and group sequential
methods. For conditional power evaluation, we will cover the case when the underlying stochastic process follows
a discrete Brownian motion process with a linear drift. Predictive power, the Bayesian version of conditional
power, will also be presented with discussion. For the topic of group sequential methods, we will start with the
classical “constant boundary” approach (Pocock 1977, O’Brien-Fleming 1979 and Wang-Tsiatis 1987) where, for
a given alpha value, number of looks and the shape of the boundary, there is an unique corresponding constant
determining the desired group sequential boundary. We will continue to introduce a more flexible alpha-spending
approach to group sequential methods. Examples will be demonstrated by the use of free software created at
University of Wisconsin-Madison.
Design of survival trials will also be covered. We will present a heuristic introduction to the logrank test which is
locally most powerful under the proportional hazards assumption. The most popular methods for the comparisons
of two survival distributions are of the Kaplan-Meier curve at a given point in time and the logrank test. When
the proportional hazards assumption is violated, we will demonstrate that these two methods might deliver quite
different messages and lead to misleading interpretations.
This workshop provides a primer with the following book: Proschan MA, Lan KKG and Wittes JT. (2006) Statistical
Monitoring of Clinical Trials – A Unified Approach, Springer.
Faculty: K. K. Gordon Lan, Janssen R+D
Michael Proschan, National Institute of Allergy and Infectious Diseases/National
Institutes of Health
Workshop Organizer:
17
May 20, 2012
Workshop P9
1:00 PM – 5:00 PM
The Prevention and Treatment of Missing Data in Clinical Trials
At the request of the U.S. Food and Drug Administration, the National Academy of Sciences convened the Panel
on the Handling of Missing Data in Clinical Trials to prepare a report that would make recommendations that
could be used to aid in the FDA’s eventual development of a Guidance for Industry on that topic. This half-day
workshop presents an overview of the findings and recommendations of the resultant report from the perspective
of two clinical trialist members of the NAS panel. The workshop will follow the basic organization of the NAS
report, though it will place greatest emphasis on aspects of trial design and trial conduct that can be used to
minimize issues arising from missing data. However, because trial protocols must also describe how any missing
data will be handled at the end of the study, methods for analysis of clinical trial results will be discussed at
a conceptual level. We will focus more on the common features of such analyses than on the technical details
of particular analytic methods. To that end, the target audience for this workshop includes biostatisticians and
epidemiologists involved in the design of clinical trials, as well as study coordinators and CRAs involved in the
conduct of the studies.
We first review settings in which missing data commonly arise and pose difficult problems in the analysis
and interpretation of clinical trial results, as a basis for discussing aspects of clinical trial design that could
minimize or even eliminate the most troublesome missing data. In particular we focus on aspects of clinical trial
design that relate to appropriate definition of primary endpoints, anticipating problems that might arise when
patients drop off study drug due to adverse events, lack of efficacy, or competing risks such as newly developed
contraindications to therapy or deaths from other causes. We further consider alternative trial designs that would
facilitate randomized comparisons among patients who can adhere to protocol defined treatment strategies.
We then consider aspects of trial conduct that will promote the collection and analysis of complete data on all
randomized subjects. Proper attention should be paid to informing both investigators and participants of the
scientific importance of complete data collection. We describe ways in which the Study Protocol, the Manual
of Operations, and the Case Report Forms can facilitate the investigators’ understanding of and adherence to
the actions that must be taken to minimize missing data, as well as discussing the impact that careful subject
education (including the Informed Consent documents) can have on preserving the scientific and statistical
relevance of clinical trial results.
Major recommendations of the Panel also included the need for lead investigators to anticipate missing data and
to plan for appropriate methods for the statistical analysis of the clinical trial results. We briefly discuss the need
for easily understood and clearly described methods based on reasonable assumptions about the mechanisms
giving rise to missing data and assumptions about the likely impact that missingness would have on conclusions
drawn from the RCT. We give a broad, non-technical overview of some of the approaches that might be used
for the primary analysis of the trial results. Then, owing to the impossibility of ever knowing that assumptions
about missing data mechanisms are valid, we conclude with an overview of general criteria that should be met
by sensitivity analyses that explore the potential impact of the assumptions about missing data.
Faculty: Scott S. Emerson, University of Washington
James D. Neaton, University of Minnesota
Workshop Organizer:
Rick Chappell, University of Wisconsin
18
All information subject to change.
7:00 AM – 5:00 PM
Registration
8:00 AM – 5:30 PM
Exhibits
8:30 AM – 8:45 AM
Welcome – SCT President, Rick Chappell
University of Wisconsin, Madison, WI
8:45 AM – 9:00 AM
Presentation of Class of 2012 Fellows
9:00 AM – 10:15 AMCurtis Meinert Lecture – Wafaa El-Sadr
“Global HIV Prevention Trials”
Director of the International Center for AIDS Care and Treatment Programs at
Columbia University
10:15 AM – 10:45 AM
Break/Exhibits/Poster Prime Time
10:45 AM – 12:15 PM
Invited Session 1: M, TM
Cancer Screening RCTs: From Start to Finish
RCTs of cancer screening modalities face challenges not common in treatment trials, including the need to
recruit large numbers of healthy participants and monitor them for many years. Nevertheless, a number of cancer
screening RCTs have been successfully completed and have been instrumental in shaping public health policy.
Our session will highlight the cancer screening lifecycle. The experiences of three pivotal trials will be presented,
with speakers focusing on challenges and successes in the areas of trial design, operations, and monitoring.
The session will begin with a brief introduction of aspects of cancer screening RCTs that make them unique.
Three trials then will be presented: the Canadian National Breast Cancer Screening Study (I and II), the Prostate,
Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial, and the National Lung Screening Trial (NLST). A
discussant will then summarize the presentations and provide his own reflections on cancer screening RCTs in
general. There will be an opportunity for comments and questions from the audience.
Organizer: Pamela Marcus, National Cancer Institute, National Institutes of Health
Chairs: Pamela Marcus, National Cancer Institute, National Institutes of Health
Phil Prorok, National Cancer Institute, National Institutes of Health
Speakers: Tony Miller, University of Toronto
Phil Prorok, National Cancer Institute, National Institutes of Health
Pamela Marcus, National Cancer Institute, National Institutes of Health
Discussant: Tony Miller, University of Toronto
10:45 AM – 12:15 PM Invited Session 2: IS/DM, TM
Clinical Site Monitoring – The Real World of Data Quality and Limited Resources
There has been a recent focus on clinical site monitoring and how much is enough. “Industry Standard” of
100% source to data system monitoring is one way to interpret the sponsor’s obligation to ensure accurate
and complete records. Clinical site monitoring programs can absorb 30% to 50% of the overall trial budget. In a
time where resources are limited, can we afford this investment? If we fail to make the investment will it impact
data quality and integrity and thus confidence in clinical trial outcomes? This session will describe approaches
to creating comprehensive monitoring plans that may improve the efficiency of monitoring programs. We will
Track Key
19
present two large multi-site NIH-sponsored clinical trial networks and monitoring strategies including both remote
and random sampling monitoring to address these issues. We will also present an approach to Centralized data
monitoring to query data bases for inconsistencies in patterns of reported data to help detect fraud or anomalous
data trends that warrant further assessment or inquiry. These examples and tools will offer alternatives to 100%
data auditing while maintaining data and ultimately study integrity.
Chair: Robert Lindblad, The EMMES Corporation
Speakers:Anne Zajicek, National Institute of Child Health and Human Development,
National Institutes of Health -- Pediatric clinical trial network under the Best
Pharmaceutical Children’s Act
Maria Campanella, The EMMES Corporation -- Multi-site, multi-protocol National
Institute on Drug Abuse network with limited resources and increased number of
clinical trials and sites actively enrolling
John Marler, U.S. Food and Drug Administration -- An FDA initiative reviewing
completed data sets through programmatic algorithms to detect fraud and
anomalies.
10:45 AM – 12:15 PM
Invited Session 3: ST
Multiplicity Issues in Confirmatory Clinical Trials for Drug Development
In drug development, confirmatory Phase III clinical trials are conducted to provide the necessary evidence to
support regulatory decision-making for drug approval. Multiplicity then becomes an important problem with various
unintended consequences. The most widely recognized result is the lack of reproducibility and that the findings of
a trial can be misleading: seemingly significant effects occur more often than expected by chance alone and not
compensating for multiplicity can have important consequences. For instance, when the multiple comparisons
involve drug efficacy, they may result in approval of a drug as an improvement over existing drugs, when there is
in fact no beneficial effect. On the other hand, when drug safety is involved, it could happen by chance that the
new drug appears to be worse for some side effect, when it is actually not worse at all. Because of the strong
level of evidence required for Phase III trials, it is mandatory to adjust statistical inferences appropriately for
multiplicity in order to enable better decision making.
The U.S. Food and Drug Administration draft guidance on multiple endpoints in clinical trials is expected to be
released soon. The guidance addresses a wide range of multiplicity issues primarily for confirmatory trials. This
panel session is organized to comment on these issues. We bring together an expert panel of seven clinicians
and statisticians, consisting of distinguished international representatives from industry, academia and regulatory
agencies. The session will have three parts. In Part I, Sue-Jane Wang (FDA) will present a case study to illustrate
key multiplicity issues arising in Phase III trials and to motivate the subsequent panel discussion in Part II. Based
on this case study, several questions will be formulated and sent in advance to the panelists. For each question
panelists will be identified to provide their perspectives at the session. Finally, in Part III the discussion will be
open for questions from the audience to the expert panel.
Organizer: Frank Bretz, Novartis
Chair: Sue-Jane Wang, U.S. Food and Drug Administration
Speakers:
Track Key
Keaven Anderson, Merck
Frank Bretz, Novartis
Susan Ellenberg, University of Pennsylvania
H.M. James Hung, US Food and Drug Administration
Walter Offen, Eli Lilly
Robert O’Neill, US Food and Drug Administration
Norman Stockbridge, US Food and Drug Administration
20
10:45 AM – 12:15 PM
Invited Session 4: M, ST
Assessing Biosimilarity and Interchangeability of Follow-on Biologics
As more and more biological products are going off patent, it is a concern whether the generic versions (biosimilars
or follow-on biologics) of the innovative biologic products are therapeutically equivalent to the innovative biologic
products and whether they can be used interchangeably. Unlike small molecule drug products, biological
products are derived from living cells, which are fundamentally different from the small molecule drug products.
Thus, standard methods for assessment of bioequivalence and drug interchangeability for small molecule drug
products are not applicable to the biologic products.
Currently there is no established regulatory pathway for approval of follow-on biologics. Woodcock et al. (2007)
pointed out that for assessment of biosimilarity of follow-on biologics, the FDA would consider the following factors
regarding (1) the robustness of the manufacturing process, (2) the degree to which structural similarity could be
assessed, (3) the extent to which mechanism of action was understood, (4) the existence of valid, mechanistically
related pharmacodynamic assays, (5) comparative pharmacokinetics, (6) comparative immunogenicity, (7) the
amount of clinical data available, and (8) the extent of experience with the original product.
In this session we will focus on the scientific/statistical issues surrounding the assessment of biosimilarity
and interchangeability of follow-on biologics including quality, pharmacokinetics and pharmacodynamics, clinical
efficacy and safety, and how regulatory agencies and industry are evolving to deal with these issues.
Organizer: Shein-Chung Chow, Duke University School of Medicine
Chair: Eric Chi, Amgen, Inc.
Speakers: Stella Grosser, U.S. Food and Drug Administration -- Current regulatory experiences
in the assessment of biosimilarity of follow-on biologics
Shein-Chung Chow, Duke University School of Medicine -- On Scientific Factors for
Assessing Biosimilarity of Follow-on Biologics
Laszlo Endrenyi, University of Toronto -- On the interchangeability of Follow-on
Biologics
Nan Zhang or Jun Yang, Amgen, Inc. -- Scaled Margins in Assessing Follow-on Biologics
Discussant: Peter Lachenbruch, Oregon State University
10:45 AM – 12:15 PM
Design and Conduct of Trials in Critically Ill Patients – Challenges and Solutions
The design and conduct of trials in critically ill patients has a number of challenges. At a design level, for
example, there is high heterogeneity in the patient population and analysis strategies need to accommodate
for complex (and often composite) outcomes, e.g. reductions in death rates but increases in length of stay and
severity of disease. At a conduct level, there are also the ethical complexities raised by informed consent in this
vulnerable population, where assent (rather than consent) is the norm. In addition, there is often uncertainty
about which intervention to take to trial. In this session, these challenges will be discussed with a panel of
researchers experienced in designing and conducting trials in critically ill populations. Speakers will provide
examples of critical care trials in action; discuss the methodological issues commonly encountered in these
trials (and provide potential solutions); provide an example of how psychological and ethical theory can aid the
identification of which trial to adopt and whether a trial is feasible; and discuss the importance of networks and
professional buy-in to promote and aid the conduct of trials in this field.
Organizer and Chair: Marion Campbell, University of Aberdeen, UK
Speakers: Graeme MacLennan, University of Aberdeen, UK
Ryan Zarychanski, University of Manitoba
John Norrie, University of Aberdeen, UK
Marion Campbell, University of Aberdeen, UK
21
12:15 PM – 1:30 PM
Lunch – Included with Meeting Registration
1:30 PM – 3:00 PM
Contributed Paper Sessions I M, TM
Moderator: Susan Shortreed
Session 1A: Management of Multicenter Trials and Dissemination of Findings
1:30 PM 01The German National Surgical Network (CHIR-Net);
Doerthe Seidel, Witten/Herdecke University
1:45 PM 02What Influences Patient Participation in Randomized Controlled
Trials of Surgical Interventions?; Katrien Oude Rengerink, Academic
Medical Center
2:00 PM 03Funding Strategies for Establishing Surgical Trial Centers –
Experience and Strategies; Gregor Stein, Cologne University Hospital
2:15 PM 04Challenges of Developing Procedures for Serious Adverse Event
Management and Reporting According to Regulatory Requirements in
Clinical Trials with Medical Devices in Germany; Heike Moenkemann,
Center Cologne (BMBF Grants 01KN1106 and 01EZ0931)
2:30 PM 05Knowledge Transfer in Clinical Research: Do We Know What is
Going On, Do We Know the Results and Are They Transferred into
Practice?; Gabriele Dreier, University Medical Center Freiburg
2:45 PM 06Clinical Trial Auditing in an Electronic World: Do Not Risk Your Data Validate Sufficiently; Jochen Dress, Clinical Trial Center Cologne
Session 1B: Dose Finding Trials ST
Moderator: Alexia Iasonos
1:30 PM 07A Simple Bayesian Decision Theoretic Design for Dose Finding
Trials; Ying Lu, Palo Alto VA and Stanford University
1:45 PM 08Interactive Software “Isotonic Design using Normalized Equivalent
Toxicity Score (ID-NETS)” for Cancer Phase I Clinical Trials;
Zhengjia Chen, Emory University
2:00 PM 09The Modified Toxicity Probability Interval (mTPI) Method for Phase I
Dose-Finding Trials; Yuan Ji, M. D. Anderson Cancer Center
2:15 PM 10Incorporating Patient’s Characteristics in Cancer Phase I Clinical
Trials Using Time to DLT: Escalation with Overdose Control;
Yuan Liu, Emory University
2:30 PM 11A Novel Statistical Software EWOC-NETS©TM for Extending Dose
Escalation With Overdose Control (EWOC) to Fully Utilize All Toxicities
in Cancer Phase I Clinical Trial; Zhibo Wang, Emory University
2:45 PM 12A Cox Regression Model with Isotonic Regressors with ChangePoint Problems: Addressing a Clinical Question; Das Purkayastha,
Novartis Pharmaceuticals
Session 1C: Randomized Trials ST
Moderator: Ying Qing Chen
1:30 PM 13The Long Road to Start Up RCTs within the Social Services
Interventions in Denmark; Maiken W. Pontoppidan, SFI - The Danish
National Center for Social Research
1:45 PM 14Elements of a Phase 3 IND Study Protocol – An FDA Statistical
Perspective; Renee C. Rees, FDA/CBER
Track Key
22
3:00 PM – 3:30 PM
2:00 PM 15 M
ust a Randomized Trial Focus on Hypothesis Testing? -- Assessing
Risks and Benefits of Withdrawal From Therapy When The Acceptable
Risk Margin is Unclear; Lisa M. Wruck, Collaborative Studies
Coordinating Center, University of North Carolina at Chapel Hill
2:15 PM 16Methods of Analyses for a Complex Intervention Cluster Randomised
Stroke Trial – Looking for the Goose that Lays The Golden Egg;
Ivana Holloway, Medical Statistician
2:30 PM 17 Does Using Minimisation Make A Difference?: Empirical Evidence
From Three Multi-Centre Studios; Marion Campbell, University of
Aberdeen
2:45 PM 18Futility Boundary Design Based on Probability of Success;
Yijie Zhou, Merck Research Laboratory
Session 1D: Information Technology IS/DM
Moderator: Scott Rushing
1:30 PM 19Online Study Monitoring for Large Multi-center Trials Via a Data
Dashboard; Ryan T. Bailey, Rho, Inc.
1:45 PM 20Technologies Supporting Clinical Research in Resource Poor
Settings; Marisa De Rosa, Cineca
2:00 PM 21Developing and Implementing a Laboratory Information System
(LIMS) to Support Trials in the United Kingdom; Jonathan Gibb,
University of Glasgow
2:15 PM 22The Development of a Safe Haven to Allow Access to Routinely
Collected Healthcare Datasets for Use in Clinical Trials;
Sharon M. Kean, University of Glasgow
2:30 PM 23Developing and Implementing Generic Components to Improve
Efficiency When Building Electronic Data Capture Systems for
Clinical Trials; Mary MacDonald, University of Glasgow
2:45 PM 24Collaborative Peer-reviewing and Data Aggregation in Site
Management With Clinicalsite.org; Gustav Vella, University of
Cologne, Clincal Trials Center (ZKS Köln)
Session 1E: Trial Monitoring ST, TM
Moderator: Milena Silverman
1:30 PM 25Cross Training Within a Clinical Research Organization: Does it Work
or Does it Muddy the Waters?; Nicole Close, EmpiriStat, Inc.
1:45 PM 26Is an Evolving Chart Audit Plan Necessary in a Long-Term
Multi-Center Trial?; Brenda K. Brewer, Westat
2:00 PM 27Central Statistical Monitoring in Clinical Trials; Erik Doffagne,
International Drug Development Institute (IDDI)
2:15 PM 28Risk-Based Approach to Monitoring: The Way of the Future;
Selma C. Kunitz, KAI Research, Inc
2:30 PM 29Effective Monitoring Strategies in a Long-term Clinical Trial with
Varying Levels of Clinic Staff Knowledge: The AREDS2 Experience;
Wendy L. McBee, The EMMES Corporation
2:45 PM 30Central Statistical Monitoring: A Model to Predict Fraud in Clinical
Trials; Janice M. Pogue, McMaster University
23
3:30 PM – 5:00 PM Invited Session 6: M, ST
Confusions and Controversies Around Pragmatic Trials
The term “pragmatic trial,” introduced by Daniel Schwartz and Joseph Lellouch [J Chron Dis 1967;20:637-48]
to designate a trial architecture designed to answer the practical question of whether offering an intervention in
the hurly-burly of routine health care does more good than harm, is receiving increasing attention as patients,
clinicians, organizers and payers for health services are increasingly clamoring for reliable and relevant answers
(e.g., the burgeoning programs of “Comparative Effectiveness” research). However, this increasing attention has
exposed considerable confusion and disagreement about whether pragmatic trials are “less perfect experiments”
than efficacy [explanatory] trials, whether permitting non-compliance and cross-overs is a “problem,” whether
knowing one’s treatment and telling examiners how one feels creates “bias,” and whether other departures from
the explanatory architecture achieve or undermine the stated goals of PCTs - to improve the value of clinical
research for clinical and health policy decision making. This 90-minute session will briefly refresh memories
about explanatory and pragmatic trial architectures and then present the views of those who are advocating more
pragmatic trials, those who carry them out, and those who criticize them.
Chair: David L. Sackett, Trout Research Centre
Speakers: Sean Tunis, Center for Medical Technology Policy
Lehana Thabane, McMaster University
James H. Ware, Harvard School of Public Health
3:30 PM – 5:00 PM Invited Session 7: IS/DM
Electronic Data Capture (eDC): One Size Does Not Fit All
Overview
This session will discuss the challenges in identifying appropriate eDC solutions when working across a range
of projects with different expectations, designs and budgets. This session will bring together four experts from
research organizations based in Australia, China, Europe and America. Each speaker will talk about their local
experience, the challenges faced and the eDC solutions they have adopted. This will include requirements for
accommodating academic and commercial trials, paper and electronic trials and very different needs in terms
of workflow and monitoring. Examples of trials will include studies in vulnerable populations such as remote
communities and emergency care patients.
Electronic Data Capture in an Academic Research Organization (Laurent Billot)
Academic research organizations (AROs) often run a mix of academic and commercial projects with different
needs, designs and especially budgets. From a pivotal Phase III commercial trial to a Phase IV investigatorinitiated trial with limited funds, it is difficult for a single EDC system to cater for all types of trials and one often
needs to have a portfolio of systems available. This talk will discuss the challenges in identifying and maintaining
a range of EDC systems and their impact on resources, training and costs.
Electronic Data Capture in Chinese Clinical Trials (Wei Li)
Despite the rapid development of drug & medical device clinical trials in China, most Chinese trials still use paper
CRFs. This is due in part to the lack of clear guidance from the SFDA and a considerable gap with developed
countries in data standardization and data management software. Lack of reliable internet access in remote
parts of the country also influences the use of electronic Data Capture. This talk will discuss the challenges
associated with the use of eDC in Chinese trials and the solutions adopted by the Chinese National Center for
Cardiovascular Diseases.
Track Key
24
Electronic Data Capture and Monitoring (Kit Roes)
Intensive on-site monitoring is a major cost driver for the clinical trial budget, generally taking up between 25%
and 30% of the total budget. Clinical research industries and regulatory bodies are now aiming to adopt riskbased monitoring strategies, making more use of remote (central) monitoring and relying less on intensive on-site
monitoring, especially for low-risk trials. In parallel, developments in electronic data capture have positioned data
management at the core of providing clinical trial teams with essential information to steer their trials. This talk
will explore different options for monitoring the quality of clinical trials via Electronic Data Capture systems and
its impact on the choice of EDC solution.
Electronic Data Capture and Workflow Flexibility (Kristine Nelson)
A trial design can be as simple as a one visit blood draw in a large teaching institute with state of the art
internet capacity to a protocol with multiple sites and multiple visits in remote areas with limited internet access.
In addition, we see trial designs requiring central laboratory assessment, integrated randomization, coding or
adjudication. From simple to complex requires an EDC system to be flexible enough for the workflow to be
designed to meet these vast differences in trial designs. We will discuss these challenges for the EDC system
and the data management staff.
Organizers: Laurent Billot and Wei Li
Chair: Laurent Billot
Speakers:
Laurent Billot – Director, Statistics and Data Management at the George Institute for
Global Health (Sydney, Australia)
Wei Li – Director and Professor, Medical Research Unit at the National Center for
Cardiovascular Diseases (Beijing, China)
Kit Roes – Professor of Biostatistics at the Julius Center for Health Sciences and
Primary Care (Utrecht, Netherlands)
Kristine Nelson – Project Director at the EMMES Corporation (Rockville MD, USA)
3:30 PM – 5:00 PM Invited Session 8: TM, ST
Methodological Challenges and Solutions for Late-Stage Clinical Trials
Many late-stage clinical trials frequently face methodological challenges in design, monitoring and analysis. Key
challenges, for example, may include the lack of a reliable surrogate marker for the primary clinical endpoint, the
need to provide risk-reduction counseling of uncertain benefit, and the difficulty of measuring and maintaining
adequate levels of product adherence and inadequate participant retention. This session intends to invite three
leading academic researchers to discuss these challenges and provide their guidance for possible solutions.
Organizer and Chair: Ying Qing Chen, Fred Hutchinson Cancer Research Center
Speakers: Victor De Gruttola, Harvard University
Jeffery Blume, Vanderbilt University
James Dai, Fred Hutchinson Cancer Research Center
3:30 PM – 5:00 PM Invited Session 9: ST
Phase II Oncology Trials: Recent Considerations in Trial Design and Endpoint
Selection
Recently there has been a lot of discussion about what are the appropriate designs and endpoints in Phase II
cancer clinical trials. Single arm designs, including the long-term staple, Simon’s two-stage design, have become
less popular because of concerns about the adequacy of historical controls, bias due to population selection,
and recent availability of a new class of molecularly targeted agents which do not necessarily shrink tumors,
but rather have different mechanisms leading to clinical benefit. The Clinical Trial Design Task Force of CTEP’s
Investigational Drug Steering Committee has encouraged greater use of randomization in monotherapy trials “to
25
optimize dose and schedule or to benchmark activity against known active therapies” and adopted the position
that “randomization is usually required for trials testing combinations of agents to establish efficacy” (Public
Summary, July 24, 2009). The editors of JCO have echoed these recommendations (Cannistra, JCO, 2009).
Many now agree that randomized Phase II designs are preferable, although they come with a host of problems of
their own, the most obvious one being prohibitively large sample size requirements. So, what is a biostatistician
to do? In this session, we will discuss the issues surrounding the design and endpoint selection in randomized
Phase II cancer trials; present feasibly-sized randomized designs which use continuous tumor size change and
progression-free survival endpoints, and hear the opinion of the JCO Statistical editors on the appropriateness
of these and other designs.
Organizer: Masha Kocherginsky, University of Chicago
Chair: Theodore Karrison, University of Chicago
Speakers: Daniel Sargent, Mayo Clinic
Karla Ballman, Mayo Clinic
Masha Kocherginsky, University of Chicago
James Dignam, University of Chicago
3:30 PM – 5:00 PM Invited Session 10: IS/DM
Common Data Elements in Clinical Research in Neurology
Many clinical trial datasets never materialize their full value because multiple data standards create barriers to
data sharing for meta-analysis and trial planning. However, the use of shared data standards can accelerate
clinical research. The NINDS Common Data Elements (CDE) Project has developed uniform standards by which
clinical research data can be systematically collected and shared across the research community.
The goals of this session are to disseminate the NINDS CDE Project and to introduce the general concept of
data sharing to the broad clinical trial community. Specifically, two speakers from the NINDS will introduce the
CDE Project and discuss its backdrop and implications; two investigators who have used the CDEs will share
their experience.
Organizer: Ken Cheung, Columbia University
Chair: Shing Lee, Columbia University
Speakers: Petra Kaufmann, Office of Clinical Research, National Institute of Neurological
Disorders and Stroke, National Institutes of Health
Joanne Odenkirchen, National Institute of Neurological Disorders and Stroke,
National Institutes of Health
Geoff Manley, University of California, San Francisco and the Brain and Spinal Injury
Center (BASIC)
Catherine Dillon, Medical University of South Carolina
6:30 PM – 8:00 PM
Track Key
Reception – Included with Meeting Registration
26
7:00 AM – 5:00 PM
Registration
8:00 AM – 5:00 PM
Exhibits
7:50 AM – 8:50 AM
Contributed Paper Sessions II
Session 2A: Cancer Clinical Trials ST, TM
Moderator: Meenakshi Devidas
7:50 AM 31Identifying Optimal Outcome Measures for Phase II Trials in Cancer;
Sarah R. Brown, University of Leeds
8:05 AM 32Experiences in Design and Implementation of Phase II Trials in
Chronic Lymphocytic Leukaemia; Dena R. Cohen, University of Leeds
8:20 AM 33Defining Clinical and Statistical Improvement in Consolidation or
Maintenance Single-arm Trials in Oncology; Alexia Iasonos, Memorial
Sloan Kettering Cancer Center
8:35 AM 34Did Death Certificates and a Mortality Review Committee Agree on
Lung Cancer Cause of Death in the National Lung Screening Trial?;
Pamela M. Marcus, National Cancer Institute
Session 2B: Data Standards and Data Exchange IS/DM
Moderator: Nicole Close
7:50 AM 35Challenges of Creating and Managing Standards (Common Data
Elements) for Use in Clinical Trials; Patti A. Shugarts, KAI Research,
Inc., an Altarum Company
8:05 AM 36Future of Data Exchange and Data Mining: Posting Data on the Grid
by a Dental Practice-based Research Network; Sherita Alai, The
EMMES Corporation
8:20 AM 37The Future of the caBIG® Clinical Trials Software Development
Mission: Engaging the Open Source Community;
Robert P. Annechiarico, Duke University
8:35 AM 38CDISC Data Standards Can Facilitate Composition of Adverse Event
Narratives; Anisa Scott, SAS Institute
Session 2C: Ethics of Clinical Trials M
Moderator: Emily Anderson
7:50 AM 39Actual Versus Reported Participant Consent Practices in Cluster
Randomized Trials: An International Survey of Trialists;
Shazia H. Chaudhry, Ottawa Hospital Research Institute
8:05 AM 40Post Trial Access to Successful Products: Ethical and Practical
Dilemmas; Liza Dawson, NIH/NIAID
8:20 AM 41Ethical Issues in Cluster Randomized Trials: International Survey of
Research Ethics Chairs; Monica Taljaard, Ottawa Hospital Research
Institute
8:35 AM 42Exception From Informed Consent (EFIC): Experiences from a
Randomized Trial in Pediatric Emergency Patients; Denise F. King,
EMMES Corporation
27
Session 2D: Safety Analysis ST
Moderator: Li Chen
7:50 AM 43Streamlined Drug Induced Liver Injury Detection with Hy’s Law and
Temporal Visualization; Kelci J. Miclaus, SAS Institute
8:05 AM 44Summarizing the Incidence of Adverse Events Using Volcano Plots
and Time Windows; Richard C. Zink, SAS Institute, Inc.
8:20 AM 45Reducing Surveillance Bias in Adverse Events Reporting in an
Unmasked Treatment Trial; Mae O. Gordon, Washington University
School of Medicine
8:35 AM 46Assessments for Safety and Efficacy in Cardiovascular Cell Therapy
Clinical Trials; Adam M. Mendizabal, The EMMES Corporation
Session 2E: Trial Conduct IS/DM
Moderator: Michele Straus
7:50 AM 47Shrinking the Global Village: The Challenges of Trial Management
in an International Multi-Centre Trial; Claire Cochran, University of
Aberdeen
8:05 AM 48The Use of Central IRBs for Multicenter Clinical Trials;
Devon K. Check, Duke University
8:20 AM 49Tracking of Regulatory Documents in a Large Clinical Trial, The AgeRelated Eye Disease Study 2 (AREDS2); Sherrie M. Schenning,
The EMMES Corporation
8:35 AM 50Electronic Health Record Systems for Medical Research Project
Stakeholder Management; Elizabeth Thomson, University of Glasgow
9:00 AM – 10:30 AM
Invited Session 11: TM
Update from the Clinical Trials Transformation Initiative: Rethinking Approaches to
Clinical Trial Oversight and Premarket Safety Management
The Clinical Trials Transformation Initiative continues to engage multiple sectors in projects seeking to improve
the quality and efficiency of clinical trials. This session will provide updates on projects that have been
rethinking approaches to clinical trial oversight and premarket safety management. Building on recommendations
presented at the 2011 SCT Annual Meeting on “Monitoring as a component of quality assurance in the conduct
of clinical trials,” one project has explored approaches to building quality into the scientific and operational
design and conduct of clinical trials by applying principles used in the manufacturing sector termed “quality by
design” and by developing risk-based “quality management plans.” These approaches are quite consistent with
recommendations in a new FDA draft guidance for industry issued in August 2011 titled “Oversight of Clinical
Investigations—A Risk-based Approach to Monitoring.” A speaker from the FDA will describe the risk-based
approaches proposed in that guidance and how monitoring might fit within a larger quality-by-design framework.
Another project has explored the management of premarket safety with the goal of promoting responsible
oversight of safety consistent with the intent of the FDA’s new premarket safety rule, effective March 28, 2011.
The project is reviewing current practices for assessing safety of a premarket product across all trials of that
product and for managing potential safety signals. A group of experts from multiple sectors will be convened to
discuss current practices and consider future approaches consistent with the FDA’s new rule, and a biostatistical
workgroup will consider methodological issues concerning the analysis of accruing safety information. During
this session, there will be time to interact with the panel regarding these 2 projects and CTTI’s approach to
influencing change.
Track Key
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Organizer: Judith M. Kramer, Duke University Medical Center
Chair:
Martin Landray, University of Oxford
Speakers: Leslie Ball, Center for Drug Evaluation and Research, U.S. Food and Drug
Administration
Patrick Archdeacon, Center for Drug Evaluation and Research, U.S. Food and Drug
Administration
Martin Landray, University of Oxford
Janet Wittes, Statistics Collaborative
9:00 AM – 10:30 AM
Developing Evidence-based Multistage Treatment Policies from Clinical Trials Data
Multistage treatment policies (also called dynamic treatment regimes) are time-varying, personalized decision
rules that allow individualizing the treatment to the patient. They offer a framework for operationalizing, and
thereby potentially improving, the adaptive clinical practice for many chronic disorders. In recent years, there has
been a surge of interest in this promising research area of tremendous methodological and practical appeal.
These treatment policies have found application in many health domains including oncology, HIV infection, mental
illnesses, substance abuse, and stroke prevention. This session presents four talks on design and analysis of
clinical trials data to develop evidence-based treatment policies.
Chair: Bibhas Chakraborty, Columbia University
Speakers: Bibhas Chakraborty, Columbia University
Eric Laber, North Carolina State University
Ying-Kuen (Ken) Cheung, Columbia University
Susan M. Shortreed, Group Health Research Institute
9:00 AM – 10:30 AM
Invited Session 13: IS/DM, ST
Open Source Statistical Software in Drug Development: Challenges and
Opportunities
Utilization of open source software, such as R and OpenBUGS, in clinical drug development conducted by the
biopharmaceutical industry is, by and large, limited to simulations for trial/program design and exploratory
analyses not included in regulatory submissions. A number of factors account for that, but chief among them
is the (incorrect) perception that open source software cannot be validated and, therefore, is not accepted by
regulatory agencies for analyses included in submission packages. Because research in statistical methodology
increasingly makes its way into software via the open source route, this perception creates further hurdles for the
utilization of novel statistical methods in an industry badly in need of innovative designs and analysis methods.
This session will discuss the challenges, perceived and real, to the broader utilization of open source software in
clinical drug development (not just in the biopharma industry, but also in NIH-sponsored trials), and opportunities
for addressing those challenges. It will feature speakers from the FDA, academia, and the biopharma industry
with practical experience with the use of open source software in drug development.
Organizer and Chair: José Pinheiro, Janssen R+D
Speakers: Mat Soukup, Center for Drug Evaluation and Research, U.S. Food and Drug
Administration
Kevin Buhr, University of Wisconsin
Keaven Anderson, Merck
Seth Berry, Quintiles
29
9:00 AM – 10:30 AM
Ethical, Regulatory and Recruitment Issues in Vulnerable Populations: Substance
Use Trials as a Case Study
Individuals with substance use disorders are considered vulnerable due to many factors, such as presenting with
co-occurring mental health disorders affecting cognitive functioning, being involved in the criminal justice system,
and suffering economic disadvantages and social stigma, among others. This session will describe ethical,
regulatory and recruitment issues when conducting clinical trials with individuals with substance use disorders.
Dr. Anderson will present evidence-based strategies for providing appropriate, effective research protections to
individuals and will also review evidence that suggests substance use populations may not be vulnerable in many
of the ways that researchers and IRBs often assume. Dr. Campbell will discuss challenges when individuals are
involved in the criminal justice system and present strategies currently used to address these challenges. Dr.
Miele will present innovative approaches to increase recruitment/retention as well as discuss regulatory and
human subject challenges when using current technologies for recruitment and retention purposes.
Chair: Carmen L. Rosa, National Institute on Drug Abuse
Speakers: Emily E. Anderson, Loyola University Chicago
Aimee N. C. Campbell, Columbia University
Gloria Miele, Columbia University College of Physicians and Surgeons
9:00 AM – 10:30 AM
Student Scholarship Presentations
In this session, students will present the papers selected as finalists in the Thomas Chalmers Scholarship
Program.
Kelley M. Kidwell Weighted Log-Rank Statistic to Compare Shared-Path Adaptive Treatment Strategies
Yunzhi Lin A Unified Method for Balancing Continuous and Categorical Baseline Covariates in
Randomized Clinical Trials
Wai Yin Yeung The Power of Covariate-Adaptive Randomization Schemes in Clinical Trials
10:30 AM – 11:00 AM
11:00 AM – 12:30 PM Invited Session 16: M, TM
Guidelines for the Ethical Conduct and Ethics Review of Cluster Randomized Trials:
Statement from an International Consensus Meeting
The cluster randomized trial (CRT) is used increasingly in knowledge translation research, quality improvement
research, community based intervention studies, public health research, and research in developing countries.
However, CRTs raise difficult ethical issues that challenge researchers, research ethics committees, regulators,
and sponsors as they seek to fulfill responsibly their respective roles. Funded by the Canadian Institutes of Health
Research, our multidisciplinary group conducted a four-year research project to study the ethical challenges in
CRTs. An international consensus meeting was held in Ottawa, Ontario from 28-30 November 2011, with the view
to generate consensus ethics guidelines for CRTs. In this session, we will present the Consensus Statement for
the Ethical Conduct and Ethics Review of CRTs coming out of the meeting, and invite comment and discussion
from the audience.
Organizer and Chair: Monica Taljaard, Ottawa Hospital
Speakers: Track Key
Monica Taljaard, Ottawa Hospital
Jeremy Grimshaw, Ottawa Hospital Research Institute
Charles Weijer, University of Western Ontario
Angela White, University of Western Ontario
30
11:00 AM – 12:30 PM Invited Session 17: IS/DM, TM
Mastering the Challenges: Academic Infrastructures for Clinical Trials in Europe
The clinical trials system needs to improve. Otherwise ‘the introduction of new treatments (…) will be delayed
and patient lives will be lost unnecessarily’.[1]
It typically requires years to design, review, and initiate Cooperative Group clinical trials. ‘In attempting to optimize
the effectiveness and safety of trials, proposals often are redrafted and recycled by multiple stakeholders from
academic institutions, federal agencies, institutional review boards, and industry. This results in frustration and
a perception that stakeholders are working at crosspurposes.’[1]
An adequate process for prioritizing trials and selecting those most likely to be successful is lacking. Slow
accrual of patients is often the result. A large number of trials is not completed and published, ‘which is a terrible
waste of human and financial resources.’[1]
Funding for Cooperative Group clinical trials is often inadequate. ‘As much as half of the cost of clinical trials
today are borne by the clinical investigators and clinical care providers who design and carry out these important
studies. Almost universally, investigators are compelled to seek supplemental support from outside sources,
such as pharmaceutical companies.’[1] In addition the cost increases because biomarkers are more often used
to predict and monitor appropriate therapy.[1]
In Europe the Fragmentation of the health and legislative systems and funding sources represent other
bottlenecks to multinational collaboration[2]. To take advantage of its population size, and to unlock the full
scientific potential the European Union has funded an increasing number of multinational clinical trials. In
addition, the Union and its Member States invest significant resources to create and maintain the European
Clinical Research Infrastructures Network (www.ecrin.org)[2].
In this session we will look at the challenges we all face and present and discuss European concepts to master
them in a world where ‘research infrastructures are becoming increasingly diverse and distributed over various
sites and are increasingly interconnected and supported by e-Infrastructures.’[3]
[1] National Academy of Sciences: IOM: A National Cancer Clinical Trials System for the 21st Century: Reinvigorating the NCI
Cooperative Group Program
[2] A European perspective – the European clinical research infrastructures network, J. Demotes-Mainard & C. Kubiak, Annals of
Oncology 22 (Supplement 7): vii44–vii49, 2011
[3] ESFRI: Strategy Report on Research Infrastructures - Roadmap 2010
Chair: Jochen Dress, University of Cologne
Speakers: Jacques Demotes, European Clinical Research Infrastructures Network, INSERM,
Institut Thématique Santé Publique
Jochen Dress, University of Cologne
Cornelius Schmaltz, Directorate General for Research and Innovation, European
Commission
11:00 AM – 12:30 PM Invited Session 18: M, ST
Data and Safety Monitoring Board (DSMB) Roles in Adaptive Design Trials
Adaptive designs have been commonly used in modern clinical trials. Many of them have a DSMB to review
certain unblinded data before making modifications to the ongoing trial. Typically the interim decision/
recommendation will follow a pre-determined decision rule in the protocol or DSMB charter. However, the DSMB
often has liberty to deviate from the decision rule if the committee thinks that is in the best interest of patients/
subjects. Sometimes the decision rules can be more subjective for non-pivotal trials. DSMBs will always face the
question regarding how the decision/recommendation will affect the rest of trial conduct and interpretation of
the trial results. This session will discuss practical and logistical issues of DSMB operations in adaptive design
trials such as (but not limited to) whether and how the DSMB should be formed; what information and restrictions
31
should the DSMB have before and during a trial; how the DSMB reviews and makes recommendations; how to
deal with unanticipated interim outcomes, and what the potential regulatory implications may be, etc.
Organizers: Xiaoyin Frank Fan, Vertex Pharmaceuticals
Dave DeMets, University of Wisconsin-Madison
Speakers: Sue-Jane Wang, U.S. Food and Drug Administration
Jerry Schindler, Merck & Co.
Bruce Turnbull, Cornell University
Discussant: Dave DeMets, University of Wisconsin-Madison
11:00 AM – 12:30 PM Invited Session 19: ST
A Centennial Celebration of Jerome Cornfield and His Contributions to Clinical Trials
Jerome Cornfield was born in New York City in 1912. With no further academic degree than a B.A. in history, he
became a leading figure in the statistics of medical research, with a substantial focus on the methodology of
clinical trials. Jerry spent many years at the National Institutes of Health, first in the National Cancer Institute
and later at the then-National Heart Institute. He was an early proponent of the use of Bayesian and likelihoodbased methods in clinical trials, and recognized the need for statistical tools to facilitate interim decision-making
when monitoring accumulating data. He was among the first to discuss randomization by group rather than by
individual for certain types of applications. Jerry’s knowledge, wisdom and humor were widely appreciated and he
served the worlds of clinical trials, medical research, and statistics in many ways. He was elected Vice President
of the American Heart Association, and President of the American Statistical Association. He chaired an FDA
statistical committee to advise the FDA on difficult statistical issues during an era when statisticians did not
serve on individual FDA advisory committees. He was an active participant in the yearly meetings of researchers
discussing clinical trials methods, held in the mid-1970s, that led to the formation of the Society for Clinical
Trials the year following his death in 1979 from pancreatic cancer. Throughout his professional lifetime and for
many years thereafter, his perspective was routinely noted (“Jerry always says…”) to provide incontrovertible
support of a methodological position.
Each speaker will comment on Cornfield’s contributions in a specific area in addition to describing developments
in this area to the present day.
Organizer and Chair: Susan S. Ellenberg
Speakers: John Lachin, The George Washington University
Joel Greenhouse, Carnegie Mellon University
Janet Wittes, Statistics Collaborative
Robert O’Neill, U.S. Food and Drug Administration
11:00 AM – 12:30 PM Invited Session 20: M
Randomized Trials in Pregnant Women
Randomized trials in pregnancy are unique in that each subject comprises two individuals: the pregnant woman
and her fetus. Both individuals are considered to be “vulnerable” according to regulatory guidance. Though
pregnancy does not in itself diminish decision-making capacity, special consideration is often warranted. The
woman is being asked to make a decision in the context of great physiological complexity concern about the
outcome of the pregnancy, and usually a paucity of data regarding safety and efficacy of interventions. The fetus
lacks autonomy, yet its experience before birth can have lasting consequences for its future. Risks and benefits
are not equivalent for mom and baby – treatments tested can range from those with potential benefit only for
the mother to those with potential benefit only to the fetus. The speakers will discuss the importance and
Track Key
32
challenges of trials in pregnant women, including informed consent issues, balancing risk, and other trial design
and analysis issues applicable to this group.
Organizers:
Elizabeth Thom, The George Washington University Biostatistics Center
Mary Foulkes, The George Washington University Biostatistics Center
Speakers: George Saade, University of Texas Medical Branch, Galveston
Ben Willem Mol, University of Amsterdam
Anne Drapkin Lyerly, University of North Carolina, Chapel Hill
Discussant: Catherine Spong, National Institute of Child Health and Human Development
12:30 PM – 1:50 PM
Lunch/SCT Business Meeting – Included with Meeting Registration
1:50 PM – 2:50 PM
Contributed Paper Sessions III
Session 3A: Biomarkers ST
Moderator: Masha Kocherginsky
1:50 PM 51Exploratory Biomarker Analysis for Randomized Phase 2 Oncology
Trials; Hongjie Deng, Amgen Inc.
2:05 PM 52Leveraging Enrichment Design Methods to Improve the Likelihood
of Success of Clinical Trials; Imogene M. Grimes, Otsuka
Pharmaceutical Development & Commercialization, Inc.
2:20 PM 53Survey of Commonly Used Analytical Methods for Analyzing
Biomarkers with Limit of Detection; Tulay Koru-Sengul,
University of Miami Miller School for Medicine
2:35 PM 54A Phase II Design with Direct Assignment Option for Initial Marker
Validation; Ming-Wen An, Vassar College
Session 3B: Patient Recruitment, Enrollment and Retention TM
Moderator: Robert Lindblad
1:50 PM 55Use of a Formal Study Run-in Phase to Reduce Recruitment Errors in a
Multi-centre Randomized Controlled Trial: Is Quality Better Than Quantity?;
Gordon S. Doig, Royal North Shore Hospital, University of Sydney
2:05 PM 56 Patients and Clinical Trials: How to Improve Their Participation?;
Carlo Tomino, Italian Medicines Agency
2:20 PM 57Recruiting Patients for an Interdisciplinary, Multi-center International
Randomized Clinical Trial: Barriers and Strategies, Bypass Angiographic
Revascularization Investigation 2 Diabetes Trial (BARI 2D);
Lisa D. Mighton, University Health Network/Toronto General Hospital
2:35 PM 58 How Effective are Patient Information Leaflets? A Framework and
Methods for Evaluation; Nicola McCleary, University of Aberdeen
Session 3C: Reporting of Clinical Trials TM, M
Moderator: Monica Taljaard
1:50 PM 59Development of a Taxonomy to Facilitate Reporting of Behavior
Change Techniques, The Active Ingredients’ of Behavior Change
Interventions; Nicola McCleary, University of Aberdeen
2:05 PM 60Which Components of Interventions are Reported in Titles and
Abstracts? A Systematic Review to Compare Reporting Practices for
Pharmacologic and Non-pharmacologic Interventions;
Nicola McCleary, University of Aberdeen
33
2:20 PM 61Failure to Report Protocol Violations in Clinical Trials: A Threat
to Internal Validity?; Elizabeth A. Sweetman, Royal North Shore
Hospital, University of Sydney
2:35 PM 62The COMET (Core Outcome Measures in Effectiveness Trials)
Initiative; Elizabeth Gargon, University of Liverpool
Session 3D: Statistical Methods and Trial Design ST
Moderator: Valerie Durkalski
1:50 PM 63The Use of Bayesian Predictive Distribution in Clinical Trials;
Bo Yang, Merck Research Laboratories
2:05 PM 64Formal Methods for Determining Sample Size- Survey of SCT
Membership; Jonathan A. Cook, University of Aberdeen
2:20 PM 65Adaptive Designs for Clinical Comparative Effectiveness Research:
Are We Ready?; John A. Kairalla, University of Florida
2:35 PM 66Perception and Use of Adaptive Designs in the Industry and
Academia: Persistent Barriers and Recommendations to Overcome
Challenges; Caroline C. Morgan, Cytel, Inc.
Session 3E: Vulnerable Populations M, TM
Moderator: Carmen Rosa
1:50 PM 67Challenges of Collecting Health Data and Maintaining Contact with
an Aging Study Population; Jo Ann L. Hartline, Cancer Research And
Biostatistics
2:05 PM 68Extended Follow-up in Multi-phase Clinical Trials;
Katherine Trigiani, Sunnybrook Research Institute
2:20 PM 69Issues to Consider in the Set-up of Complex Intervention Trials in
Vulnerable Populations; Shamaila Anwar, University of Leeds
2:35 PM 70Designing Clinical Trials for Testing Disease-modifying Agents on
Alzheimer’s Disease; Chengjie Xiong, Washington University
2:50 PM – 3:20 PM
3:20 PM – 4:50 PM
Invited Session 21: M
Translational Behavioral Science: A Framework to Guide the Development of
Health-related Behavioral Interventions
Our ability to improve health-related behaviors, such as physical activity and dietary patterns, is enhanced by our
understanding of the fundamental bases of human behavior and the translation of that knowledge into effective
interventions. In drug development, research concerned with the development and testing of interventions is
labeled “bench to bedside” or Translational research. Translational research begins with basic research to
identify mechanisms and intervention targets, proceeds to the conduct of small-scale human trials to assess
safety and optimal dosing, and includes pilot studies to assess feasibility and provide estimates of yield and
effect. These early phases of therapy development are followed by large-scale, Phase III clinical trials that test
the effects of the treatment on the health outcomes of interest. This paradigm is well-accepted in the biomedical
arena; however, no such widely accepted paradigm exists for guiding the development of health-related behavioral
interventions. In this symposium, members of the NIH-sponsored ORBIT (Obesity Related Behavioral Intervention
Trials) consortium, which aims to develop new approaches to reducing obesity based on basic behavioral science
research, will first present a framework that can be used to guide the development of health-related behavioral
interventions, followed by a description of the aims, study designs and methodological approaches of two ORBIT
projects that are using this framework to develop innovative obesity-related interventions. One project uses a
Track Key
34
series of qualitative, epidemiologic and proof-of-concept studies to develop a multi-level intervention to reduce
the progression of visceral fat in women undergoing menopause. The other utilizes a sequential randomized
assignment trial and qualitative analysis to design and test an intervention to promote weight loss in obese
African American adolescents. The discussant will comment on needs and opportunities in basic and translational
behavioral science research and highlight NIH’s role in supporting Translational behavioral science.
Organizers & Chairs: Susan Czajkowski, National Heart, Lung, & Blood Institute, National Institutes of Health
Lynda Powell, Rush University Medical Center
Speakers: Susan Czajkowski, National Heart, Lung, & Blood Institute, National Institutes of
Health -- Overview of a Framework to Guide Health-related Behavioral Intervention
Development
Lynda Powell, Rush University Medical Center -- WISHFIT: Women In the Southside
Health Project - FITness Studies
Sylvie Naar-King, Wayne State University -- Interventionist Procedures for Adherence
to Weight Loss Recommendations in Black Adolescents
Discussant: Robert Kaplan, Office of Behavioral & Social Sciences Research, National Institutes
of Health
3:20 PM – 4:50 PM
Invited Session 22: IS/DM
Registration and Reporting of Clinical Trials: Key Informatics Issues and Trends
Following the invited session “Reporting of Clinical Trial Results at Clinicaltrials.Gov: Key Scientific Issues” at
SCT 2011, this session is intended to highlight informatics approaches to the reporting of clinical trial results,
not just at clinicaltrials.gov but also in two key reporting initiatives within the National Cancer Institute.
The Food and Drug Administration Amendments Act of 2007 (FDAAA) expanded clinical trial registration
and results reporting requirements in clinicaltrials.gov and made them mandatory for the first time. These
requirements have increased in parallel with requirements of public sector study sponsors, such as the National
Cancer Institute, both of which are occurring at a time when the budgets of academic medical centers are under
considerable pressure.
This session will examine the current and potential future registration and reporting requirements both of
clinicaltrials.gov and of the National Cancer Institute’s Clinical Trials Reporting Program. Emphasis will be placed
on opportunities that have been taken, and future opportunities that could be taken, to streamline the reporting
process and to minimize duplicative reporting requirements.
Another aspect of clinical trials reporting is NCI’s longstanding expedited reporting requirements for serious
adverse events in clinical trials. Recent developments to automate this process will be discussed. Representatives
both of government sponsors and academic sites will present their experience in managing and responding to
these requirements and challenges.
Organizer and Chair: John Speakman, National Cancer Institute, National Institutes of Health
Speakers and Discussants:
Jose Galvez, National Cancer Institute, National Institutes of Health
Charles Hurmiz, St. Jude Children’s Research Hospital
David Patton, National Cancer Institute, National Institutes of Health
Kim Johnson, Alliance for Clinical Trials in Oncology, Duke University Medical Center
Deborah Zarin, ClinicalTrials.gov
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3:20 PM – 4:50 PM
Increasing Clinical Program Success with Modeling and Simulation
The fact that regulators have been leading the effort to modernize clinical trial design has spurred interest in
industry and academia. Improving the development strategy by taking into account data from early development
and applying innovative statistical methods is one of the major objectives for biostatisticians designing and
supporting clinical programs. Modeling and simulation approaches can help to optimize an individual trial, to
see the benefit of novel designs, and to increase success of a clinical program by making better decisions while
developing a drug. In this session, presenters from academia, the pharmaceutical industry, and CROs will share
their experience and ideas on how modeling and simulation can increase clinical program success and enable
study and program teams to make better decisions through the process. Simulated case studies and examples
from real trials will be used to motivate and illustrate the key ideas.
Organizer & Chair: Olga Marchenko, Quintiles
Speakers: Don Berry, MD Anderson Cancer Center
Russell Reeve, Quintiles
Discussant: Tom Parke, Tessella Technology & Consulting
3:20 PM – 4:50 PM
Safety Evaluation with Clinical Trial Information and Postmarketing Data
Proactive planning of safety evaluation is an essential part of clinical drug development. The drug safety evaluation,
however, can be very different from the efficacy evaluation, primarily due to small treatment differences on safety
measures as well as varying safety risk over time. Such differences pose new challenges using clinical trial
information for drug safety evaluation. Handling the challenges requires the understanding of possible safety
issues, the limitations of clinical trials, careful strategies in handling data, and innovative statistical methods.
The understanding of a drug’s safety profile from clinical trials is limited by several factors. These factors include
but are not limited to the study of selected populations of limited size compared to wide distribution in the
public, protocol-driven drug use and monitoring compared to unsupervised use, and short evaluation times in
clinical trials compared to use in the general population. To avoid serious consequences to the public health it
is necessary to continue safety monitoring and evaluation after the marketing of the drug.
In this session, clinicians and statisticians will jointly address the following:
• Program safety analysis plan (PSAP) including the timing and framework, principles for safety data
collection, and experience in developing the PSAP intended to advance the way clinical trial safety data are
prospectively collected, analyzed and presented.
• Statistical methods on handling rare events, quantify the small risk (sample size in evaluating small risk
and confidence level to exclude the small risk) and how to handle risk changes over time.
• Issues in assessing postmarketing data (typically noncontrolled), current tools and data sources available
to FDA for postmarketing evaluation of adverse events, and initiatives to explore postmarketing data to
maintain an ongoing understanding of drug safety issues as they happen.
Organizers: Li Chen, Amgen
Qian Li, National Center for Complementary and Alternative Medicine, NIH
Chair: Li Chen, Amgen, Inc.
Speakers: James Kaiser, U.S. Food and Drug Administration
Seta Shahin, Amgen
Qian Li, National Center for Complementary and Alternative Medicine, NIH
Discussant:
Track Key
Joan Hu, Simon Fraser University
36
3:20 PM – 4:50 PM
Invited Session 25: TM
Coordination and Conduct of Phase III Emergency Treatment Trials
This session will examine the coordination and conduct of large multicenter emergency care trials using a recently
completed Phase 3 trial as a case study. The Rapid Anticonvulsant Medication Prior to Arrival Trial (RAMPART)
was a double-blind, randomized, controlled, non-inferiority clinical trial designed to compare the efficacy of
intramuscular midazolam versus intravenous lorazepam in the pre-hospital treatment of status epilepticus. The
emergent nature of the disease inherently created special requirements for the coordination and conduct of the
trial including: exception from informed consent, randomization in the ambulance, training of paramedics, tracking
of study drug packages, and data management, project management, and regulatory management issues.
Organizer: Wenle Zhao, Medical University of South Carolina
Speakers: Valerie Durkalski, Medical University of South Carolina or Robert Silbergleit,
University of Michigan
Deneil Harney, University of Michigan
Catherine Dillon, Medical University of South Carolina
5:00 PM – 6:20 PM
Plenary Session I: In Memory of Paul Meier/Trial of the Year
Theodore Karrison, SCT Secretary
University of Chicago
6:30 PM – 7:30 PM
Affinity Group Receptions – Included with Meeting Registration
• Information Technology
• Clinical Research Associates
• MD Clinical Trialists
• Members of Industry or FDA
• Trialists Practicing in Europe
37
7:00 AM – 11:00 AM
Registration
8:00 AM – 9:30 AM
Invited Session 27: IS/DM, M, ST
A Real-time Electronic Remote Data Capture and Therapeutic Risk Group
Communication System: From Central Laboratories to Individual Patient Treatment
in Pediatric Cancer Clinical Trials
The Children’s Oncology Group (COG) has complex classification systems in place for pediatric clinical trials,
including those for acute lymphoblastic leukemia and neuroblastoma. Classification of patients is based
on biological, clinical, and genomic data obtained at initial diagnosis/during therapy. The COG web-based
remote data entry (RDE) system enables submission of data in real time from central laboratories and treating
institutions. The use of RDE technology, including an automated risk-assignment algorithm that triggers an email
to the patient’s treating institution, permits much more rapid determination and delivery of the appropriate
level of therapeutic intensity to an individual patient enrolled in a clinical trial than ever before. This approach
is applicable to any disease where therapy varies on the basis of factors identified at baseline or early therapy,
and will be useful in adult cancer in the near future with the advent of prognostic and targeted genomic factors.
Organizers: Meenakshi Devidas, University of Florida
Wendy B. London, Harvard Medical School
James R. Anderson, University of Nebraska College of Public Health
Chair: Meenakshi Devidas, University of Florida
Speakers: James R. Anderson, University of Nebraska College of Public Health
Wendy B. London, Harvard Medical School
Meenakshi Devidas, University of Florida
Discussants: Karla Ballman, Mayo Clinic
8:00 AM – 9:30 AM
Response-Adaptive Treatment Allocation in Clinical Trials: The Costs and Benefits
Response adaptive randomization (RAR) was originally proposed based on study subject ethical considerations.
Early implementation of RAR using the Play the Winner (PW) or Random Play the Winner (RPW) algorithm resulted
in allocation ratios with wide variations. Optimal target allocation ratios aim to minimize the total number of
failures or to maximize the statistical power, but often end with an allocation ratio close to the equal allocation.
The implementation of RAR requires a procedure to ensure that the target allocation ratio is achieved with a
small variation and the treatment groups are compatible with regards to baseline characteristics. This needs to
be balanced with joint considerations of study subject ethics and trial operation. In this session, the speakers
will share their opinions and experiences in the design and implementation of RAR in large multicenter clinical
trials, with the goal of providing suggestions on the selection and implementation of RAR based on operation
issues in clinical trial practice.
Organizer: Valerie Durkalski, Medical University of South Carolina
Speakers: Wenle Zhao, Medical University of South Carolina
Ying Yuan, University of Texas MD Anderson Cancer Center
Oleksandr Sverdlov, Bristol-Myers Squibb
Discussant: Sue-Jane Wang, Center for Drug Evaluation and Research, U.S. Food and Drug
Administration
Track Key
38
8:00 AM – 9:30 AM
Invited Session 29: ST, TM
Emerging Issues and Their Solutions in the Implementation of Adaptive Designs in
Clinical Trials
Adaptive designs represent a new technology in drug development. These designs have an impact on drug
development strategies, clinical trial management systems and clinical data management systems. Adaptive
design will also change enrollment, EDC/IV(W)RS, drug supply management, DMC operating procedures, trial
protocols, informed consent forms, and data analysis plans. In this session, we will discuss the emerging issues
associated with adaptive clinical trials and present the latest solutions for their successful implementation:
controlling flexible randomization and optimizing the quantities of required drug supplies, expanding role and
broader responsibility of DMC, and a fully integrated adaptive execution environment, with a particular focus on
maintaining validity and integrity of the trial.
Chair: Vlad Dragalin, Aptiv Solutions
Presenters: Olga Kuznetsova, Merck Sharp & Dohme Corp.
Paul Gallo, Novartis Pharmaceuticals
Judith Quinlan, Aptiv Solutions
8:00 AM – 9:30 AM
Dealing with Treatment Compliance in Clinical Trials on Inherently Low-Compliant
Populations: What to do at the Design, Monitoring and Analysis Stages
Ensuring treatment compliance is difficult in general. Particular difficulties are found in vulnerable populations, such
as those with substance abuse disorders. A very low treatment compliance rate, common in such populations,
can render a clinical trial worthless. We’ve heard physicians say “if they don’t take their medication, they can’t
get better”. In a clinical trial context, one can similarly say “if they don’t take their medication, we cannot find
out whether it is effective”. It is therefore important to design a clinical trial to maximize compliance, monitor
the trial to assess the actual compliance level, and analyze its data in a way that minimizes the detrimental
impact of poor treatment compliance. This session will provide some answers to the following critical questions
on treatment compliance at these important stages of a clinical trial:
(1) How best to design a study to maximize medication or psychosocial treatment compliance? What are
successful (and unsuccessful) trial design strategies for improving compliance? Are clinical trials where
compliance is so low worth doing? At what compliance level does a trial become useless?
(2) What are participants telling us about the barriers that affect compliance?
(3) What are available technologies and methods to maximize compliance? How best to monitor to ensure
compliance?
(4) How best to analyze the data in the presence of less-than-perfect treatment compliance? Which should be the
primary analysis: intent-to-treat, “completers,” or something else? What are the pros and cons?
Organizers: Paul Wakim, National Institute on Drug Abuse, National Institutes of Health
Michele Straus, National Institute on Drug Abuse, National Institutes of Health
Chair:
Speakers: Paul Wakim, National Institute on Drug Abuse, National Institutes of Health
Lawrence M. Friedman, Consultant to National Institutes of Health
Viviana Horigian, University of Miami Miller School of Medicine
Michele Straus, National Institute on Drug Abuse, National Institutes of Health
James Rochon, Rho Inc.
39
9:45 AM – 11:15 AM Contributed Paper Sessions IV
Session 4A: Clinical Epidemiology M, ST
Moderator: Yves Rosenberg
9:45 AM 71Soundness of Evidence Derived from Meta-analysis of High Quality
Observational Studies: A Case in Cardiology;
Catherine Klersy, IRCCS Fondazione Policlinico San Matteo
10:00 AM 72Using Meta-Synthesis of Three Randomized Controlled Trials in
Colorectal Cancer (CRC) Screening to Inform Assumptions on
Natural History of CRC in Microsimulation Modeling;
Ann G. Zauber, Memorial Sloan-Kettering Cancer Center
10:15 AM 73Combining Randomized and Observational Data Using Network
Meta-Analysis to Explore Drug Safety: The Case of Antifibrinolytics in
Cardiac Surgery; Brian Hutton, Ottawa Hospital Research Institute
10:30 AM 74The Publication of Preclinical Evidence Supporting Translation of
New Drugs: An Empirical Analysis; Carole Federico, McGill University
10:45 AM 75 Can Exercise Enhance Smoking Cessation Outcomes? A Pragmatic
Randomized Controlled Trial (Fit2Quit Study);
Yannan Jiang, The University of Auckland
11:00 AM 76Group-Based Trajectory Models in a Clinical Study in Nutrition;
Yassin Mazroui, Université Bordeaux Segalen, INSERM U897,
ISPED, Bordeaux Cedex F-33076
Session 4B: Data Management IS/DM
Moderator:
9:45 AM 77The Life Study Outcomes Management Tool; Lea N. Harvin,
Wake Forest University School of Medicine
10:00 AM 78Improving Data Quality Using Quality Improvement; Daniel Jeffers,
Cincinnati Children’s Hospital Medical Center
10:15 AM 79Streamlining Data Collection and Flow for Central Units in Large
Multi-Center Clinical Trials; Pam Mangat,
George Washington University
10:30 AM 80Design of a Comprehensive Rule-based, Real-time Data Validation
Function in a Web-based Clinical Trial Management System;
Keith H. Pauls, Medical University of South Carolina
10:45 AM 81Survey of the Current Beliefs and Attitudes of the Canadian Critical
Care Trials Group Regarding Source Data Verification;
Roxanne Ward, Children’s Hospital of Eastern Ontario Research
Institute
11:00 AM 82Reproducible Research and Clinical Trials;
Paul A. Thompson, Sanford Research/USD
Track Key
40
Session 4C: New Opportunities in Data Capture IS/DM
Moderator: Lauren Billot
9:45 AM 83The Use of Ancillary Data Capture Systems in Clinical Trials;
Colleen C. Allen, The EMMES Corporation
10:00 AM 84Electronic Patient Reported Data for Risk Screening in Primary Care
Clinics using OpenClinica and CDISC ODM; Cal Collins, OpenClinica
10:15 AM 85Implementation of Digital Pen Technology to Capture Clinical Trial
Data; Nicole Close, EmpiriStat, Inc.
10:30 AM 86Responding to the Growing Need for Alternative Platforms for
Collecting Clinical Research Data; Milena Silverman,
Memorial Sloan-Kettering Cancer Center
10:45 AM 87Challenges and Implications of Patient Reported Clinical Outcomes
for Randomised Controlled Trials; Suzanne Breeman,
University of Aberdeen
11:00 AM 88Electronic Patient-Reported Outcome (ePRO) Assessment in Clinical
Trials: Strategies for Preserving Statistical Power; Antonia Bennett,
Memorial Sloan-Kettering Cancer Center
Session 4D: Statistical Methods ST
Moderator: John Kairalla
9:45 AM 89Randomized Decision Designs when the Number of Available
Subjects Precludes a More Standard Study Design;
James Anderson, U Nebraska College of Public Health
10:00 AM 90Bio-Creep Under Serial Use of Non-inferiority Trials Designed for
Preservation of Effect; Katherine S. Odem-Davis, Fred Hutchinson
Cancer Research Center
10:15 AM 91Standard Deviation Choice and Sample Size Calculation in Clinical
Trials; Henian Chen, University of South Florida
10:30 AM 92Measurement Issues in the Hamilton Rating Scaled for Depression
May Conceal Positive Findings in Clinical Trials for Major
Depression; Chengwu Yang, Pennsylvania State University College of
Medicine
10:45 AM 93Lasso Tree for Cancer Stage Grouping; Yunzhi Lin,
University of Wisconsin - Madison
11:00 AM 94Some Strategies for Defining Non-Inferiority Bounds in ActiveControlled Trials with No Placebo-Controlled Data for the Active
Comparator; Aditi Sapre, Merck Research Laboratories
41
Session 4E: Recent Trends in Trial Design ST
Moderator: Elizabeth Thom
9:45 AM 95Use of Routinely Collected Data Within Primary Care Medical Centrebased Trials; Nicola Greenlaw, University of Glasgow
10:00 AM 96 Routine Data – Is it Good Enough for Trials?; Alex M. Wright-Hughes,
Leeds University
10:15 AM 97Contemporary Clinical Research in Adult Cardiovascular Medicine:
A Perspective from ClinicalTrials.gov; David F. Kong,
Duke Clinical Research Institute
10:30 AM 98The Clinicaltrials.gov Results Database as a Resource for Designing
Clinical Trials; Elizabeth C. Wright, NIDDK/NIH
10:45 AM 99Supplementing the Design of Comparative Binary Outcome Trials
with Sequential Meta-Analyses; Mireya Diaz, Henry Ford Hospital
11:00 AM 100Developing Stop-Go criteria for Pilot / Feasibility Studies to Continue
to Full Trials; John Norrie, University of Aberdeen
11:15 AM – 11:30 AM
Break
11:30 AM – 12:30 PM
Founders Lecture – John P.A. Ioannidis
“Designing and Dissecting the Geometry of Randomized Evidence”
Director of the Stanford Prevention Research Center
42
Poster Presentations
Poster Presentation Monday, May 21, 2012, 8:30 AM – 5:00 PM
Prime Time 10:15 – 10:45 AM and 3:00 – 3:30 PM
P01 Working with At-Risk Populations; Allison Caban-Holt, University of Kentucky
P02 Interobserver Reliability of Tongue Diagnosis Using Traditional Korean Medicine for Stroke Patients; Mi Mi Ko,
Korea Institute of Oriental Medicine
P03 Factors that Affect Men’s Feelings About Their Urination: Findings from a Multi-center Clinical Trial of
Phytotherapy to Treat Lower Urinary Tract Symptoms; Alan B. Cantor, University of Alabama Birmingham
P04 Compliance Assessment for Eligibility in a 1-Year-Long Ophthalmic Clinical Trial Investigating Eye Drops;
Talat Almukhtar, Jaeb Center for Health Research
P05 Strategies Implemented to Ensure Data Accuracy for Final Analysis; Kathryn E. Mangoff, Sunnybrook Research
Institute
P06 Integration of Data Management Systems for Large International Randomised Controlled Trials; Michael X. Shi,
Sunnybrook Research Institute
P07 Improving Data Management Through Data Transfer; Janice C.H. Kwok, Sunnybrook Health Sciences Centre
P08 Adjudicating Life Study Outcomes through the Outcome Management Tool; Lea Harvin, Wake Forest University
Health Sciences
P09 Implementation of a Drug Management Utility in a Multi-Site, Randomized, Double-Blinded Study;
Jennifer McCormack, The EMMES Corporation
P10 Conquering the Challenges of Conducting a Trial’s Central Initial Training at an O’Hare Hotel: The Blood Pressure
in HemoDialysis (BID) Pilot Study Experience; Kimberly A. Wiggins, Cleveland Clinic
P11 Integrating Data from Disparate Sources into a Central Database in Trial with Hybrid Funding: The Blood Pressure
In HemoDialysis (BID) Pilot Study; Jennifer J. Gassman, Cleveland Clinic
P12 The Italian Register for Clinical Trials; The “Unique” E-access for Regulatory, Submission and Management of
Clinical Trials; Carlo Tomino, Italian Medicines Agency
P13 An Efficient and Inexpensive System for the Distribution and Tracking of Investigational Medicinal Products in
Clinical Trials; Patrick G. McDonnell, University of Dundee, Dundee, UK
P14 Gynecolgic Oncology Group (GOG): Making A Web-Based Cardiff Teleform Generated PDF Patient Clinical Reporting
Form Dynamic with the Use of Adobe FDF Files; Karen Puehn, Gynecologic Oncology Group Statistical & Data
Center
P15 Eosinophilia as a Potential Surrogate for Definitive Diagnosis of Strongyloidasis in an Immigrant Population at a
Community Clinic; Kathryn E. Spates, SAIC-Frederick, Inc.
P16 Posting Study Results to Clinicaltrials.gov: Effective Tools and Lessons Learned; Elizabeth Paynter, Rho
P17 Changing Directions in the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial – Involving
Outside Investigators in Manuscript Preparation and Ancillary Studies; Sara L. Pressel, University of Texas School
of Public Health
P18 The Global Obstetrics Network (GONet): An International Collaborative Group; Elizabeth A. Thom, The George
Washington University
P19 Estimating Death Rates in Substance Use Disorder Clinical Trials; Robert W. Lindblad, The EMMES Corporation
P20 Statistical Considerations for Analysis of Progression-Free Survival Data; Imogene M. Grimes, Otsuka
Pharmaceutical Development & Commercialization, Inc.
P21 A Study of Autologous Valve Replacement - CD133+ Stem Cell-Plus-Fibrin Composite Based Sprayed Cell Seeding
for Intra-Operative Heart Valve Tissue Engineering; Aenne Glass, University of Rostock
P22 Confidence Intervals for Difference of Correlated Proportions Based on Paired and Unpaired Data; Jiajun Liu,
Merck Research Laboratories
43
P23 Change Point Identification with Adaptive Partitioning in Isotonic Regression for Event-Time Data; Yong Ma,
P24 SAS Enterprise Guide and Graphics in Clinical Trials; Levent Bayman, University of Iowa
P25 Methods for Calculating Variability of the Incremental Cost Effectiveness Ratio in Cost-Effectiveness Studies;
Nicole C. Foster, Jaeb Center for Health Research
P26 Use of Historical Controls in Assessing Long-Term Zoster Vaccine Efficacy; Gary R. Johnson, VA Cooperative
Studies Program Coordinating Center, VA Connecticut Healthcare System
P27 Sampling Considerations for Genetic Associations in the Environmental Polymorphisms Registry (EPR);
Lindsey A. Ho, SRA International, Inc.
P28 Repeat Participants in Clinical Research: An Overlooked Sub-Population? Evidence from 20 Years of Inner City
Asthma Consortium (ICAC) Studies; Miguel A. Villarreal, Rho, Inc.
P29 Results of Remote Monitoring Techniques for Multi-Center Ophthalmic Imaging Trials; Dana A.H. Keane,
Optos, Inc.
P30 The Use of Adult Learning Theory in Critical Care Clinical Trials Site Initiation Meetings Improves Confidence in
New Research Skills and Techniques and May Enhance Study Conduct; Elizabeth A. Sweetman, Royal North Shore
P31 Demographic and Health Factors Associated with Enrollment in Post-Trial Studies: The Women’s Health Initiative
Hormone Therapy Trials; Sarah A. Gaussoin, Wake Forest School of Medicine
P32 Impacting a Clinical Trial’s Success by Integrating Regulations, Standards and Guidelines into Organizational
Culture; Jan H. Hickey, Department of Veterans Affairs Cooperative Studies Program
P33 Abstract Withdrawn
P34 Resolving the Conflict: Sponsor-Investigators and the Ethical Concern Behind the Consent Process;
Melissa Y. Brown, Sunnybrook Research Institute
P35 The Quality of Medical Record Abstraction in a Multi-Center Study: The Importance of Training; Nancy Payte,
Westat
P36 Outcomes Adjudication - The Preparation Process; Ainy Zahid, Sunnybrook Research Institute
P37 Transitioning an Adolescent Cohort from a Randomized Clinical Trial (TODAY) to a Post-Intervention Follow-Up
Study (TODAY2); Christen J. Long, The George Washington University Biostatistics Center
P38 Adverse Event Reporting for Hematopoietic Stem Cell Transplant Studies; Mary E. Crann, The EMMES Corporation
P39 NeuroNEXT: Developing Infrastructure for Phase 2 Clinical Trials in Neurological Disorders; Dixie J. Ecklund,
University of Iowa CTSDMC
P40 Serious Unexpected Events in an Obstetric Clinical Trial – Definitional Challenges; Laura A. Magee, The University
of British Columbia
P41 Planning for the End: The Type 1 Diabetes Genetics Consortium (T1DGC); Joan E. Hilner, University of Alabama at
Birmingham, School of Public Health
P42 Risk Management of Non-CTIMP Trials: Focus on Complex Intervention Trials; Shamaila T. Anwar, University of
Leeds
P43 Strategies to Maximise Response Rates to Postal Questionnaires in Pragmatic Trials Involving Elderly Stroke
Patients and Their Caregivers; Shamaila T. Anwar, University of Leeds
P44 Pregnant Women’s Views About Participation in Trials – A Qualitative Study; Katrien Oude Rengerink, Academic
Medical Center
P45 Good Clinical Practice Compliance in a Surgical Trial - Results of Monitoring and Audit; Inga Rossion, Study Center
of the German Surgical Society
44
P46 Parental Perception of a Contract Improves Adherence in Longitudinal Randomized Controlled Trials of Disease
Prevention in Early Life; Helen R. Fisher, Kings College London
P47 Factors That Influence Recruitment to Longitudinal Randomized Controlled Trials of Disease Prevention in Early
Life; Helen R. Fisher, Kings College London
P48 Recruiting and Retaining Minority Subjects for Genetic Research: Challenges and Successes; Andrea S. Zombeck,
SRA International, Inc.
P49 Data Collection for an Aging Cohort in Long-Term Clinical Trials; Pam Mangat, George Washington University
P50 Participant Perception of Treatment Assignment is Related to Symptom Severity in a Clinical Trial of Phytotherapy;
Jeannette Y. Lee, University of Arkansas for Medical Sciences
P51 Dollars and Sense: Effective Fiscal Management of the Carotid Revascularization Endarterectomy Versus Stenting
Trial (CREST); Alice J. Sheffet, UMDNJ-New Jersey Medical School
P52 Adjudication of Safety Outcomes in a Web-Based Clinical Trial Management System; Aaron S. Perlmutter, MUSC
P53 Study Design Issues in a Randomized Trial Comparing the Cost-Effectiveness of Immediate Treatment vs.
Observation/Deferred Treatment Approaches; Danielle L. Chandler, Jaeb Center for Health Research
P54 Starting a Genetic Repository; Alice K. Henning, The EMMES Corporation
P55 Interim Analysis with Sample Size Re-estimation for Binary Outcome in a Trial of Intravitreal Ranibizumab versus Saline Injection for Prevention of Vitrectomy in Eyes with Proliferative Diabetic Retinopathy and Vitreous
Hemorrhage; Michele Melia, Jaeb Center for Health Research
P57 Alcoholism Treatment Studies: A Design Proposal to Improve Relevance; Robert A. Lew, VA Boston Healthcare
System, Boston, MA
P58 Randomised Controlled Trials with the Purpose to Gain Reimbursement for Medical Devices in Germany Responsible Institutions and Trial Design Requirements for the Implementation of Study Results in the Decisionmaking Processes Using the Example of Negat; Doerthe Seidel, Private University of Witten/Herdecke gGmbH
P59 Multicentre Trial Electronic Data Capture Platform (MCT eDC) OHRI-CEP, Methods Centre-Data Management
Services; Dong Vo, OHRI-CEP
45
Poster Presentation Tuesday, May 22, 2012, 8:30 AM – 5:00 PM
P60 Aging in Numbers - National Health Care Trends and the National Institute on Aging Funded Clinical Trials;
Tibor Szentendrei, KAI Research, Inc.
P61 Factor Analysis of the Correlates and Characteristics of Stressful Life Events in the TODAY Cohort; Laura Pyle,
P62 Strategies Implemented for Successful Data Retrieval and Accuaracy in a Long Term Follow-up Study;
Mariam Saleem, Sunnybrook Research Institute
P63 An Approach to Study Drug Management in Randomised Controlled Trials; Sunny Chan, Sunnybrook Research
Institute
P64 Using iPods© as an Intervention Delivery Method and Fidelity Monitoring Device; Tamara Olinger, Rush University
Medical Center
P65 Establishing a Remote Data Entry System in a Rural Tribal Community; Dixie J. Ecklund, University of Iowa
CTSDMC
P66 Clinical Data Management of HIV/AIDS-Related Illnesses in HIV Clinical Trials: Challenges and Solutions;
Maija A. Anderson, Fred Hutchinson Cancer Research Center
P67 Coding Open-ended Responses: Identifying Problems and Solutions; Jennifer W. Talton, Wake Forest School of
Medicine
P68 Database Structure for Multiple Protocols Within a Project; Danielle L. Smith, The EMMES Corporation
P69 Optimizing Optical Character Recognition Software for High Quality Data; Jennifer N. Andringa, Cincinnati
Children’s Hospital Medical Center
P70 Challenges to Transitioning from Paper-based Data Collection to Electronic Data Capture; Trinh Hoac,
P71 Utilizing a Web-Based Telephone Call Tracking System in the Collection of Cognitive Data; Darrin A. Harris,
Wake Forest School of Medicine
P72 Improving the Reliability of Web-based Randomization using Encrypted Allocation Information Embedded into Data
Elements; Gordon S. Doig, Royal North Shore Hospital, University of Sydney
P73 A Tailored Communication Platform for a Virtual Intervention Team; Elizabeth F. Avery, Rush University Medical
Center
P74 The Use of a Multifaceted Clinical Trial Implementation and Education Strategy to Minimise Major Protocol
Violations; Fiona Simpson, Royal North Shore Hospital, University of Sydney
P75 The Novel Use of Site Selection Surveys to Improve Sub-optimal Recruitment; Fiona Simpson, Royal North Shore
P76 Consort-like Flowcharts in DSMB Reports; Patricia A. Feeney, Statistics Collaborative, Inc.
P77 Ethical Issues in Secondary Research with Human Specimens; Liza Dawson, NIH/NIAID Division of AIDS
P79 Compensation for Bodily Damage to Participants in Un-notified Clinical Trials in Japan; Toshinori Murayama, Kyoto
University Hospital
P80 Increasing Institutional Oversight for Multicenter Protocols: An Institutional Office at Memorial Sloan-Kettering
Cancer Center (MSKCC); Supriya G. Parikh, Memorial Sloan-Kettering Cancer Center
P81 Use of Barnard’s Test as a More Powerful Alternative to Fisher’s Exact Test; Peter M. Calhoun,
Jaeb Center for Health Research
P82 Interpretation and Results Comparing Frequentist and Bayesian Interim Monitoring: Survival and Continuous
Outcomes; Alice R. Pressman, Kaiser Permanente
46
Presentations
P83 Implementation and Diagnostics for Frequentist and Bayesian Interim Monitoring: Sequential Bounds and Chain
Convergence in SAS; Marnie Bertolet, University of Pittsburgh, School of Public Health
P84 Analysis of Safety Data Using SAS; Thomas Bruckner, University Heidelberg
P85 Multiple Hypotheses Testing and Simultaneous Confidence Intervals for Multiple Adverse Event Assessment;
Zhibao Mi, VA Cooperative Study Program
P86 Enrollment Propensity Weighting to Assess the Generalizability of a Randomized Clinical Trial; Marie G. Gantz,
RTI International
P87 Sample Size Considerations in Cluster Randomised Trials with Unequal Clusters – Experience from Two UK Stroke
Rehabilitation Trials; Ivana Holloway, Medical Statistician
P88 Monitoring Rare Events in a Single Arm Non-inferiority Trial (111; CRUK/09/011); Eleftheria Kalaitzaki,
The Institute of Cancer Research
P89 The VACS Index Score as an Alternative Endpoint in HIV/AIDS Studies; Tassos Kyriakides, VA Cooperative Studies
Program Coordinating Center, VA CT Healthcare System
P90 Responsive Recruitment Strategies to Maximise Recruitment: Experience from National UK Stroke Trials;
Shamalia T. Anwar, University of Leeds
P91 Challenges of Recruiting Women to a Clinical Trial of Treatment for Mucopurulent Cervicitis; Jeannette Y. Lee,
University of Arkansas for Medical Sciences
P92 Transformation of Regulatory Requirements into a Training Curriculum for Investigational Site Teams of Clinical
Trials with Medical Devices in Germany** Granted by the German Federal Ministry of Research and Education,
Germany, BMBF Grant 01KN1106; Heike Moenkemann, Clinical Trials Center Cologne (BMBF grant 01KN1106)
P93 Methodology Matters: Spotlight on the Network of Hubs for Trials Methodology Research (HTMR) in the UK;
Elizabeth Gargon, University of Liverpool
P94 Evaluation of a New Institutional Clinical Research Monitoring Program for Investigator Initiated Studies;
Jami N. Jackson, Memorial Sloan-Kettering Cancer Center
P95 Lessons Learned: Effective Training Strategies for Electronic Data Capturing; Siobhan Tobin,
P96 Factors Influencing Recruitment in Clinical Trials; Katrien Oude Rengerink, Academic Medical Center
P97 Role of Glucocorticoid Receptor SNPs in Receptor Function and Metabolic Disease; Lisa B. Murphy,
SRA International Inc.
P98 Ensuring Successful Adherence to Study Requirements in a Multi-centre Study; Asma T. Qureshi,
P99 WHO can RECIST?: The Evolution of Solid Tumor Response Criteria; Bingyan Wu, Rho, Inc.
P100 Partners in Research: Effective Collaboration between a National Clinical Trial (TODAY Study) and Oklahoma-Based
Multi-Tribal Health Boards; Jennifer Q. Chadwick, University of Oklahoma Health Science Center
P101 Minority Cancer Survivors’ Attitudes and Experiences Related to Participation in Cancer Clinical Trials;
Margaret M. Byrne, University of Miami
P102 Development of a Decision Aid to Improve Minority Cancer Patients’ Decisions About Participating in Clinical
Trials; Margaret M. Byrne, University of Miami
P103 Developing and Maintaining Standard Operating Procedures for a Multi-Trial Data Coordinating Centre;
Johanna Sanchez, Sunnybrook Research Institute
P104 Developing an Effective Site Feasibilty Questionnaire for the Site Selection Process; Johanna Sanchez,
P105 Recruitment and Retention of Trial Subjects in the 21st Century: Insights from Experience from Conducting
Several Recent Large International Trials in Cardiology; Susan Chrolavicius, McMaster University
47
Presentations
P106 Monitoring Blood Sample Collection and Shipment in a Publicly Funded Post Thrombotic Syndrome (PTS)
Randomized Controlled Trial (RCT); Adrielle H. Houweling, McGill University
P107 Challenges and Strategies in the Start-up Phase of Large, International Clinical Trials in Cardiac Surgery;
Jessica C. Vincent, Hamilton Health Sciences/McMaster University
P108 Transitioning Paper to Electronic Case Report Forms Mid-study from One Clinical Research Organization to
Another; Caroline Kim, EMMES Corporation
P109 NIAID Auditing Services Program (NASP): Providing Worldwide Quality Assurance Audits of DAIDS Monitoring
Functions; Jan S. Peterson, The EMMES Corporation
P110 Provision of Coverage Analysis in Multi-Site Clinical Trials Aids All Sites and Particularly Smaller, Community-Based
Practices; Kati M. Stoermer, University of Michigan
P111 Implementation of Likelihood-based Continual Reassessment Method Designs in Dose Finding Trials;
Emily M. Van Meter, University of Kentucky
P112 Application of Different Randomized Phase II Trial Designs in a Breast Cancer Trial; Heidi L. Weiss,
University of Kentucky
P113 Ranking and Selection Design of a Phase IIa HIV Vaccine Clinical Trial in China with Three Active Arms and
Multiple Endpoints of Interest; Yunda Huang, Fred Hutchinson Cancer Research Center
P114 US-China Collaborations on the Design of China’s First Phase IIb HIV Vaccine Efficacy Trial; Yunda Huang,
Fred Hutchinson Cancer Research Center
P115 Design of a Neonatal Intervention Based on Joint Evaluation of Efficacy and Toxicity; Dennis D. Wallace,
Research Triangle Institute
P116 A Two Stage Phase II Design Incorporating the Possibility that the Treatment Effect May be Restricted to a
Biomarker Defined Subgroup: Investigation of a PARP Inhibitor (Olaparib) in Castration Resistant Prostate Cancer
(CRPC); Roger P. A’Hern, Clinical Trials and Statistics Unit
P117 Designing Trials for Proving Efficay of Multifunctional Food: Some Notes on the Need for Multiplicity Adjustment;
Federica Zobec, ZETA Research Ltd
P118 Could Methods be a Factor in Early Closures of HIV Pre-exposure Prophylaxis Trials?; Madzouka B. Kokolo,
Ottawa Hospital Research Institute
48
Abstracts
Abstracts appearing in this SCT final program book are printed as submitted by the author(s) of that
abstract. Unless instructed by the author, the content of the abstract was not edited or reformatted.
A01
The German National Surgical Network (CHIR-Net)
Dörthe Seidel, Vanessa Jakob, Edmund A.M. Neugebauer
Witten/Herdecke University Germany on behalf of all CHIR-Net partners
A decision of the Federal Joint Committee Germany states that negative pressure wound therapy is not accepted
as a standard therapy with full reimbursement by the health insurance companies in Germany. This decision is
based on the rapid report and the final report of the Institute for Quality and Efficiency in Health Care, which demonstrated through systematic reviews and meta-analysis of previous studies projects that an insufficient state
of evidence regarding the use of negative pressure wound therapy (NPWT) for treatment of acute and chronic
wounds exists. The Institute for Research in Operative Medicine (IFOM) as part of the University of Witten /
Herdecke gGmbH is an independent scientific institute that is responsible for the planning, implementation,
analysis and publication of trial projects regarding the efficacy and effectiveness of negative pressure wound
therapy for acute and chronic wounds in both medical sectors (in- and outpatient care) in Germany.
The study projects are designed and conducted with the aim to provide solid evidence regarding the efficacy
of NPWT. The trials evaluate the treatment outcome of the application of a technical medical device which is
based on the principle of negative pressure wound therapy (Intervention Group) in comparison to standard wound
therapy (Control group) in the treatment of chronic foot wounds and acute subcutaneous abdominal wounds after
surgery. All used treatment systems bear the CE mark and will be used within normal conditions of clinical routine
and according to manufacturer’s instructions.
The aim of the trial projects is to compare the clinical, safety and economic results of both treatment arms.
Study results will be provided until the end of 2014 to contribute to the final decision of the Federal Joint
Committee Germany regarding the general admission of negative pressure wound therapy as a standard of performance within both medical sectors.
A02
What Influences Patient Participation in Randomized
Controlled Trials of Surgical Interventions?
Katrien Oude Rengerink, Renée Barendse, Paul Fockens, Ben Willem Mol, Evelien Dekker
Department of Obstetrics and Gynaecology, Academic Medical Center, Amsterdam, the Netherlands
Department of Gastroenterology, Academic Medical Center, Amsterdam, the Netherlands
INTRODUCTION: Adequate patient recruitment is a key condition determining the validity, duration and costs of
RCTs, yet remains challenging. The expanding interface between therapeutic endoscopy and minimally invasive
surgery for the treatment of benign gastrointestinal diseases demands RCTs to compare safety and cost-effectiveness of comparable interventions. We aimed to identify patient motives and barriers for (non)participation in
the TREND study.
METHODS: Patients with large rectal adenomas counseled between January and July 2011 for participation in an
RCT comparing endoscopic mucosal resection (EMR) with transanal endoscopic microsurgery (TEM) were invited
for a semi-structured interview (14 participants, 12 non- participants). Interviewees were asked to discuss their
main motive for (non-) participation in an open fashion. Subsequently, potential other barriers and motivations
as previously described in the literature were presented by the interviewer. Interviews were coded and analyzed
by 2 independent researchers.
RESULTS: We interviewed 10 participants and 7 non-participants, aged 54-84. Key motive for trial participation
was contribution to medical science and future clinical practice (all participants). Other motives included satisfactory counseling, sufficient time to reflect and the sense that participation was completely voluntary. The vast
majority of non-participants had previous in-hospital experience, however more than half had not been introduced
49
to research prior. Although most non-participants felt contributing to research was important, key barriers to participation included a distinct preference for either EMR (n=4) or TEM (n=3) or intervention-specific characteristics
like type of sedation (all non-participants). Consultation of family members affected half of all decisions. Study
characteristics such as randomization, blinding, insurance and ethical approval hardly influenced the decision
making.
CONCLUSION: In RCTs comparing similar endoscopic and surgical strategies, thorough, tailored and timely
counseling is crucial to clarify the study purpose and to emphasize the presumed equality of allocation arms.
Avoidance of common barriers to participation will improve trial inclusion.
A03
Funding Strategies for Establishing Surgical Trial
Centers – Experience and Strategies
Gregor Stein, Peter Knöll, Peer Eysel, Lars Peter Mueller,
Oliver Cornely, Margarete Wicharz, Kourosh Zarghooni
Cologne University Hospital, Department of Orthopaedic and Trauma
Surgery, Cologne, Germany (BMBF 01KN1106)
The establishment of clinical trial centers creates a demand for both infrastructure and skilled staff. While establishment and operation of clinical trial centers in surgical specialties have in recent years often been conducted
by medical staff in addition to clinical practice, the intensification of legal regulations and the increased number
of clinical trials in surgery requires rethinking. The ability to fulfill these more specialized demands can only be
given by allocating sufficient funds. These funds can be used to employ trained paramedical staff and furthermore to release medical staff from clinical work and thereby enable full-time scientific work. On the other hand, a
demand for funding is risen to implement infrastructural requirements such as IT hardware and premises. Once
a clinical trial center has been established, further operation has to be ensured by generating additional funds.
While the demand for start-up financing of a clinical trial unit is most meaningful arranged by governmental or
institutional fundraising, the operation relies on generating sufficient funds through the conduction of industryinitiated trials. Own experience and further possibilities are demonstrated by reporting on different strategies for
funding of clinical trial centers and the general demand of funds during establishment and operation of clinical
trial centers. Therefore, different governmental, industrial as well as institutional supports are relevant factors.
A04
Challenges of Developing Procedures for Serious Adverse Event Management and
Reporting According to Regulatory Requirements in Clinical Trials With Medical
Devices in Germany* * Granted by the German Federal Ministry of Research
and Education (BMBF Grants 01KN1106 and 01EZ0931) and by the “Technology,
Methods, and Instructions for Networked Medical Research” (TMF E.V.)
Heike Moenkemann, Sylvia Reinecker, Stefanie de Lange, Rita Pilger;
Ursula Paulus for the QM working group of the CTC-network
University of Cologne, Clinical Trials Center Cologne, 50935 Cologne,
Germany, BMBF Grants 01KN1106 and 01EZ0931
In Europe safety management requirements in clinical trials with medical devices were changed fundamentally
by the council directive 2007/47/EC in 2007 and internationally with the ISO 14155:2011 in 2011. Previously
adverse incidents had to be reported to the competent authority. Since implementation of the directive in
Germany each serious adverse event (SAE) which happened or might have happened to a patient, user, or
third party, must be reported immediately. Sponsor and investigators must report SAEs via an electronic form
centrally provided by the Federal Institute for Drugs and Medical Devices (BfArM). Besides profound knowledge
adequate IT equipment at all investigator trial sites are needed. The latter being a challenge for academic trials
with their low budgets. To develop operational competence the quality management (QM) working group of the
Clinical Trials Centers (CTC)-network developed a harmonized SOP describing the complex procedures of safety
management for sponsor and investigator trial sites. It includes appendices providing among others definitions,
a template for an SAE-manual, and instructions for completing the electronic form. This document particularly
suggests solutions regarding more general regulatory requirements, e.g. follow-up information for the sponsor or
50
for the competent authority. The implemented safety management procedures consider experiences derived from
clinical trials with medicinal products and the special characteristics of academic trials. As increased numbers
of clinical trials with medical devices are to be expected according to changed regulations CTCs will become
more experienced with these complex procedures. Thus they will be competent partners to industry in conducting
national and international clinical trials with medical devices. Our report will show the challenges of coping with
this novel electronic reporting process, and provide our experiences in fulfilling the updated changed German
national regulations.
A05
Knowledge Transfer in Clinical Research: Do We Know What Is Going On,
Do We Know the Results and Are They Transferred Into Practice?
Dr. Gabriele Dreier, Dr. Susanne Jena
University Medical Center Freiburg Clinical Trials Unit, Freiburg, Germany; University Medical Center Freiburg
Institute for Medical Biometry and Medical Informatics University Medical Center Freiburg, Freiburg, Germany
Due to the ever increasing global activity in clinical research, knowledge transfer between researchers and all
stakeholders in clinical health care (including patients) worldwide is an indispensable requirement. A prerequisite
for knowledge transfer in clinical research is an unbiased and complete view on clinical trial results. How is the
arising number of clinical trials registries and results databases being utilized by different user groups including ethics committees, clinicians, patients, researchers, reimbursement and funding institutions? What are the
different requirements defined by the parties involved? How can variable needs be met? What seem to be the
arising issues concerning database content, language barriers, retrieval problems, implementation of knowledge
into daily work, evaluation of existing evidence? What efforts are made to overcome the obstacles?
A06
Clinical Trial Auditing in an Electronic World: Do
Not Risk You Data - Validate Sufficiently
Jochen Dress1, Markus Wallstein2, Hans Poland3
1Clinical
2Dr.
Trial Center Cologne (BMBF Grant 01KN1106), Cologne, Germany;
Hans Poland Consulting GmbH, Germany; 3ADAMAS Consulting Ltd.
Meanwhile it is daily experience that conduct of a clinical quality assurance audit involves some kind of computer
system to be considered and assessed. The following fundamental question comes immediately to mind: how
valid are data and information kept and handled by the systems employed? This question will be subdivided in
five parts for the purpose of this session: Where does the basic computer system used come from, how has it
been implemented and validated and how is it maintained? How has the computer system application used in a
specific trial been developed, validated and deployed and how is it operated and maintained? Which regulations,
guidelines and state of the art standards are to be expected to be observed for development, validation and
operation? How big are the risks on data quality and acceptability of the study outcome in case of malfunction
of the computer system application? How high are chances that system weaknesses can be detected in a standard audit setting and how can auditors optimise the preparation and conduct of their review to detect hidden
system bugs? The session presents an overview over the current situation, naming specific risks and gives some
answers to the questions posed afore, mainly by giving practical examples how to proceed in the most frequent
audit situations, namely investigator site audits (eClinical and electronic source documents), CRO system audits
and vendor audits.
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A07
A Simple Bayesian Decision Theoretic Design for Dose Finding Trials
Ying Lu, Shenghua Fan, You-Gan Wang
Palo Alto VA CSP Coordinating Center & Stanford University, Mountain View, CA, USA
A flexible and simple Bayesian decision- theoretic design for dose finding trials is proposed in this paper. In
order to reduce the computational complexity, we adopt a working model which produces analytic posterior distributions. In addition, this working model is sufficiently flexible to fit all monotonic dose-toxicity curves. We also
discuss how to use a proper utility function to reflect the interest of the trial. Patients are allocated based on
not only the utility function but also the chosen dose selection rule. The most popular dose selection rule is the
one-step-look-ahead (OSLA), which selects the best so far dose. More complicated rules such as two-step-lookahead (TSLA) are surely more efficient than OSLA only when the required distributional assumptions are met
which is however often not the case in practice. We carry out extensive simulation studies to evaluate a variety
of dose selection rules and have found that OSLA is often more efficient than TSLA under our proposed method.
Moreover, our simulation results show that the proposed method performs superior to several popular Bayesian
methods and the negative impact of prior mis-specification could be considered in the design stage.
A08
Interactive Software “Isotonic Design Using Normalized Equivalent
Toxicity Score (ID-NETS)” for Cancer Phase I Clinical Trials
Zhengjia Chen1,2,Zhibo Wang2, Taofeek K. Owonikoko3, Jeanne Kowalski1,2, Fadlo R. Khuri3
1Department
of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA;
and Bioinformatics Shared Resource at Winship Cancer Institute GA, USA;
3Department of Hematology and Medical Oncology, Emory University, Atlanta, GA, USA
2Biostatistics
Isotonic Design using Normalized Equivalent Toxicity Score (ID-NETS) is a novel Phase I design originally proposed
by Chen et al. by integrating the novel toxicity scoring system proposed by Chen et al. and the original Isotonic
Design proposed by Leung et al. ID-NETS has substantially improved the accuracy of maximum tolerated dose
(MTD) estimation and efficiency of trial by fully utilizing all toxicities of each patient and treating toxicity response
as a quasi-continuous variable instead of a binary indicator of dose limiting toxicity (DLT) in a Phase I clinical
trial. To facilitate designing and conducting a Phase I clinical trial with ID-NETS, we have developed a user-friendly
software ID-NETS©TM, which has two functions: 1) Calculating the recommended next dose level from completed
data; and 2) Performing simulation to obtain the operating characteristics of a trial. Currently, ID-NETS©TM v1.0
is available for download at http://winshipbbisr.emory.edu/IDNETS.html.
A09
The Modified Toxicity Probability Interval (MTPI)
Method for Phase I Dose-Finding Trials
Yuan Ji, Sue-Jane Wang, Ping Liu
Department of Biostatistics, The University of Texas M. D. Anderson Cancer Center Houston, TX, USA
Building on the toxicity probability interval (TPI) design in Ji et al. (2007), we present a modified TPI design (mTPI)
that is calibration-free for phase I trials. Our goal is to further simplify the design and improve the trial conduct,
and provide more effective and safer methods while maintaining the simplicity of the original TPI design. Like the
TPI method, mTPI consists of a practical dose-finding scheme guided by the posterior inference using a simple
Bayesian model. However, the new method benefits from improved dose-finding decision rules based on a new
statistic, the unit probability mass (UPM). The improvement through the use of the UPM for dose finding is significant. We will present extensive simulation results comparing the mTPI design to the 3+3 and CRM methods,
and provide convincing evidence why the mTPI is a practically superior method.
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A10
Incorporating Patient’s Characteristics in Cancer Phase I Clinical
Trials Using Time to DLT: Escalation With Overdose Control
Yuan Liu, Mourad Tighiouart, Andre Rogatko
Winship Cancer Institute, Emory University, Atlanta, GA, USA
Among the most recent advances in escalation with overdose control (EWOC) based Bayesian adaptive phase I
clinical trial designs, Tighiouart et al (2011) developed EWOC based on the proportional hazards model (EWOCPH) using time to toxicity to estimate the MTD. The method has been shown to be more efficient to estimate
MTD comparing to the original EWOC and a version of time to event EWOC (TITE-EWOC) proposed by Mauguen et
al (2010). In this study, we will further extent EWOC-PH to take into account patients’ baseline covariates. The
extension of EWOC to accommodate baseline covariates has been developed by Babb and Rogatko (2001) and
Tighiouart and Rogatko (2010). We expect that the new design will provide better safety protection by assigning
a personalized dose to the next available patient based on his/her own baseline characteristics and lead to an
estimation for covariate specific phase II dose. We assess the operating characteristics for the design via extensive simulations including three scenarios: (1) design using a covariate; (2) Design ignoring the covariate; (3)
Design using separate trials. The efficiency of estimating the conditional MTD and safety of the trial are compared
with original EWOC with covariate using DLT as a binary indicator of toxicity.
A11
A Novel Statistical Software Ewoc-Nets©TM for Extending
Dose Escalation With Overdose Control (EWOC) to Fully
Utilize All Toxicities in Cancer Phase I Clinical Trial
Zhibo Wang1, Taofeek K. Owonikoko2, Jeanne Kowalski1,3, Fadlo R. Khuri2, Zhengjia Chen1,3
1Biostatistics
and Bioinformatics Shared Resource at Winship Cancer Institute, GA, USA;
of Hematology and Medical Oncology, Emory University, Atlanta, GA, USA;
3Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA
2Department
Escalation with overdose control (EWOC) is a successful Phase I design and has been widely used. Chen et al.
further extended EWOC to utilize fully all toxicities of patients instead of a binary indicator of dose limiting toxicity (DLT) by incorporating the normalized toxicity scoring system (NETS) proposed by Chen et al. into EWOC with
a quasi-Bernoulli likelihood approach. The new design is called EWOC-NETS which has been demonstrated by
simulation studies to have good operating characteristics and improve the accuracy and efficiency of the maximum tolerated dose (MTD) estimation relative to common Phase I designs. In this study, we have developed an
interactive software called EWOC-NETS©TM which is very user friendly to facilitate designing and conducting a
Phase I clinical trial with EWOC-NETS and available for free download at the website of Emory University http://
winshipbbisr.emory.edu/Software.html. We would like to introduce this novel statistical software and translate
EWOC-NETS into Phase I cancer clinical trials in the future.
A12
A Cox Regression Model With Isotonic Regressors With ChangePoint Problems: Addressing a Clinical Question
Das Purkayastha; Stan Li
Novartis Pharmaceuticals Biometrics, US Medical East Hanover, NJ, USA
Some clinical predictors may or may not have monotonic properties. They may have increasing or decreasing
pattern or they may remain steady during a period of observation time. A clinical question is raised on how such
increasing or decreasing or constant pattern of variations may have effect on survival or on clinical outcomes
independently during a period of time. Generally we ignore such point of transitions and independent pattern of
variations while investigating their overall effect.
Isotonicity is called the simple or partial ordered monotonicity mathematically. Isotonic regression is performed
under ordered monotonic restrictions criteria. Either increasing or decreasing or constant variation of a clinical
predicator or of a prognostic variable generates a change-point problem at the transition from increasing order to
53
decreasing order or vice versa or from the steady condition to either increasing or decreasing pattern of clinical
predictors.
The primary thrust of this paper is to address such clinical questions using a Cox Regression Model with isotonic
regressors with such change-point problems. In a case study with multiple myeloma the impact of such changepoint patterns of clinically significant predictors such as hemoglobin, blood urea nitrogen, white blood corpuscles,
platelets on patients median survival time have been explored.
A13
The Long Road to Start up Rcts Within the Social Services Interventions in Denmark
Maiken Pontoppidan
SFI – The Danish National Institute for Social Research, Copenhagen, Denmark
Policy makers in Denmark are starting to realize that RCT designs are needed if they want to know the impact of
social interventions. Therefore the Ministry of Social Affair granted funding to do three RCTs of family programs
(Multidimension Treatment Foster Care-MTFC, Parent Management Training Oregon -PMTO and Multisystemic
Therapy-MST). During the last year SFI has been planning the studies including all relevant parts in the process.
The process has been long and challenging. Problems faced include: 1: A pronounced resistance to randomization within all levels of social services. 2: An economic crisis in the municipalities causing both unwillingness to
participate in the research study and a significant lower caseload in the MST and MTFC teams. 3: Fear of the
study going to steal half of the families from the programs. 4: Underfunding of the studies. 5: Resistance against
using standardized tests because this is not common in social work, and 6: Difficulties in getting data for power
calculations. Recurring issues that we have had to deal with are: “do we really have to randomize? Can’t we
just do some kind of matching?” and “it would be much better to spend the money on a wider implementation
of the program and practice oriented qualitative research.” Recently the MST study was cancelled since all five
MST teams declined to participate. Funding was transferred to the other two studies making them look more
promising. A lot of resources have been used to prepare the studies and expectations are high. Hopefully by May
2012 the MTFC study will be recruiting families and the PMTO study will be ready to start recruiting in September
2012. If all goes well the two studies will be among the first RCTs carried out on social interventions in Denmark.
A14
Elements of a Phase 3 IND Study Protocol – An FDA Statistical Perspective
Renee Rees, Ghideon Ghebregiorgis, Shiowjen Lee, Lihan Yan
FDA, Center for Biologics Evaluation and Research (CBER), Division of Biostatistics Rockville, MD, USA
Regulatory goals for a clinical study can be different from research and exploratory goals. For the Food and
Drug Administration (FDA), Phase 3 Investigational New Drug (IND) studies (i.e., adequate and well- controlled
studies) will provide the primary clinical evidence to support a marketing application such as a Biologic License
Application (BLA). To support approval and initiation of these studies, the protocol should cover all the statistical
issues considered by the reviewers when assessing the study design and its ability to adequately address the
study objectives. As an aid to statistical reviewers, as well as to improve efficiency and consistency in our reviews
of these protocols, the Division of Biostatistics in the Center for Biologics Evaluation and Research (CBER) has
developed a checklist outlining the important elements of a Phase 3 protocol. Some elements included in this
checklist are consistency between the study objectives and endpoints; number and regions of study sites; statistical hypotheses; planned interim analyses; sample size assumptions and calculations; randomization description; blinding techniques; analysis populations; multiplicity considerations; missing data considerations; study
success criterion; and study conduct. Original IND submissions with protocols with such elements may also lead
to less correspondence with the sponsor to clarify items in the protocol. We note that the elements identified in
this checklist may also be helpful in designing earlier phase studies as well as non-IND studies. This presentation will focus on the motivation, contents, and use of the checklist.
54
A15
Must a Randomized Trial Focus on Hypothesis Testing? -- Assessing Risks and
Benefits of Withdrawal From Therapy When the Acceptable Risk Margin Is Unclear
Lisa Wruck1, Lynette Keyes-Elstein2, Erica Brittain3, Tammy Utset4,
Eliza Chakravarty5, Meagan Spychala2, Ellen Goldmuntz3
1Collaborative
Studies Coordinating Center, Department of Biostatistics, UNC - CH, Chapel Hill, NC, USA;
Inc., Chapel Hill, NC, USA; 3DAIT/NIAID/NIH Bethesda, MD, USA; 4University of Chicago,
Chicago, IL, USA; 5Oklahoma Medical Research Foundation, Oklahoma City, OK, USA
2Rho
In non-inferiority trials, a pre-specified margin of non-inferiority must be defined a priori. However, what happens
when an acceptable risk varies according to physician risk tolerance or patient circumstances, so a pre-specified
margin of non-inferiority cannot be easily defined? We will discuss a double-blind clinical trial in which SLE patients
on long-term MMF therapy with stable disease are randomized to continue therapy or withdraw. It is expected that
withdrawal from MMF will result in increased risk of disease reactivation; however, long- term MMF treatment is
not without risk of side effects. The goal of the trial is to determine if the increase in risk of disease reactivation
outweighs the benefits of withdrawal. One could frame this goal as a test of the non-inferiority hypothesis that
the increased risk of disease reactivation is greater than a pre-specified margin, determined by potential benefit.
However, how the risks and benefits should be weighed is highly individual, even for experienced rheumatologists.
Rather than design the study to test a hypothesis of non- inferiority using an arbitrary risk margin that may or may
not be relevant for any particular patient, the results of this trial will be reported as effect estimates for change in
risk of disease reactivation in addition to other disease activity, safety, quality of life and medication use endpoints.
These effect estimates and confidence intervals will describe the risks and benefits of withdrawal from study therapy and may be used to guide physicians and patients in making decisions based on individualized assessments of
acceptable risk. As clinicians are likely to find interpretation of results difficult in the absence of hypothesis testing
(and p-values), we will discuss the approach planned for disseminating clinical trial results.
A 16
Methods of Analyses for a Complex Intervention Cluster Randomised
Stroke Trial – Looking for the Goose That Lays the Golden Egg
Ivana Holloway, Amanda Farrin
Clinical Trials Research Unit (CTRU), University of Leeds, Leeds, UK
Cluster randomised trials (CRTs), compared to individually randomised trials, require specific analysis; statistical
models need to take account of between-cluster variability. This abstract focuses on two main approaches to
analysis, cluster-level (CL) and individual-level (IL), and examines their efficiency for the Training Caregivers After
Stroke trial (TRACS). TRACS is a CRT evaluating a complex intervention in stroke rehabilitation with 928 dyads of
patients and caregivers within 36 stoke rehabilitation units. The primary outcome is NEADL score at 6 months.
CL analysis is attractive due to its simplicity. We compare performance of three techniques; simple summaries
(using appropriate two- sample weighted t-tests), CL analysis adjusted for covariates and nonparametric methods. The CL approach is a two-stage method; in unadjusted analysis, a summary measure for each cluster is
calculated and two sets of cluster-specific measures are compared using the weighted t-test. When performing CL
analysis adjusted for covariates; we carried out an IL regression with all but intervention effect covariates ignoring
the clustering effect. Secondly, we compared the residuals for each cluster between treatment arms using the
weighted two-sample t-test. Wilcoxon’s rank sum test was used as a nonparametric substitute to the two-sample
t- test. IL analysis, using a random effects linear mixed model with stroke rehabilitation units as level 2, was the
preferred method, because of its greater computational convenience and it is possible to analyse the intervention effect and other covariates simultaneously. The CL approach is robust, particularly for a smaller number of
clusters. However, it may not be statistically the most efficient, especially if clusters are of varying size. Such
weighting is incorporated in IL analysis. Analysis of cluster randomised trials can be undertaken in a number of
ways. We will present and discuss the advantages and disadvantages of each of these analytical methods.
55
A17
Does Using Minimisation Make a Difference?: Empirical
Evidence From Three Multi-Centre Studies.
Gladys McPherson1, Marion Campbell1, Diana Elbourne2
1Health
Services Research Unit, University of Aberdeen, UK;
School of Hygiene and Tropical Medicine, UK
2London
Simple randomisation is the easiest method for allocating participants to treatment groups in clinical trials. In the
long run it balances all features of participants across the groups but may not be suitable for small to medium
sized trials, or for larger trials at the time of interim analysis. If important prognostic factors are identified at the
design stage then minimisation can help to balance these features.
There is uncertainty as to whether treatment groups need to be balanced at baseline, but many researchers believe this to be advantageous, allowing comparison between groups without the need for sophisticated
analysis. Balance between treatment groups can be desirable in a range of scenarios: for small trials, interim
analyses, early termination, analysis of subgroups or where the credibility of an unbalanced trial is considered
problematic (e.g. in the case of a small treatment effect).
Three completed trials of varying size, originally using minimisation as method of treatment allocation, were “rerandomised”, in the order that participants joined the study, using simple randomisation. Datasets frozen at the
time of either interim or full analysis were used.
For all three trials treatment allocation was well balanced across prognostic variables and between treatment
arms when using minimisation at all time points, i.e. for any number of participants recruited at that time. With
simple randomisation, at each timepoint imbalances were identified that could have made analysis more difficult.
In some cases the potential imbalance across treatment groups within a factor reached 100% (where all participants with a given characteristic were in the same treatment allocation group) and no amount of sophisticated
analysis could compensate for this. The simulations demonstrated the need for incorporating minimisation into
the randomisation algorithm of trials of any size in order to achieve treatment balance which cannot be achieved
by using simple randomisation alone.
A18
Futility Boundary Design Based on Probability of Success
Yijie Zhou, Ruji Yao, Bo Yang, Ramachandran Suresh
Merck Research Laboratories, Kenilworth, NJ, USA
A futility analysis is commonly utilized in clinical trials for early read of trial efficacy data. An investigational drug
will be declared futile if the prespecified futility boundary is met, and the trial will be stopped. In a conventional
group sequential design, a futility boundary is selected based on power preservation or sufficient conditional
power, which protects the probability of rejecting the null hypothesis at the end of a trial. However, the observed
treatment effect size is of increasing importance beyond rejecting the null hypothesis and is directly associated
with the eventual success of drug development. To ensure a high probability of observing a desired effect size,
or in another words a high probability of success, we propose a new futility analysis design approach where the
futility boundary is selected based on preserving the probability of success. We define the relative preservation
of this probability as “pseudo-power”, using which we propose the boundary selection criteria. Via a case study,
we evaluate various operational characteristic of this approach in term of the probability of correct and incorrect
stopping, with respect to the futility boundary, the underlying true effect size and the timing of the futility analysis.
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A19
Online Study Monitoring for Large Multi-Center Trials Via a Data Dashboard
Ryan Bailey, Laurie McLeod, Jeremy Wildfire, Katy Jaffee, William
Taylor, Tee Bahnson, Rich Budrevich, Cynthia Visness
Rho, Inc. Chapel Hill, NC, USA
Increasingly, the NIH and Industry sponsors are establishing large multi-center collaborative research efforts
that implement multiple studies simultaneously through a network of investigators. This presents a challenge
for the sponsors and leadership teams who are responsible for monitoring activities across studies. The business world has addressed this need for complex information monitoring systems with a high- level summarized
overview called a dashboard. We created a web-based dashboard for the Inner City Asthma Consortium (ICAC), a
large, federally-funded, multi-center research consortium. The consortium has eight active studies that are being
conducted across ten clinical centers with total projected enrollment of over 3500 participants. Many research
programs provide web-based resources to aid stakeholders with study supervision. Unfortunately, traditional
study portals can be hindered by an overabundance of information and tedious top-down navigation. These characteristics make them an inefficient resource for large multi-center programs. Our dashboard avoids the typical
information- dense, hierarchical construction of traditional websites in favor of a comprehensive single- webpage
display that is easier for stakeholders to access and use. Dashboards summarize and display critical information on a single page, with an emphasis on graphical, rather than text-heavy displays. Our dashboard has a main
page for the consortium, which provides comparative enrollment graphs for the active studies, and displays pertinent deadlines and announcements. Each study also has a dedicated page that follows this same “dashboard”
approach. We update the dashboard data weekly. Sponsors have responded positively to the ICAC dashboard,
voicing appreciation for the system’s efficient presentation of data and ease of use. Given the success of the
dashboard, we plan to expand the system to other federal and commercial programs. Our experience suggests
that multi-center or multi-study programs would benefit from creating a dashboard to provide sponsors and network leadership teams with key study monitoring information in a quick, succinct manner.
A20
Technologies Supporting Clinical Research in Resource Poor Settings
Marisa De Rosa
Cineca
Due to the lack of infrastructure in resource poor settings and despite the strong need for Clinical Research
coordination, Information and Communication Technology has not been systematically and sustainably integrated
into health research, hospital administration and practice, thus limiting efficiency and outcomes of the efforts to
fight poverty related diseases. Cloud-based technology could now overcome infrastructure scarcity problems of
resource poor settings and thus greatly support Clinical Research by integrating mobile, online, offline and Voice
over IP technology. The Italian Inter University Consortium Cineca, a non-profit Consortium of Italian Universities
for high performance computing and ICT , has an over 20 year experience in providing technological support to
health research for activities related to the design and development of IT systems and services in the health care
and biomedical area, using advanced technologies and methodologies.
In particular, since 2008 Cineca has been involved in projects providing and developing technology to collect and
analyze clinical and health related data in Africa. The European funded project Medishare, coordinated by Cineca,
successfully managed to collect standardized data for over 15000 patients affected by HIV/AIDS, Malaria and TB
in Kenya Tanzania and Uganda in one central database. Medishare was recognized supportive of the Millennium
Development Goals by the United Nations. The Europe – Africa Research Network for Evaluation of Second-line
Therapy (EARNEST) is a trial supported by the European and Developing Countries Clinical Trials Partnership
(EDCTP) that is successfully using Cineca integrated technology in Uganda, Malawi, Zimbabwe.
Cineca exploits the integration of newer technologies to fill in the infrastructural gaps of Africa and provides a
sustainable centralized infrastructure which is fully certified for quality, safety and security procedures.
A21
Developing and Implementing a Laboratory Information
System (lims) to Support Trials in the United Kingdom
Jonathan Gibb1, Sharon Kean1, Caron Paterson2, Jane Hair2
57
1University
of Glasgow, Glasgow, Scotland; 2NHS Greater Glasgow and Clyde Health Board, Glasgow, Scotland
We have developed a LIMS to manage biobank samples for the Scottish Early Rheumatoid Arthritis (SERA)
cohort study. Commercial and open-source solutions were evaluated and it was concluded that development of
a bespoke LIMS system was needed to provide scalability and flexibility to support future projects with different
requirements.
The system developed includes a generic workflow which is capable of modelling:
• Complex storage configurations with up to 1024 dimensions over multiple geographic sites • Storage rules for
sample type , method and time of storage • Multi-event work flow processing from site collection to arrival at labs
• Lab technician workflows incorporating working plate practices • Manual and automated validation methods
using a combination of 1D and 2D barcode technologies
The system is based on a tree structure; all samples are stored in a parentage tree that shows the lineage of
the sample allowing for exploration of any number of generations of derived samples. Our tree based approach
allows the LIMS to be largely generic. By defining the storage, site configuration and the collection protocols the
system can operate with scenarios ranging from a single lab collecting ad-hoc samples, to a multi-lab, multi collection site protocol hosting thousands of samples.
We will discuss the functionality provided by the LIMS system, the tree based design and the possibilities it
allows, the pros and cons of the development, its integration with two additional large multicentre, multinational,
clinical trials and future functionality enhancements.
A22
The Development of a Safe Haven to Allow Access to Routinely
Collected Healthcare Datasets for Use in Clinical Trials
Sharon Kean, Ian Ford, Marion Flood, Roma Armstrong
Glasgow, University of Glasgow, Greater Glasgow and Clyde Health Board, Scotand, UK
The Glasgow Safe Haven aims to provide the physical location and informatics infrastructure to permit confidential and secure access to routinely collected healthcare data for research purposes. We will discuss the design
of this infrastructure illustrating how the availability of routinely collected data can potentially enhance the
design and delivery of clinical trials. This will include: • Extraction of prescription and laboratory data during the
follow-up phase of a clinical trial • Identification of potentially eligible participants for a multicentre clinical trial
in sub-clinical hypothyroidism using centrally held routinely collected laboratory data • Building a clinical data
warehouse in specific disease areas to support clinical trial feasibility assessment.
We will discuss the proposed governance and access structure. The presentation will be illustrated with examples of trials that will benefit from this infrastructure.
A23
Developing and Implementing Generic Components to Improve Efficiency
When Building Electronic Data Capture Systems for Clinical Trials
Mary MacDonald, Sharon Kean, Ian Ford
University of Glasgow
The Robertson Centre for Biostatistics, University of Glasgow have been involved in the development of electronic
solutions to enhance the conduct of clinical research projects for many years. This includes integrated secure
electronic solutions for enrolment and randomisation (web and IVRS), electronic data capture and management
via e-CRF (on- and off-line), trial management, information delivery and reporting, eg Independent Data Monitoring
Committees. Our systems have been implemented for many clinical trials both commercial and academic. To
enhance our ability to produce robust and validated systems efficiently we foresaw a requirement for a standardized library of components. In addition, our systems have to be able to provide specific functionality in accordance with our trial requirements. Included in our system:
·S
tandard screens and functionality to allow trial co-ordinators to register their own users and assign the appropriate access rights.
58
· Inclusion of previously developed screens eg standard questionnaires
· Demographics
· Concomitant medications
· Medical history
· Standard measurements eg Height, Weight, Blood Pressure
· Adverse Events and Serious Adverse Events, and regulatory reporting requirements
· Metrics required for reporting to funders within the United Kingdom
· Implementation of CDISC SDTM to standardize our databases
· Notification and communication to users, either by email or bulletin style within the system
· Document repository to ensure all sites have correct versions of approved documents
We will discuss the implementation of these components in our recent clinical trial systems and how this has
improved efficiency in delivering validated systems to our clients. In addition, we will discuss and further explore
our implementation of CDISC formats
A24
Collaborative Peer-Reviewing and Data Aggregation
in Site Management With Clinicalsite.org
Gustav Vella, Dorothee Arenz, Aristoteles Pagaltzis, Dirk Colaert,
Maik Stumpf, Michael Hallek, Oliver Cornely
University of Cologne, Clinical Trials Center Cologne, Cologne, Germany, BMBF01KN1106
Objective. We present a community developed system focussing on clinical sites, operated as a service by the
Clinical Trials Center of the University of Cologne, which employs collaborative peer reviewing in order to support
timeliness, efficacy, accuracy and safety in site management.
Background. Managing clinical sites in a trial can be very resource-intensive for sponsor and for study site, this,
largely due to disconnect in systems and processes, impeding different parties from collaboratively capturing
organizational data meaningful to all.
Methods. Sponsors, Coordinating Centers, Sites, Study Groups, Societies, Networks and other relevant parties
participating in clinical trials each are individually best positioned and incentivized to capture and/or monitor
certain organizational trial data. On clinicalsite.org role-based access and specific views enhance individual value
and incentives. Reusability of data, meaningful to all, provides the strongest incentive. As a case in point, roles
and responsibilities in a trial can be syndicated to be displayed on institutional websites. The data can also be
aggregated to the trial track record by the investigator as part of his CV. The sponsor, in turn, can review site
and investigator qualifications electronically, cutting turnaround considerably. Furthermore, with roles formally
captured and confirmed, the system can act as a Physician Master Index and provide authentication and authorization credentials for external systems. A plugin framework enables parties to embed their own apps while saving
the data locally. An API for various services and formats can serve data for aggregation within external systems.
Both options provide added value and minimize centrally hosted data, ensuring better data privacy compliance.
Results. Currently 1282 trials with 1681 investigators and 997 organizational units involved are managed in the
system.
Conclusion. Our approach provides critical organizational data of quality with less effort. Exposing the data for
reuse and aggregation unlocks new possibilities within and outside the system.
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A25
Cross Training Within a Clinical Research Organization:
Does It Work or Does It Muddy the Waters?
Fawna L. Start, Nicole C. Close
EmpiriStat, Inc., Mt. Airy, MD, USA
Within any organization the workflow structure and departments are clearly defined. Through a case study we will
examine the lessons learned and outcomes when staff within specific departments are trained round robin to
understand the functions of other departments. By specifically reviewing the cross training of Clinical Research
Associates (CRAs) to periodically perform data entry within a CRO, we show meaningful subject matter expertise
improvements, positive study impact, and a gain in project efficiency.
Pros:
Learning Experience: The trainer becomes more familiar with details of his or her position when outlining a training program to teach others. The trainee once completing the instructional information has a broader picture of
the entire process and often is able to see the bigger picture and the results of where their work is going.
Error Identification: CRA’s have the skills to notice consistency errors that a site may be making emphasizing the
need for additional training or reeducation in a particular area.
CRAs have the expertise to identify clinical errors including but not limited to the incorrect use of a specific form
and inclusion/exclusion criteria errors.
Cons:
Time and Funds: CRA’s are often paid at a higher rate than data entry staff and their talents may be better utilized
in their respective area of expertise.
Analysis of Data: CRA’s in most cases have a significant understanding of site operations and clinical information which usually equates to a slow data entry process as they are always scouring data for errors and not just
entering what is documented.
After considering both pros and cons and the review of a case study where CRA’s perform data entry tasks for
quality purposes this often proves to be beneficial not only to the project, but Corporate Structure and capabilities.
A26
Is an Evolving Chart Audit Plan Necessary in a Long-Term Multi-Center Trial?
Brenda Brewer, Kathy Clingan, Nancy Payte, Jennifer Rosenbaum
Westat, Rockville, MD, USA
The National Lung Screening Trial (NLST) was a randomized controlled trial, funded by the National Cancer
Institute, to determine whether screening with low-dose helical computed tomography reduces lung cancer
mortality relative to screening with conventional chest x-ray in persons at elevated risk of lung cancer. It was
comprised of two components: the Lung Screening Study (LSS) and the American College of Radiology Imaging
Network (ACRIN). The Coordinating Center (CC) for the LSS (n=34,614) provided coordination and data management support for 10 screening sites. One CC challenge was to ensure completeness and accuracy of data collected throughout all stages of the study (e.g., recruitment, screening, follow up, endpoint verification, close-out).
As part of monitoring, the CC conducted visits to each site annually for 9 years. Visits included observation of
procedures and random chart audits. Chart audits served to confirm source documents for consents; eligibility
and randomization verification; screening results; and diagnostic evaluation and followup. On-site monitoring also
provided an opportunity to review and reinforce key study elements with project staff. Annual assessments of
the CC audit plan resulted in 6 revisions to the audit form and 4 revisions to the chart selection, reflecting evolving focus from recruitment through close- out. Throughout the trial, 2457 randomly selected charts (7%) were
reviewed. Source documents verified ~ 50 data elements during Year 1 and >150 data elements in later years.
While chart audits confirmed overall data integrity, selected findings included 17 changes in eligibility status, 18
new protocol violations, and >200 requests for data clarification and modification. The CC found that chart audits
were an important part of the total monitoring plan, and that it was important to develop a flexible approach. We
will present the challenges of chart audits as part of a monitoring plan throughout the lifecycle of this complex
long-term multicenter trial.
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A27
Central Statistical Monitoring in Clinical Trials
Erik Doffagne1, David Venet1,2, Tomasz Burzykowski1,3, Marc Buyse3,4
1International
Drug Development Institute (IDDI), Louvain-la-Neuve, Belgium; 2Institut de Recherches
Interdisciplinaires et de Développements en Intelligence Artificielle (IRIDIA), Free University of Brussels ,
Brussels, Belgium; 3Interuniversity Institute for Biostatistics and statistical Bioinformatics (I-BioStat), Hasselt
University, Diepenbeek, Belgium; 4International Drug Development Institute (IDDI), Houston, TX, USA
Clinical trial sponsors are required to set up appropriate measures to monitor the conduct of the trial. The aim
of monitoring is to ensure the patients’ well being, compliance with the approved protocol and regulatory requirements, as well as data accuracy and completeness. Classical monitoring approaches that rely on on-site visits
are useful for some of these purposes, but extensive source data verification is extremely time consuming and
may have only a limited impact on data quality. It is therefore not surprising that the current practice of performing intensive on-site monitoring is coming into question and that interest focuses on more pragmatic, risk- based
approaches that improve the cost- effectiveness ratio without compromising the quality and integrity of clinical
trials. A recent draft guidance of the Food and Drug Administration (FDA) reflects this trend and states unequivocally: “FDA encourages greater reliance on centralized monitoring practices than has been the case historically,
with correspondingly less emphasis on on-site monitoring”.
In this presentation, we first review the potential sources of data errors in clinical trials. We then outline the principles of central statistical monitoring and the challenges of its implementation in actual trials. Results from both
terminated and on-going trials are presented to illustrate typical findings that can be expected from the monitoring approach. We conclude by a discussion of the potential role and limitations of central statistical monitoring,
and we argue that it can both optimize on-site monitoring and improve the quality of clinical trial data.
Reference: http://www.fda.gov/downloads/Drugs/Guidanc eComplianceRegulatoryInformation/Guidances /
UCM269919.pdf (accessed 10 November 2011).
A28
Risk-Based Approach to Monitoring: the Way of the Future
Patti Shugarts, Rene Kozloff, Ph.D., Selma C. Kunitz, Ph.D.
KAI Research Inc., an Altarum Company, Rockville, MD, USA
Due to a dramatic increase in the number and complexity of clinical trials and the costs associated with them,
the FDA recently introduced a draft guidance “Oversight of Clinical Investigations - A Risk-based Approach to
Monitoring”. This new guidance suggests it is acceptable to use alternative approaches to monitoring clinical trials including remote monitoring, centralized monitoring, and risk-based monitoring. The guidance also suggests
that source data verification should be focused on critical fields (key efficacy and safety variables) and less than
100% source data verification for less important fields may be acceptable. The guidance gives a clear signal
encouraging sponsors to explore cost-effective ways to conduct clinical monitoring instead of relying solely on
the on-site monitoring.
KAI Research, Inc. has used a variety of alternative approaches to assess data quality and patient safety in its
support of NIH clinical trials which often do not have budgets for 100% monitoring. We will describe lessons
learned from implementing risk based monitoring approaches that include a central data review to identify potential anomalies. The anomalies help to focus site visits. Focusing on critical data elements has also helped to
streamline monitoring visits. We have also implemented centralized monitoring techniques on a sample of data
from each of the sites in a study. Through a description of these examples, we will demonstrate alternative
methods for ascertaining data quality and subject protection that are both cost effective and efficient. We will
also describe how our monitoring plans consider complexity of the study, risk associated with the intervention
as well as its safety profile, severity of the illness of the study subjects and experience of the investigators and
study sites.
We will demonstrate that well thought out alternative approaches to monitoring can meet FDA’s expectations for
quality assurance and participant safety.
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A29
Effective Monitoring Strategies in a Long-Term Clinical Trial With
Varying Levels of Clinic Staff Knowledge: the AREDS2 Experience
Wendy L. McBee1, Sherrie Schenning, Traci E. Clemons, Emily Y. Chew, John Paul SanGiovanni
1The
EMMES Corporation, Rockville, MD, USA
Considerable time and expense are incurred to ensure data quality in a long-term clinical trial. The Protocol
Monitor assumes much of the scientific responsibility of closely checking the accuracy and completeness of
data collected prior to construction of the final data set. Administrative responsibilities involve assuring clinical
sites’ adherence to the protocol, federal guidelines and regulations. Eighty-two clinical sites participate in the
Age- Related Eye Disease Study 2 (AREDS2) and are following approximately 4,000 participants throughout five
years of follow-up. Data pertaining to effects of supplemental doses of xanthophylls and omega-3 fatty acids on
the progression of age-related macular degeneration and vision loss, among other clinical outcomes, are collected at annual visits. Four AREDS2 Protocol Monitors serve as the front line of communication between the
study leadership and the clinical sites. The Monitors employ multiple strategies to assist the sites in meeting
project deliverables. Routine performance includes standardized protocol review calls on a variety of topics and
frequent review of multiple types of data anomaly reports. Monitoring responsibilities constantly change in nature
and effort with the revolving door of new Clinic Coordinators and amendments or additions to the protocol through
the life of the study. When a new Clinic Coordinator is hired by a site, the Monitor must quickly determine the
Coordinator’s knowledge of the protocol, disease topic, and general skills required for the proper conduct of clinical trials. Some clinical sites have educational sessions in place or access to the previous Clinic Coordinator,
and others do not. The monitor also carries much historical knowledge of a site’s subject population and may
serve as a valuable resource to the new Clinic Coordinator. The many different hats of a Protocol Monitor, as
experienced in AREDS2, will be described as both a challenging and rewarding experience.
A30
Central Statistical Monitoring: a Model to Predict Fraud in Clinical Trials
Janice Pogue, PJ Devereaux, Kristian Thorlund, Salim Yusuf
McMaster Universtity, Hamilton, Ontario, Canada
It has been suggested that central statistical monitoring may serve as the foundation for quality assurance and
center monitoring in multicenter clinical trials (Knatterud 1998; Buyse 1999; Baiget 2008; Eisenstein 2008).
Authors have proposed that central statistical monitoring may identify procedural errors, data errors and data
fabrication at centers. Since there are no published evaluations of the different ways of performing central statistical monitoring to detect fraud, we constructed several prognostic models using data from a multi-center trial in
which the data from 9 of 196 centers were documented to be fabricated. These data were used to build a series
of risk scores to predict fraud at centers. Five different risk scores were identified and each had the ability to discriminate well between centers with and without fabricated data (area under the curve values ranged from 0.90
to 0.95). True and false positive rates are presented for each risk score to arrive at a recommended cut off of 7
or above (high risk score) out of a possible score of 12. We validated these risk scores, using an independent
multi-center trial database that contained no data fabrication and found the occurrence of false positive high risk
scores to be low and comparable to the model-building data set. With further validation, these risk scores may
become part of a series of tools that provide evidence- based central statistical monitoring, which in turn may
improve the efficiency of trials, and minimize the need for expensive on-site monitoring.
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A31
Identifying Optimal Outcome Measures for Phase II Trials in Cancer
Sarah Brown
Clinical Trials Research Unit, University of Leeds, Leeds, UK
Phase II studies in cancer usually consider short-term outcomes such as response, that are to some degree
‘surrogates’ of phase III outcomes, most typically overall survival (OS). Understanding the relationships between
phase II and phase III outcome measures is essential in designing phase II trials and understanding the degree
of reliability with which we can move between phases. We consider the association between alternative phase
II outcome measures and OS in advanced colorectal cancer (aCRC), to identify measures which may predict
treatment effect on OS in phase III trials. Phase II outcomes of response, disease control, continuous tumour
measurements and progression-free survival (PFS) were considered. Using surrogacy methodology originally proposed by Buyse et al (2000), estimates of R-squared(R2) were calculated to assess the relationship with OS
for each outcome. Individual patient data on 5435 patients from seven trials of aCRC, recruited between 1999
and 2007, were obtained. Data from three 3- arm trials were split to form two treatment comparisons each,
resulting in a total of 10 grouping units. As the reference outcome, response was found to have poor predictive
ability of the treatment effect on OS, with R2 (trial)=0.14, 95% CI (-0.28,0.56). A much stronger relationship was
observed for continuous tumour measurements (R2(trial) =0.65 (0, 0.86)) and PFS (R2(trial)=0.59 (0.18,1.00)).
The relationship between OS and disease control was slightly weaker, but still stronger than for response, with
R2(trial) =0.44, 95% CI (-0.05,0.93). Sensitivity analyses were performed to investigate alternative grouping units
and the impact of covariates. Issues faced in applying surrogacy methodology to the phase II setting, and using
these results to identify an optimal outcome measure for phase II aCRC trials, will be discussed. Specific issues
include the use of OS as an appropriate phase III outcome, comparability of R2 values for differing outcome
measures, and the number of grouping units incorporated.
A32
Experiences in Design and Implementation of Phase II
Trials in Chronic Lymphocytic Leukemia
Dena Cohen, Peter Hillmen, Julia Brown, Walter Gregory
University of Leeds, Leeds, UK
Since 2004, we have developed five phase II trials in Chronic Lymphocytic Leukaemia (CLL), utilising six different statistical methods. Two trials have closed to recruitment and three are currently open. The rationale behind
the different designs and methodologies used will be explained. Difficulties and learning experiences with the
implementation, wider understanding and interpretation of the trials will be discussed.
CLL201 used Gehan’s two-stage approach to assess response, and randomised to a control arm which was not
included for formal comparison, but to give validity of the study results. The two stage approach was difficult to
implement and of limited use as it only considered efficacy and not safety. Challenges were faced regarding the
inclusion and interpretation of the control arm, although randomisation proved to be valuable.
CLL207 was a single arm trial designed using Bryant and Day’s two-stage design, incorporating toxicity considerations as well as efficacy. The two-stage aspect worked well, but the implementation of a toxicity stopping guide
proved problematic.
ARCTIC and ADMIRE are two large, randomised phase IIb trials, both formally powered to compare responses
against a common control arm. One of the trials assesses non-inferiority. The choice of the unusual phase II
design, and difficulties in justifying it to reviewers will be discussed.
COSMIC is a randomised selection design with two experimental arms, combining two phase II trial designs to
firstly assess efficacy, and secondly select the treatment to be taken forward. The A’Hern one-stage design is
used to determine which treatments are eligible to be further investigated. In the case where both are acceptable, Sargent & Goldberg’s selection criteria will be used. The sample size was inflated to ensure acceptable
power for selecting the best treatment.
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A33
Defining Clinical and Statistical Improvement in Consolidation
or Maintenance Single-arm Trials in Oncology
A. Iasonos1, P. Sabbatini2, DR Spriggs2, H. Thaler1
1Department
of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer
Center, New York, NY, USA; 2Gynecologic Medical Oncology Service, Department of
Medicine, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
Single-arm Phase II consolidation/maintenance trials in oncology are currently designed to show an improvement
in Progression-Free Survival (PFS) when considered against historical controls. PFS includes duration of second
line therapy (SLT), treatment free interval (TFI), and time on the investigational therapy (IT). We hypothesize that
the duration of SLT, the time on the investigational therapy and patient enrollment plan can affect efficacy measures from maintenance trials and might result in underpowered studies. Efficacy data from four published singlearm consolidation therapies in second remission in ovarian cancer (Sabbatini et al, Gyn Onc 2010, 116(1):66-71)
are used for illustration. The studies were designed to show increase in estimated median PFS from 9 to 13.5
months (mos). We partitioned PFS as the sum of the duration of SLT, TFI, and duration of IT. We calculated the
statistical power when IT is given concurrently with SLT or following SLT by varying the start of IT. Required sample
sizes varied with duration of SLT. If IT starts with initiation of SLT, only 34 patients are needed to provide 80%
power to detect a 33% hazard reduction. Alternatively, if one accrues 34 patients at start of SLT with expected
33% hazard reduction and the duration of SLT delays the start of IT to 7.5 months, the power drops to 50%. To
maintain 80% power in this scenario, either the protocol therapy would have to reduce the hazard by 50%, or
sample size would have to increase to 104. A longer duration of SLT is associated with lower statistical power
unless the magnitude of benefit with the new investigational treatment is greater than expected, or the sample
size is increased. Designs of consolidation trials should take into account the duration of SLT, by either excluding
it from the definition of PFS or restricting it per protocol.
A34
Did Death Certificates and a Mortality Review Committee Agree on
Lung Cancer Cause of Death in the National Lung Screening Trial?
Pamela M. Marcus1, Ilana F. Gareen2, V. Paul Doria-Rose1, Jennifer
Rosenbaum3, Kathy Clingan3, Brenda Brewer3, Anthony B. Miller4
1NCI,
Bethesda, MD, USA; 2Center for Statistical Sciences and Department of Community
Health, Brown University, Providence, RI, USA; 3Westat, Inc., Rockville, MD, USA;
4Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
Background: RCTs frequently use mortality review committees to assign a cause of death (COD) rather than relying on COD assignments on death certificates (DCs). The National Lung Screening Trial (NLST), an RCT of lung
cancer screening with low dose radiation computed tomography versus chest x-ray among heavy and/or long-term
smokers, used a committee blinded to arm assignment to determine whether COD was due to lung cancer.
Methods: NLST’s committee reviewed a subset of deaths, chosen by a pre-determined algorithm. The algorithm
selected deaths with a DC COD that were most likely to represent a death due to lung cancer (either directly
or indirectly) and deaths that might have been erroneously assigned a DC lung cancer COD. Also included were
deaths within six months of a screen suspicious for lung cancer and within 60 days of certain lung cancer diagnostic evaluation procedures. Using the committee assignment as the gold standard and a lung cancer COD as
the outcome of interest, we calculated positive predictive value (PPV) and negative predictive value (NPV) of the
death certificate COD assignment (lung cancer vs. non-lung cancer).
Results: The committee examined and assigned COD for 1643 deaths (42% of the 3877 NLST deaths). Sensitivity
was 90%; specificity, 97%; PPV, 97%; and NPV, 88%. The kappa statistic was 0.87. 40% of the deaths with a
DC non-lung cancer COD reclassified to lung cancer had a DC COD of a neoplasm other than lung. Limitations:
2141 deaths with a DC-non lung cancer COD were not reviewed because the DC COD was unlikely to have been
in error. Had these deaths been reviewed and assigned a non-lung cancer COD, the specificity would have been
99% and the NPV 97%.
Conclusions: When assigning lung cancer COD among heavy/long-term smokers, death certificates provide accurate information nearly all the time.
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A35
Challenges of Creating and Managing Standards (common Data Elements) for Use in Clinical Trials
Patti Shugarts, Yun Lu, Ph.D., Stacie Trollinger, M.S., Kristy Miller, MPH, Selma C. Kunitz, Ph.D.
KAI Research Inc., an Altarum Company, Rockville, MD, USA
To streamline the implementation of clinical studies, reduce start-up time and accelerate data aggregation across
studies, the National Institutes of Health (NIH) together with KAI Research, Inc. (KAI), embarked on common
data element (CDE) projects. KAI has developed a systematic approach to the development and implementation
of data standards. These standards span the entire study lifecycle, facilitating study start up, data collection
and management, and data archiving and sharing. With more and more CDEs developed, establishing standard
approaches to manage CDEs becomes critical.
This abstract will provide information on the challenges with creating, implementing and managing standards.
The challenges as well as our best practices in overcoming these challenges are:
-K
eeping up with current standards (CDISC, caBIG, etc.) o Harmonization efforts ongoing o Regular communications with these groups key
-R
eviewing the Literature o Including references for the CDEs adds credibility o Publications may lack detailed
data management information
- L imiting the universe o Identification of core CDEs (those most essential for data collection) o Build from existing forms to gain buy in from the clinical research community
-C
reating a team of experts o Identifying who should be part of the team o Advantages and disadvantages to top
down vs. bottom up development
-E
stablishing standard procedures for standard development o Development of standard procedures in parallel
to standards o Internal standard review committee for quality and consistency
- T ools to enhance use o Dictionary, template forms, suggested edits, data management plan (DMP), etc. o
Website design/ layout - making it user friendly.
The process for creating, implementing and managing standards has been met with many challenges but the
benefits outweigh the frustrations. CDEs and standards have demonstrated enhanced data quality, decreases
the time and resources needed to develop a study database, and helps customize the DMP.
A36
Future of Data Exchange and Data Mining: Posting Data on the
Grid by a Dental Practice-Based Research Network
Sherita Alai
The EMMES Corporation, Rockville, MD, USA
The Practitioners Engaged in Applied Research and Learning (PEARL) Network, a National Institute of Dental and
Craniofacial Research- sponsored network of practice-based dentists have successfully created a data service
on the cancer Biomedical Informatics Grid’s (caBIG’s) open source platform (caGrid). PEARL has registered the
semantically annotated model and implemented the necessary registration interface steps and posted the deidentified clinical data on the caGrid.
PEARL has taken the needed steps to create harmonized, semantic metadata in order to leverage the collaborative nature of caBIG with use of caBIG grid architecture and services. PEARL created the metadata based
on the International Organization for Standardization Metadata 11179 Model in the Cancer Data Standards
Repository (caDSR) which uses the semantic linkages of the hierarchical ontology contained in the National
Cancer Institute’s Enterprise Vocabulary Service. New components created by PEARL are:
• 1321 Data Elements • 999 Data Element Concepts • 254 Value Domains
PEARL used caBIG grid architecture to share Oral Health Inventory Profile and Tooth Sensitivity data from a study
of postoperative hypersensitivity (Study PRL0602) following resin-based composite restoration of posterior teeth.
The related Unified Modeling Language (UML) model for this data set has been registered in the caDSR where
65
the related CDEs are classified as part of the UML model and visible in the UML Model Browser as a collection.
PEARL encountered some challenges during implementation. Firstly, some issues and bugs had to be resolved
with the system configuration and web services communication that required additional steps between PEARL
and the caGrid team. Additionally, the caGrid data extraction process is not as intuitive as anticipated, and
requires detailed instructions to overcome this barrier to data sharing.
The projected benefit is that exposing clinically relevant data and the needed descriptive metadata that underpins
those data provides informed, meaningful access to researchers, clinicians, and patients.
A37
The Future of the caBIG® Clinical Trials Software Development
Mission: Engaging the Open Source Community
Robert Annechiarico, Mohammad Farid, Madeline Carroll, Kimberly Johnson
Duke University, Durham, NC, USA
The Clinical Trials Management Systems (CTMS) workspace within the caBIG® program was tasked to deliver
integrated software solutions to the clinical research community. These tools are vetted by the community, who
require the ability to securely gather, exchange, explore, integrate, and reuse data and information for clinical trials research. As a result the CTMS Workspace developed modular, interoperable and standards-based software
tools designed to meet diverse clinical trials data management needs. The tools developed were configurable
to work within trial sites with little or no clinical data management systems in place, as well as those sites with
extensive existing systems. These tools took into account the diversity of clinical research activities and local
practices that existed among trial sites.
CTMS software tools enable management of clinical trials tasks such as: patient registration; patient scheduling; integration of laboratory results; adverse events capture/reporting; and the capture, analysis and sharing of
clinical data among relevant systems. All tools are also available as a modular enterprise clinical trials management system designed to facilitate clinical workflows and data sharing in single and multi-site settings for use
in trial sites.
To continue the development/support of these tools with community and industry participation, the caBIG® program is evolving from its role as an active software developer to a facilitator of open source, community-based
development. The NCI will provide a range of mechanisms to support open-source development efforts, including:
•Processes to report software defects and suggest feature requests, •Forums for information exchange,
•Resources for software version control and distribution, •Support of an open source governance framework
with an emphasis on standards.
We will discuss the implementation plan and the crucial factors for the continued development of these tools
through the open-source model, and how this will serve the ultimate mission of furthering cancer research.
A38
CDISC Data Standards Can Facilitate Composition of Adverse Event Narratives
Anisa Scott, Richard Zink
SAS Institute, Cary, NC, USA
When a clinical trial subject has a serious adverse event (SAE) or other significant adverse event (AE), such as
those leading to the discontinuation of the study, a narrative is written for the clinical study report. These AE
narratives summarize the details surrounding the event to enable understanding of the circumstances that may
have led to the occurrence and its subsequent management. Such details may include the dose of study drug
at the time of the event, the duration of the dose prior to the event, concomitant medications taken at the time
of the event and used to treat the event, and other AEs that may have recently occurred. Other details include
demography, medical history, laboratory results, the severity of the event and whether the event was related to
study medication. Narratives are typically written from the original SAE report faxed from the clinical site in combination with data listings generated as part of the study deliverables. Information contained in the typical narrative
requires manual review of these disparate data sources. This is time- consuming and often will require additional
review and quality control. Too often, these narratives are written when the full data becomes available, which
66
may become a rate-limiting factor in completing the study report. Since its inception in 1997, the Clinical Data
Interchange Standards Consortium (CDISC) has developed standards for data models, study design and supporting clinical trial documents. CDISC standards have made such gains that the Center for Drug Evaluation and
Research strongly encourages their use and implementation for the submission of new drug applications. The
benefits of CDISC standards for statistics, programming and data management are well established. We will
illustrate how these data standards can be used to facilitate composition of adverse event narratives.
A39
Actual Versus Reported Participant Consent Practices in Cluster
Randomized Trials: an International Survey of Trialists
Shazia H. Chaudhry1,2, Monica Taljaard1,2, Jamie C. Brehaut1,2, Robert Boruch3,
Allan Donner4, Martin P. Eccles5, Andrew D. McRae6, Raphael Saginur1,7,
Charles Weijer8, Merrick Zwarenstein9, Jeremy M. Grimshaw1,2
1Ottawa
Hospital Research Institute, Clinical Epidemiology Program, Ottawa Hospital, Civic Campus,
Ottawa, Ontario, Canada; 2Department of Epidemiology and Community Medicine, University of Ottawa,
Ottawa, Canada; 3Graduate School of Education and Statistics Department, Wharton School, University of
Pennsylvania, Philadelphia, PA, USA; 4Robarts Clinical Trials, Robarts Research Institute, London, Ontario,
Canada; 5Institute of Health & Society, Newcastle University, Newcastle upon Tyne, UK; 6Division of
Emergency Medicine, University of Calgary, Foothills Medical Centre, Calgary, Alberta, Canada; 7Department
of Medicine, University of Ottawa, Ottawa, Canada; 8Departments of Philosophy and Medicine, Joseph
L. Rotman Institute of Science and Values, University of Western Ontario, London, Ontario, Canada;
9Centre for Health Services Sciences, Sunnybrook Health Sciences Centre, Toronto, Canada
Background: Unique characteristics of cluster randomized trials (CRTs) complicate the interpretation of standard
research ethics guidelines, including from whom, when, and how informed consent ought to be obtained. As part
of a larger project to generate ethics guidelines for CRTs, we reviewed a random sample of 300 published CRTs
and found that participant consent was reported in only 63% of trials. Whether this reflects an under- reporting of
consent, or actual consent practices, is unclear. We therefore conducted a survey of the CRT investigators to (a)
gather detailed information about consent practices in the selected CRT, and (b) investigate factors associated
with obtaining participant consent in CRTs.
Methods: A web-based survey was administered to corresponding authors of the sample of CRTs, in a series of
six contacts. Trialists surveyed were based in USA/Canada (47%), UK/Ireland (18%), elsewhere in Europe (21%),
Australia/New Zealand (5%), and various low/middle income countries (9%).
Results: The survey response rate was 64%. Participant consent had been sought for some aspect of the study
in 93% of trials: in 79% of trials consent had been sought from participants at the individual level (56% for the
experimental intervention(s), 75% for data collection). Among CRTs with participants at the cluster level, 82%
indicated that consent had been sought from cluster level participants (62% for the experimental intervention(s),
75% for data collection). Factors associated with individual level consent for the experimental intervention(s)
were a smaller cluster size, and whether experimental and data collection interventions were targeted at the
individual level. In addition, setting (healthcare vs. non-healthcare) was associated with seeking individual level
consent for data collection.
Conclusion: Unique characteristics of the CRT design are associated with participant consent practices, which
are under-reported in CRT publications. Further ethical analysis is required to determine whether CRT consent
practices meet the highest ethical standards.
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A40
Post Trial Access to Successful Products: Ethical and Practical Dilemmas
Liza Dawson
NIH/NIAID Division of AIDS Research Ethics Team, Bethesda, MD, USA
In some cases it is difficult for study participants to obtain access to a successful study intervention after the
conclusion of a clinical trial. A number of international ethical guidelines call for researchers to provide access
to products post trial for study participants when they are proven effective and unavailable through local mechanisms. The nature of this ethical obligation is debated, and the moral basis for such an obligation should help
determine who bears responsibility for fulfilling it. There is no consensus among bioethicists about whether this
is a firm obligation and if so, whether it is based on the idea of reciprocity or gratitude, as a safeguard against
exploitation, as compensation for risk or burden, or some other basis. Also, ethical analysis is complicated by
the fact that other community members who need the same medical care may have a competing claim for access
to the product. Moreover, practical challenges in ensuring post trial access are numerous, and often multiple
stakeholders need to be engaged. An interesting consequence of the call for post trial access is that many
pharmaceutical companies decline to participate in research studies in countries where they have no plans to
register their products. When studies are conducted in developing countries, challenges may arise due to slow or
non-existent regulatory structures, lack of funds for product procurement and delivery, and lack of infrastructure.
For research sponsors such as NIH, lack of authorization to use funds for non- research purposes may hamper
efforts to support post trial access. These ethical and practical challenges will be discussed in detail, with recommendations for future policies to address them.
A41
Ethical Issues in Cluster Randomized Trials: International
Survey of Research Ethics Chairs
Monica Taljaard
Ottawa Hospital Research Institute
Background: Cluster randomized trials (CRTs) have unique characteristics that complicate the interpretation of
standard research ethics guidelines. We conducted an international web-based survey of research ethics chairs
in advance of a consensus meeting to generate ethics guidelines for CRTs.
Methods: We included all biomedical ethics committees in Canada and the UK, and a random sample from the
USA (one per institution). After the initial e-mail invitation, we sent three e-mail reminders and a final postal
reminder. The 45-minute questionnaire presented three hypothetical CRTs evaluating: a community-level health
promotion intervention, an educational intervention targeted at health professionals, and distribution of insecticide-treated bed nets to villages in a low income country. Using closed- and open-ended items, participants
were asked to indicate the type of review required (full board or expedited), whom they would consider research
subjects, and objections that might be raised
A42
Exception From Informed Consent (EFIC): Experiences From a
Randomized Trial in Pediatric Emergency Patients
1
Caroline Kim , Traci Clemons1, Diane Brandt1, James Chamberlain2, Bambi Bademosi2
1
EMMES Corporation, Rockville, MD, USA; 2Children’s National Medical Center, Washington, DC, USA
“Use of Lorazepam for the Treatment of Pediatric Status Epilepticus: A Randomized, Double-Blinded Trial of
Lorazepam and Diazepam” (Status2), is a protocol conducted under the Best Pharmaceutical for Children Act
(BPCA) to evaluate efficacy and safety of lorazepam compared to diazepam in pediatric patients presenting to
the emergency department (ED) in status epilepticus (SE).
Because of the potentially life threatening presentation, the narrow therapeutic window, and the lack of proven,
effective treatments for SE in the pediatric population, this study was approved under the auspices of 21 CFR
50.24, the Exception from Informed Consent (EFIC) for Emergency Research.
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Navigating the regulatory requirements required significant sponsor, study management and site resources. The
design of the protocol included informed consent, data collection and follow up procedures to assure protection
of human subjects under EFIC. All sites (14) conducted community consultation and public disclosure activities
that were reviewed and approved by the sponsor and local IRBs. The sponsor created training materials on the
EFIC regulations to educate study personnel and local IRB members and to assist with community consultation
planning. Opt-out procedures were implemented at each site and nationally prior to study initiation. Due to the
emergency nature of SE, protocol deviations were common. These included incorrect weight estimation and therefore inaccurate dosing, and failure to adhere to timely study procedures. Study monitoring included assuring that
legally authorized representatives of study subjects were approached in a timely manner and that opt-out and
study procedures were followed in accordance with the study protocol.
In conclusion, significant resources are required to meet the requirements of the Exception from Informed
Consent regulations. Emergency conditions may preclude a carefully controlled study environment, so good training and monitoring are required to ensure that all protocol deviations are accurately recorded and reported to
local IRBs.
A43
Streamlined Drug Induced Liver Injury Detection With
Hy’s Law and Temporal Visualization
Kelci Miclaus
SAS Institute Inc., Cary, NC, USA
Drug Induced Liver Injury (DILI) is the most common safety-related reason for withdrawing a drug from the market.
Therefore, it is critical to assess potential hepatotoxicity from treatment using an analysis of liver-related laboratory tests. A starting point is to plot peak values of lab measurements with regard to the upper limit of normal
reference ranges to identify patients with elevated levels of bilirubin and alanine aminotransferase as potential
Hy’s Law cases. However, this plot alone does not acknowledge the temporal considerations of Hy’s Law and
liver injury. Following the FDA Guidance of DILI evaluation, this view can be augmented to flag patients based
on the occurrence of elevated liver tests within a clinically- relevant time period. Moreover, by incorporating the
temporal dependence of liver test elevations, the frequency and duration of Hy’s Law instances across treatment
groups can be interrogated and reported. This presentation will highlight a statistically-driven interactive visualization approach implemented in JMP Clinical software to streamline the detection of potential DILI cases through
summary views of lab test elevations and Hy’s Law occurrence that lead to targeted patient time trend plots and
cross-domain profiles for further clinical insight.
A44
Summarizing the Incidence of Adverse Events Using
Volcano Plots and Time Windows
Richard C. Zink, Russ Wolfinger, Geoffrey Mann
JMP Life Sciences, SAS Institute, Inc., Cary, NC, USA
It can be challenging to perform a concise and easily-interpretable analysis of adverse events (AEs). For therapeutic areas where patients have frequent AEs, understanding the safety profile of a new intervention is critical.
In these instances, however, understanding the analysis is made more difficult by the sheer number and variety
of AEs that occur.
Traditionally, the incidence of adverse events is presented in lengthy tables, with coded AE terms grouped by
body system or system organ class and presented in order of descending frequency. Many times, statistical
testing is not be performed due to the high likelihood of committing multiple Type I errors. Further tables may
highlight AEs that occur for specific periods of time (for example, treatment phase or off-treatment follow-up).
Needless to say, it is difficult to summarize this information to gain a clear understanding of the risk (or benefit)
a new therapy may present.
Incidence analyses of adverse events are straightforward to present graphically using Volcano Plots to highlight
treatment differences. Color indicates the treatment with higher incidence, with bubble size representing the
total number of events that occur during the trial. Adjustments for multiple comparisons can be presented in a
69
manner to clearly indicate which events exhibit statistically significant treatment differences. Further, the study
can be broken into distinct time windows, with multiple plots or animation displaying changes in adverse event
risk over time. This presentation can emphasize early differences across treatments that may eventually resolve
or highlight events that could approach significance given a longer study duration.
The use of Volcano Plots is illustrated with an analysis of data on aneurysmal subarachnoid hemorrhage.
A45
Reducing Surveillance Bias in Adverse Events
Reporting in an Unmasked Treatment Trial
Mae Gordon, Julia Beiser, Patricia Morris, J. Phillip Miller,
Michael Kass for the Ocular Hypertension Treatment Trial
Washington University School of Medicine, St. Louis, MO, USA
We describe the challenge of collecting adverse events (AE) data in an unmasked randomized treatment trial.
The Ocular Hypertension Treatment Study randomized 1,636 participants to either observation or to treatment
with eye drops to lower intraocular pressure (IOP) to prevent the development of glaucoma. Masking would have
been impossible to maintain. Participants could become unmasked at free IOP screenings or non-study eye
examinations. Clinic personnel would become unmasked by measuring IOP to adjust medication to achieve IOP
treatment targets. Efficacy outcomes were masked, but AE data were collected by unmasked clinic personnel and
participant self-report. At 24 months, 774 AE’s had been received, 31% in the observation group and 69% in the
medication group. The clinic to clinic rate in AE reporting ranged from 7% to 60% signaling a standardization problem. To improve standardization, we reduced branching logic, consolidated forms, included more check boxes
and used a scripted interview. The Data Safety Monitoring Committee recommended that AE data received prior
to these protocol changes be excluded from future publications. In the 18 months after these protocol changes,
1,688 AE reports were received, more than double the previous rate, 44% of the AE’s were in the observation
group and 56% in the medication group. It is striking that the differential between groups decreased from 38% to
12%. This suggests that potential surveillance or detection bias in an unmasked treatment trial can be reduced
by a rigorous protocol.
A46
Assessments for Safety and Efficacy in Cardiovascular
Cell Therapy Clinical Trials
Adam M. Mendizabal, Erica Anderson, Melinda Tibbals, Nilay Shah, Robert Lindblad, Shelly Carter
Stem cell clinical trials for cardiovascular disease in the last decade have been well tolerated with preliminary
evidence suggesting efficacy. Standardization of endpoints is important to facilitate comparisons across studies. We describe our methods of safety and efficacy assessment based on our experience coordinating multiple
studies using various cell populations and administration methods.
Adverse events (AEs) are collected after enrollment, evaluated by independent medical monitors throughout the
trial and coded using the most current version of the Medical Dictionary for Regulatory Activities (MedDRA) and
reviewed every 6-months by an independent Data and Safety Monitoring Board. Major Adverse Cardiac Events
(MACE) are defined as death, hospitalization for heart failure or non-fatal recurrent myocardial infarction. Patients
are evaluated for complications during study product administration and within 24-48 hours. Cardiac enzymes
(CK-MB and Troponin) are collected every 12 hours for the first 48 hours. Echocardiograms are performed following the procedure and within 24-48 hours to assess for pericardial effusions. Incidence of arrhythmias is
assessed by ambulatory electrocardiograms. Hospitalizations are adjudicated independently and classified as
cardiac related or not. Ectopic tissue formation is assessed using CT scan.
Functional benefit is evaluated using New York Heart Association Class, Six Minute Walk Test, Peak VO2, and
forced expiratory volume in 1 second. Quality of life is measured by the Minnesota Living with Heart Failure
Questionnaire (MLHFQ). Cardiac magnetic resonance imaging is used for assessing global and regional function.
Patients who are device dependent undergo cardiac CT at baseline and 12 months.
Clinical trials of cardiovascular cell therapy are expanding due to the excellent safety profile and early signs of
70
efficacy. Safety is paramount and constantly monitored. Centralized cores such as imaging labs are important to
maintain consistency and independence. As therapies evolve, consistency in the endpoint assessment should
be considered to ensure comparability across studies.
A47
Shrinking the Global Village: the Challenges of Trial
Management in an International Multi-Centre Trial
Claire Cochran, Jennifer Burr, Augusto Azuara-Blanco, Pauline Garden,
John Norrie, Alison McDonald, Gladys McPherson on behalf of the EAGLE group
Univeristy of Aberdeen
Randomised Controlled Trials (RCTs) require efficient subject recruitment and retention. Often the management
of such a trial poses significant challenges.
EAGLE (Effectiveness, in Angle closure Glaucoma, of Lens Extraction) is an international multi-centre, pragmatic,
publicly funded randomised controlled trial (RCT). EAGLE addresses whether removal of the lens of the eye for
newly diagnosed Primary Angle Closure Glaucoma results in better clinical, economic and patient focussed outcomes compared with standard management.
The EAGLE management team are UK based; however identification, recruitment and three year participant follow
up is executed by staff working in sites across the UK, Malaysia, Hong Kong, Singapore, (Peoples Republic Of)
China and Australia. The EAGLE study design requires minimal direct contact between the UK management team
and the participant. The maintenance of effective working relationships between the UK management team and
the international recruiting teams is, therefore, crucial to project success.
To conduct EAGLE across different health care, legal, and cultural settings, a robust but pragmatic protocol was
designed. A process for individual site assessment in terms of suitability as a recruiting site was developed
involving honest discussion of trial budget and realistic timelines at outset. Maintaining momentum and focus
on the research question among collaborators was addressed through site visits, regular scheduled video conferences, newsletter bulletins and an ongoing training regime of bespoke design that altered as appropriate when
the trial matured and entered new phases. Global teleconferences were negotiated across time zones. Escalating
costs of printing and translating trial paperwork into three different languages required re-profiling of a fixed budget without compromising trial delivery.
This paper describes the challenges encountered in EAGLE across the first half of its data collection journey and
the strategies employed to overcome them. The EAGLE study experience is widely applicable to any centrally
managed international multi-centre RCT.
A48
The Use of Central IRBs for Multicenter Clinical Trials
Devon K. Check, Kathryn E. Flynn, Judith M. Kramer, Kevin P. Weinfurt
Duke Clinical Research Institute; Durham, NC, USA
Background: Multicenter clinical trials are designed to generate data that may be generalized across diverse
populations with the goal of facilitating unbiased answers to important medical questions. The Food and Drug
Administration, the Office of Human Research Protections, and the Department of Health and Human Services
(DHHS) support the use of a centralized IRB review process, that is, a single IRB of record for a given protocol,
to improve multicenter trial efficiency. Most recently, the DHHS proposed to change the Common Rule to include
mandated centralized review for multicenter trials; however, there are concerns that the benefits of centralized
review have not been sufficiently demonstrated.
Methods: We identified published articles relating to centralized review through PubMed and hand searching. We
categorized articles by topic and type (commentary or empirical research).
Results: Our review includes 78 sources. Of these, 22 articles describe inefficiencies and inconsistencies with
multiple review (12 empirical), 4 articles compare multiple to central review (1 empirical), and 5 articles describe
barriers to the adoption of central review (1 empirical). The single empirical study directly comparing multiple and
central review showed that affiliation with a central IRB was associated with faster reviews and financial savings.
71
Several limitations of the empirical work were noted: 1) Absent a standardized metric for measuring review quality, all studies focus on efficiency, without informing the debate over the ethical quality of central versus local
review, 2) Methodological quality is weak, as the majority of articles are case studies using a sample size of
less than 20, and 3) The existing empirical work is not generalizable, as it is unclear how descriptions of prior
practices would carry over to a still-undefined system of mandated centralized review.
Conclusions: The limitations of the existing empirical work constrain meaningful conclusions about centralized
review.
A49
Tracking of Regulatory Documents in a Large Clinical Trial,
the Age-Related Eye Disease Study 2 (areds2)
1
Sherrie Schenning , Wendy L. McBee, Traci E. Clemons, Emily Y. Chew, John Paul SanGiovanni
1
The EMMES Corporation, Rockville, Maryland
The storage and tracking of regulatory documents in a large, long-term clinical trial can quickly become unmanageable without a proper tracking system. Gone are the days of manual files, as clinical trials move to the use
of electronic regulatory tracking databases. The Age-Related Eye Disease Study 2 (AREDS2) is a multi-centered
clinical trial designed to assess the effects of oral supplementation of high doses of macular xanthophylls and/
or omega -3 fatty acids for the treatment of age-related macular degeneration and cataract in just over 4,000
participants. The Administrator and Protocol Monitors at the AREDS2 Coordinating Center have the immense task
of tracking regulatory documents for the 82 clinical sites and the 1200 past and present clinical site personnel.
A customized electronic regulatory tracking system, Site Management Utility (SMU), was implemented to manage all regulatory documents including those required for study activation at participating sites. SMU enables
staff to efficiently track such documents as IRB approvals, medical licenses, Human Subject Protection Training
notifications, and protocol specific certifications. The utility also allows the Coordinating Center to maintain a full
project contact list and archive of present and former staff. During the study start-up phase, SAS reports linked
to regulatory information in SMU were generated to monitor completion of all requirements for study activation.
Throughout study follow- up, a SAS program was run to generate automatic email reminders to the clinical sites
at 60, 30, and 7 days prior to IRB and/or medical license expirations. SMU and other effective tools utilized at
the Coordinating Center will be highlighted during this discussion of efficient methods of regulatory tracking and
storage.
A50
Electronic Health Record Systems for Medical
Research Project Stakeholder Management
Elizabeth Thomson, Derek Warren, Ian Ford, Dipak Kalra, Mats Sundgren and
Georges De Moor on behalf of the EHR4CR Research Consortium
Robertson Centre for Biostatistics, University of Glasgow, Glasgow, Scotland
EHR4CR (Electronic Health Records for Clinical Research) is a research project funded by the European Union
Commission and the European Federation of Pharmaceutical Industries and Associations (EFPIA) within the
Innovative Medicines Initiative framework. EHR4CR is a collaborative project involving primarily universities, the
pharmaceutical industry with input from organisations and groups representing patients and covering aspects of
the law, ethics and technologies associated with the use of electronic data for research purposes.
The EHR4CR project aims to improve the efficiency of, and reduce the cost of, conducting clinical trials, by better
leveraging routinely collected clinical data through development of both an EHR4CR platform (primarily tools and
services) and implementing an innovative and sustainable EHR4CR business model.
Introducing innovative technology involves cost, new ways of working and organisational change. The multinational scope of the project means that every effort must be made to ensure that the approaches, methodologies
and technologies conform to local and international legal and ethical requirements related to data protection,
privacy and confidentiality. The project must also conform to the standards required by national and international
drug regulators (MHRA, EMA, FDA, etc.) and satisfy the needs of the pharmaceutical industry. The approaches
taken also need to be acceptable to the general public, patients, medical professionals (both study investigators
72
and otherwise), and also to politicians and professional bodies sensitive to the concerns of their constituencies.
Proactive management of the complex network of European stakeholders external to the EHR4CR project team is
an essential task which will continue throughout the full four year lifecycle of the EHR4CR project. This presentation describes a pilot exercise that has been carried out in Scotland in order to develop a best practice approach
for local national stakeholder identification, analysis engagement and management during the development
phase of the EHR4CR project. A summary of the key outcomes of the Scottish pilot activity and the planned next
steps for roll out of the stakeholder management process across Europe will be presented.
A51
Exploratory Biomarker Analysis for Randomized Phase 2 Oncology Trials
Hongjie Deng, Rui (Sammi) Tang, Li Chen, Mike Hale
Amgen Inc. Thousand Oaks, CA, USA
Randomized Phase 2 oncology trials are mainly aimed at demonstration of improved efficacy (e.g. improved
Progression Free Survival, Overall Survival) and acceptable safety profile of the target therapy versus the control
therapy. With the development of the new bio-assay technology, biomarkers may provide an important role in
demonstrating mechanism of action and pathway intervention of drugs and provide preliminary evidence of treatment effect of the target therapies. In addition, biomarkers may also be used to select patients who are mostly
likely to benefit from the treatments. Based on preliminary biological hypothesis of the biomarkers, data generated from Phase 2 studies can be used to identify biomarkers that have predictive potentials on treatment effect.
The potential predictive effect of biomarkers can then be further tested in large Phase 3 trials with adequate
planning to provide more definitive evidence of the utility of the biomarker for patient selection.
In this presentation, we will discuss the exploratory statistical analysis of biomarker data for randomized Phase
2 oncology trials and the impact of the analysis on Phase 3 study designs. Both continuous and categorical
biomarker data will be discussed. Applications of statistical methodology including survival analysis, subgroup
analysis, logistic regression analysis and time dependent ROC curves will be presented. Potential confounding
factors of the biomarkers will be discussed. Experience on practical considerations in exploratory biomarker data
analysis such as data collection and transfer, potential un-blinding, ascertainment rate will be shared.
A52
Leveraging Enrichment Design Methods to Improve the
Likelihood of Success of Clinical Trials
Imogene Grimes1, John Schoenfelder2
1Otsuka; 2Abbott
Ostuka Pharmaceutical Development & Commercialization, Inc., Rockville, MD, USA
The sponsor owns the responsibility for a clinical study to comply with the protocol, including enrollment of
patients who meet eligibility requirements. It is the responsibility of the investigator to give the best care available to patients. Struggles sometimes result when investigators, who have enthusiasm and optimism that a
particular investigational drug will benefit their patients, have disappointment when trial eligibility criteria exclude
patients that they want to enroll in a study. Patients who are enrolled into studies when they are on the edge
of eligibility can chip away at the statistical power of a study to demonstrate treatment benefit. From the statistical perspective, having a homogeneous population with a smaller variance can have more statistical power
for analysis than having a larger sample size when the population is more heterogeneous and the variability is
greater. The enrichment design (referenced in FDA’s Adaptive Design Clinical Trials for Drugs and Biologics, Draft
Guidance; CBER, CDER, 10 February 2010) when supported by a conditional sequence of hypothesis tests using
methodologies proposed by Bauer (cited in the FDA’s draft guidance on adaptive designs) offer an opportunity
for a trial to enroll heterogeneous populations while protecting the ability for the study to be positive. Strategic
utilization of the enrichment design can improve the likelihood of success of a study by using Bauer closed procedures. The proposed methodology has two major advantages: (1) using the conditional sequence of hypothesis
tests to control multiplicity, alpha can be 0.05 for each hypothesis test while preserving the overall study-wise
alpha at 0.05; and (2) it allows patient recruitment to permit “all comers” in the study protocol while protecting
the primary analysis to be done in a subpopulation enriched with patients in whom the benefit may be easier to
measure, hence, demonstrate
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A53
Survey of Commonly Used Analytical Methods for
Analyzing Biomarkers With Limit of Detection
Tulay Koru-Sengul, John D. Clark III, Manuel A. Ocasio, Lora E. Fleming, David J. Lee
University of Miami, Miami, FL, USA; Kaiser Permanente, Los Angeles, California,
USA; European Centre for Environment and Human Health, Peninsula College of
Medicine and Dentistry, Universities of Exeter and Plymouth, Cornwall, UK
Biomarkers are laboratory measures of biological processes. Because they are viewed to be objective and quantifiable by providing valuable information in both assessing exposure and disease status, they are increasingly
used in biomedical and public health sciences, drug development programs, testing for targeted therapeutics and
personalized medicine. This increased use creates a venue for the development of methods to address important, unexplored analytic issues such as properly handling biomarker measurements below the limit of detection (LOD). Researchers working with biomarker data inevitably have to deal with data containing non-detects,
and how to combine non-detects with values above the LOD for data analysis. The common statistical analysis
approach has been either to exclude measurements with LOD or perform ad-hoc single imputation techniques.
Ad-hoc imputation techniques include replacing each measurement below the LOD with a value such as zero, a
half of the detection limit, or LOD value itself, and then conducting the analysis under the assumption that the
imputed values are the actual observed values. However, there are other parametric and nonparametric statistical methods, such as model based single imputation methods, Reverse Kaplan-Meier method, and multiple
imputation methods that are not widely used in the literature but are better alternatives to ad-hoc single imputation techniques. We will facilitate broader use of all of these methods by describing their properties, illustrating
their use with population-based data for secondhand smoke exposure research and showing how they can be
calculated using standard software. This work was funded in by FAMRI, NIH, NIOSH.
A54
A Phase II Design With Direct Assignment Option for Initial Marker Validation
Ming-Wen An, Sumithra Mandrekar, Daniel Sargent
An - Vassar College, Poughkeepsie NY USA; Mandrekar & Sargent - Mayo Clinic, Rochester, MN, USA
Biomarkers are a critical component of targeted therapies as they can be used to identify patients who are more
likely to benefit from a particular treatment. Several prospective clinical trial designs for biomarker directed
therapy have been previously proposed including the marker-stratified, sequential testing strategy, adaptive, and
enrichment designs. These designs differ primarily in study populations (marker-defined or all-comers) and randomization scheme (fixed or adaptive). Recognizing the need for randomization yet acknowledging the possibility
of remarkably promising results at interim, we propose a two-stage Phase II marker-positive design that allows for
direct assignment in Stage II. In particular, Stage I of our proposed design randomizes marker- positive patients
equally to receive targeted therapy or control, while Stage II has the option to adopt “direct assignment” whereby
all Stage II patients receive the targeted therapy. Through simulation, we study the effect of varying the alpha
decision cutoffs at interim and timing of interim analysis on power and Type I error rate. We compare our design
with a balanced randomized two-stage design. Our results suggest relatively minimal loss in power (<2%) and
increase in Type I error rate (<5%). A sensitivity analysis to examine the possible effects of a population shift
also suggests relatively minimal inflation of power, compared with no population shift. Our design has a greater
appeal to clinicians and patients with its direct assignment option, while maintaining relatively desirable statistical properties. The direct assignment, if adopted in stage II, provides for an “extended confirmation phase” as
an alternative to stopping the trial early for efficacy which may help to avoid possibly prematurely launching into
a Phase III trial, thereby potentially addressing the high failure rates of Phase III trials.
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A55
Use of a of a Formal Study Run-In Phase to Reduce Recruitment Errors in a
Multi-Centre Randomized Controlled Trial: Is Quality Better Than Quantity?
Gordon S. Doig, Fiona Simpson, Elizabeth A. Sweetman
Northern Clinical School Intensive Care Research Unit, University of Sydney, Australia;
Royal North Shore Hospital, Intensive Care Unit, Sydney, NSW 2065, Australia.
Introduction: Major protocol violations occur more frequently during the early stages of a clinical trial, when investigators are less familiar with study processes. Recruitment errors arise when study eligibility criteria are violated
and can account for 50% of all major protocol violations. Study Objectives: To determine whether a formal study
run-in phase can improve familiarity with study eligibility criteria and reduce recruitment errors.
Methods: Prior to starting a multi-centre clinical trial, participating centres were required to submit de-identified
potentially eligible patients to a study web site. The run-in web site did not allocate patients to treatment or control groups however, the information captured allowed true eligibility to be assessed. Appropriateness of enrolment was fed back to the participating centre. Each centre was required to demonstrate proficiency at identifying
consecutive truly eligible patients before being allowed to start the trial.
Results: Thirty-two centres submitted 199 potentially eligible patients to the run-in site. 32 of 199 (16%) patients
did not meet eligibility criteria (recruitment errors). After successful completion of the run-in phase, at the time of
this analysis participating centres had enrolled 409 patients into the trial, with four (1%) recruitment errors (16%
vs 1%, p<0.001). This is significantly lower than published benchmarks obtained from FDA Phase III licensing
trials (PROWESS 159/1690, p<0.001 and INTERSEPT 77/531, p<0.001).
Conclusions: A formal run-in phase that provides performance feedback can improve familiarity with trial eligibility
criteria and significantly reduces recruitment errors. If a multi-centre trial does not offer a formal run-in phase,
we strongly urge local investigators to conduct their own formal run-in phase.
A56
Patients and Clinical Trials: How Improve Their Participation ?
Carlo Tomino
Italian Medicines Agency, Rome, Italy
It will be explain the results of a large communication project performed by the Italian Medicines Agency (AIFA),
together with the Italian Society of General Practitioners and the Italian Federation of Family Doctors, on topics
related to clinical trial of drugs. To promote knowledge on clinical trials’ mechanisms, to explain how subjects
involved are protected by specific rules, to define potential risks and benefits deriving from the use of unregistered drugs were among the goals of this campaign. A special informative poster had been distributed to a huge
number of family doctors; citizens had been asked to fill in a questionnaire, regardless they had read the poster
or not, and their answers analyzed. The number of filled-in questionnaires was high (around 25,000) and results
show a fair distribution among population. Information campaign showed to be effective: people who read the
poster gave answers up to 15 times more correct, especially in the case of technical questions. Instead, to
questions regarding the possible involvement in clinical trials, all answered more or less in the same way. We
have also performed the same process in different therapeutic area within public hospital and the results will
be presented. The encouraging results of this first information campaign show the direction for future years programs: on one hand, conceiving an always more detailed mechanism to inform citizens and, on the other hand,
expanding such program to health structures in which clinical trials are carried out, focusing on special populations (i.e. paediatric patients, elderly, pregnant women).
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A57
Recruiting Patients for an Interdisciplinary, Multi-Center International
Randomized Clinical Trial: Barriers and Strategies, Bypass Angiographic
Revascularization Investigation 2 Diabetes Trial (bari 2d)
Lisa D. Mighton1, Joan M. MacGregor2, Veronica Sansing2, Elaine Massaro3,
Glory Koerbel2, Gail Woodhead4, Scott M. O’Neal2, Stephen B. Thomas5,
Ruth Churley-Strom6, Christine Kwong7, Leonard Schwartz1
1University
Health Network/Toronto General Hospital, Toronto, Ontario, Canada; 2University of
Pittsburgh, Pittsburgh, PA, USA; 3Northwest University School of Medicine, Chicago, IL, USA; 4Lahey
Clinic Medical Center, Burlington, MA, USA; 5University of Maryland, College Park, MD, USA; 6Saint
Joseph Mercy Health System, Ypsilanti, MI, USA; 7University of Minnesota, Minneapolis, MN, USA
Abstract Objective: Achieving required enrollment and diversity in a multi-center international randomized clinical
trial is an arduous mission. We will outline the strategies leading to BARI 2D’s success in reaching the final participant target number and doubling the minority participant enrollment recommended in the National Institutes
of Health (NIH) guidelines.
Methods: Recruitment data were collected from pre-trial, Vanguard and recruitment phase assessments, site
visit reports, screening logs and cost analyses before and during the four-year enrollment period to evaluate
enrollment rates. Data were analyzed periodically throughout the enrollment phase, identifying barriers and strategies to reach recruitment targets.
Results: Pre-trial recruitment assessments of the pool of eligible participants from selected sites did not provide an accurate portrayal of the total number of sites required to reach recruitment goals. Recruitment during
Vanguard was half what was expected due to delayed site regulatory approvals and ineffective recruitment procedures. The recruitment period was extended, sites were added including several carefully selected foreign institutions, and a composite end point utilized to adjust total recruitment necessary to power conclusions. Eighty-two
percent of sites faced recruitment source barriers, notably reluctance from physicians to refer and difficulty
identifying patients before clinical treatment decisions were made. Sixty-nine percent reported inadequate staffing and staff turnover as detriments to recruitment. Extra funding, although useful, did not necessarily equate
to higher recruitment numbers. Recruitment and Minority Recruitment working groups were effective in fostering
strategies to overcome barriers. Best practices were identified through site visits and a centralized recruitment
coordinator disseminated this information to struggling sites.
Conclusion: Time and resources must be invested early to complete a realistic pre-assessment of potential
sites’ capabilities and initiate an adequate Vanguard phase to pre-test recruitment strategies ensuring success.
Proficient study teams with dedicated internal and external support are crucial to meeting recruitment goals in
large multi-center trials.
A58
How Effective Are Patient Information Leaflets?
A Framework and Methods for Evaluation
Seonaidh Cotton, Julie Brittenden, Jill Francis
University of Aberdeen, Aberdeen, United Kingdom
Patient information leaflets (PILs) are a core component of the informed consent process in clinical trials. Most
evaluation of PILs, if conducted at all, is based on indices of readability, yet several writers argue that readability
is not enough. We propose a framework for evaluating PILs that reflects the central role of the patient perspective in communication, based on simple principles from linguistic theory. The framework has three elements: a)
Readability (attribute of text) which may be assessed using well- established procedures that assess superficial
features of the text; b) Comprehensibility (attribute of reader-and- text) which may be assessed using multiple
choice questions based on the lexical and semantic features of the text; and c) Communicative effectiveness
(attribute of reader relative to writer’s intent) which focuses on discrepancies between responses of the reader
and intentions of the writer. We will discuss the implementation of this framework using the case study of the
CLASS trial: Comparison of LAser, Surgery and foam Sclerotherapy, a UK multi-centre randomised controlled trial
comparing three treatments for varicose veins. Using the proposed framework, the overall reading grade of the
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CLASS PIL was observed to be borderline for reading ease acceptability. Readability differed across the descriptions of the three trial interventions with information about laser therapy being most readable while surgery text
was least readable. Similarly, communicative effectiveness differed across the descriptions. Foam sclerotherapy
was the most communicative, with higher levels of agreement between participants’ and the clinician/author’s
views. The observations from this study could be used to revise the PIL to promote equal understanding across
the descriptions of the interventions, and thus minimise a potentially hidden bias in trial paperwork. This
approach has broad applicability to all clinical trials and has the potential to move the field beyond readability to
broader indicators of quality, facilitating enhanced informed consent.
A59
Development of a Taxonomy to Facilitate Reporting of Behaviour Change
Techniques, the ‘active Ingredients’ of Behaviour Change Interventions
Marie Johnston1, Charles Abraham2, Wendy Hardeman3,
Martin P. Eccles4, Michelle Richardson5, Susan Michie5
1University
of Aberdeen, UK; 2University of Exeter, UK; 3Cambridge University, UK;
University of Newcastle on Tyne, UK; 5University College London, UK
4
Background: There is no shared language in the research community for describing the ‘active ingredients’ of
behaviour change interventions. Hence, the body of evidence from randomized studies to assess the effectiveness of interventions for changing health-related behaviour is limited. Without a precise nomenclature, it
is impossible to replicate effective interventions, discard ineffective interventions, validly synthesize evidence
about behaviour change interventions, or propose causal mechanisms underlying behaviour change. The project
reported here aims to develop a reliable method for specifying behaviour change techniques (BCTs), how they
work and how to identify when they have been delivered.
Methods: In several stages, we generated lists of BCT labels based on a) systematic reviews of behaviour change
interventions; b) systematic text-book search; c) expert brainstorming. We also identified definitions from textbooks and dictionaries. The resulting draft list of BCTs and definitions was refined using consensus methods to
identify redundancy and improve clarity. The nomenclature was used to code published descriptions of complex
behaviour change interventions and inter-coder reliability was assessed.
Results: To date, we have agreed specification for 87 BCTs relevant to changing health behaviours. These can
now be adopted to accurately specify future trials of these interventions, facilitating appropriate reporting as
required by CONSORT.
Conclusion: International consensus is required to facilitate the adoption of this nomenclature into standard
reporting practice. An international advisory board has been convened. Further research will test the value of the
developed system for increasing the reliability of coding of published interventions for evidence synthesis and
increasing the replicability of effective interventions.
A60
Which Components of Interventions Are Reported in Titles and
Abstracts? A Systematic Review to Compare Reporting Practices
for Pharmacologic and Non-Pharmacologic Interventions
Eilidh Duncan, Fiona Stewart, Jill Francis
University of Aberdeen Aberdeen, Scotland, United Kingdom
Background: Key components of healthcare interventions such as ‘active ingredients’ should be reported in titles
and abstracts of published reports of RCTs. Evidence suggests that reporting of non- pharmacologic interventions (NPIs) is inadequate compared to pharmacologic interventions (PIs). There are particular challenges for
specifying the active ingredients of behaviour change interventions. Aim: This review compared the reporting of
components of PIs and NPIs in the titles and abstracts of published reports of RCTs. It was hypothesised that
active ingredients would be reported more often in PIs than NPIs and less often in behaviour change interventions than in other NPIs.
Methods: MEDLINE and EMBASE were searched from 2009 to March 2011 for randomised studies published in
the BMJ, JAMA, NEJM, Lancet, and Annals of Behavioral Medicine. All types of interventions, participants, and
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outcomes were included. Data were extracted from titles and abstracts of 198 randomly selected reports. The
papers were coded for the presence or absence of key intervention components. The resulting frequency data
were subjected to chi-square analysis.
Results: The search strategy returned 1,454 papers. Of 198 papers randomly selected, 98 reported PIs, 96
reported NPIs, and four reported both PIs and NPIs. There were significant associations between intervention
type and reporting of active ingredients: 88.2/94.6% of PI papers and 39.6/67.7% of NPI papers reported active
ingredients in the title/abstract. Furthermore, 29.3/61.0% of behaviour change papers and 52.0/78.0% of other
NPI papers reported active ingredients in the title/abstract. Reporting practice differed for other components
such as trial setting, intervention provider and comparator interventions.
Conclusions: This review provides further evidence of the need for improved reporting of NPIs. Researchers need
a shared language for describing active ingredients of behaviour change interventions. This would ensure that
interventions could be faithfully replicated and evidence validly synthesized.
A61
Failure to Report Protocol Violations in Clinical
Trials: a Threat to Internal Validity?
Elizabeth A. Sweetman, Gordon S. Doig
Northern Clinical School Intensive Care Research Unit, University of Sydney, Australia and
Royal North Shore Hospital, Intensive Care Unit, Sydney, NSW, Australia 2065
Background: Excessive protocol violations (PVs), defined as preventable mistakes in study conduct, may result
in patient harm and may dilute statistical power.
Purpose: To gain a better understanding of reported PV rates, to describe interventions used to reduce PVs and
to investigate relationships between trial characteristics and PVs.
Methods: We reviewed consecutive trials published in four major journals identified using a PubMed search.
Two authors independently abstracted information on trial characteristics, PV reporting, PV rates and interventions used to reduce PVs. PVs were categorized into one of five distinct types: enrolment, randomization, study
intervention, patient compliance and data collection. Associations between PVs and trial characteristics were
investigated.
Results: Eighty clinical trials (20 from each journal) were identified from 101 consecutive abstracts. Median
number of participants was 701 (range: 20-162,367) and median number of participating sites was 15 (range:
1-701). Nineteen percent (15/80) of included trials were single centred. Median study duration was 24 months
(range: 5.81-127 months) and 74% (59/80) of trials were primarily academic funded.
Thirty two percent (26/80) of trials failed to provide explicit reporting of any type of PV and none (0/80) of provided explicit reporting of all five types of PVs. Larger trials (more patients, more sites, longer duration, more complex management structure) were more likely to have more complete reporting of PV’s. Only 9% (7/80) of trials
reported the use of a specific study method to prevent PVs. Use of a run-in phase was the only method reported.
Conclusions: PVs are under-reported. Although the CONSORT statement provides guidance on the reporting of
PVs, reporting requirements are not explicit for all types of PVs. As a first step towards improved reporting by
authors, we recommend the CONSORT statement highlight the importance of PVs by making reporting requirements more explicit.
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A62
The Comet (core Outcome Measures in Effectiveness Trials) Initiative
Paula Williamson1, Doug Altman2, Jane Blazeby3, Mike Clarke4, Elizabeth Gargon1
1University
of Liverpool, UK; 2University of Oxford, UK; 3University of Bristol, UK; 4Queen’s University Belfast, UK
There is growing recognition that insufficient attention is paid to the outcomes measured and reported in clinical
trials. Selection of outcomes is crucial to trials designed to compare the effects of different interventions. For
the findings to influence policy and practice, the chosen outcomes need to be relevant to patients and the public,
healthcare professionals and others making decisions about health care.
Trials in a specific condition often report different outcomes, or address the same outcome in different ways.
Inconsistency in reported outcomes causes well known problems for those who attempt to synthesise evidence,
and many meta-analyses have to exclude key studies because relevant outcomes are not reported. Furthermore,
the measured outcomes may not always be important to patients or health service users.
Much could be gained if an agreed core outcome set (COS) of a minimum number of appropriate and important
outcomes was measured and reported in all clinical trials in a specific condition. Key stakeholders, including
patients, should be involved in establishing COS, to ensure consideration of appropriate outcomes. COS may
encompass all stages or severities of a condition or may focus on a particular disease category. Likewise, a
COS may be for use in trials of all treatment types or only trials of a particular intervention. The scope of a COS
should be defined to identify the relevant health condition, population and types of interventions.
The COMET Initiative (http://www.comet-initiative.org/) aims to foster and facilitate methodological research in
the area of standardising outcomes, to develop much needed standards for methods of COS development and
to develop and maintain a publically available internet-based resource to collate the knowledge base for COS
development. Work on COS has been identified in over 80 clinical areas. The database will be demonstrated,
progress to date presented, and the impact of COS discussed.
A63
The Use of Bayesian Predictive Distribution in Clinical Trials
Bo Yang and Ram Suresh
Merck Research Laboratories, Kenilworth, NJ, USA
It is not uncommon in allergy field that a drug can be approved if two out of three pivotal clinical trials are successful. To limit the cost, many sponsors start with two pivotal trials. In situations where one of the two trials
is successful and the other one only demonstrates numerical improvement, the decision has to be made as
whether a third study should be conducted for the pursuit of approval. In this presentation, we apply the Bayesian
approach to assist the decision making. Specifically, a Bayesian hierarchical model was utilized to evaluate the
probability of success of the third trial. The posterior probability and predictive probability are derived for assessing the chances for a successful third study. A real example is used to illustrate such approach.
A64
Formal Methods for Determining Sample Size - Survey of Sct Membership
Jonathan A. Cook1, Jennifer M. Hislop1, Doug G. Altman2, Andrew H. Briggs3, Peter M. Fayers4,
John D. Norrie1, Craig R. Ramsay1, Ian M. Harvey5, Luke D. Vale6, for the DELTA group
1
Health Services Research Unit, University of Aberdeen, Aberdeen, UK; 2Centre for Statistics in Medicine,
University of Oxford, Oxford, UK; 3Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK;
4Population Health, University of Aberdeen, Aberdeen, UK; 5Faculty of Medicine and Health Sciences, University
of East Anglia, Norwich, UK; 6Institute of Health and Society, University of Newcastle, Newcastle, UK
Background: Central to the validity of a randomised controlled trial (RCT) is a calculation of the number of participants needed (the sample size). This provides reassurance that the trial will identify a difference of a particular
magnitude if such a difference exists. Given its importance, determination of this target difference, as opposed
to statistical approaches to calculating the sample size, has been greatly neglected. A variety of approaches
have been proposed for formally determining what an important difference is (such as the “minimum clinically
important difference” approach). However, in practice the target difference may be driven by convenience or
some other informal basis. The awareness and use of formal methods in the trial community is unclear.
79
Aim: To assess awareness and use of formal methods for determining the target difference and thereby the RCT
sample size.
Methods: Members of the Society for Clinical Trials were sent an email invitation to complete an online survey
through the society’s email distribution list. The survey collected information about the individual responding
(e.g. position, affiliation and location). Seven formal methods were identified that could potentially be used.
Respondents were asked about their awareness and use of, and willingness to recommend, methods.
Results: 180 responses were received representing 13 countries and a variety of professions and institutions.
Awareness of methods varied from 69 (38%) for health economic methods to 162 (90%) for using pilot data. A
majority (96, 53%) had used no more than three of the available methods. Recommendation of methods tended
to be lower than use except for health economic and reviewing the evidence base methods.
Conclusions: Awareness, use and willingness to recommend varied greatly between methods. Trial specific guidance documentation may increase both awareness and use of formal methods.
A65
Adaptive Designs for Clinical Comparative Effectiveness Research: Are We Ready?
John A. Kairalla1, Christopher S. Coffey2, Keith E. Muller1, Mitchell A. Thomann2,
Ronald I. Shorr1, James C. Torner2, and Elizabeth A. Chrischilles2
1University
of Florida, Gainesville, FL, USA; 2University of Iowa, Iowa City, IA, USA
There is clearly increasing national interest in comparative effectiveness research (CER). Randomized controlled
trials must have a prominent place in CER due to their reliable information and well respected standard; however,
improved approaches and CER-focused rethinking are needed to ensure their feasibility and overcome tendencies
to be slow, expensive, and homogeneous. As in other clinical research, randomized CE trials there may have
limited information to guide initial design choices including the patient population, the primary outcome, or the
target effect size. In the general RCT setting, adaptive designs have been proposed to address these concerns.
There are potential advantages to expanding adaptive designs to within the CE context. However, although there
are many similarities between the two, CE trials have some fundamental differences from standard clinical trials. For one, the heterogeneity in the population studied in CE creates higher variability in outcomes. CE studies
could be underpowered if they use planning values obtained from tightly controlled clinical trials. Additionally,
the concept of a ‘minimum clinically meaningful difference’ is hard to define in the CE context. Even assuming
equal cost and safety, a range of meaningful effect sizes could be defined with upper limit the largest effect
with reasonable chance of being observed and lower limit the minimal effect deemed sizable enough to change
practice in the study context. Following a brief introduction to clinical CER, this talk will focus on additional decisions and methodology needed before the promise of adaptive designs can be achieved in the CE setting. We
will describe the evaluative process to determine the usefulness of these designs in CER, assess whether or not
we are ready as a scientific community to move on from basic designs to more advanced methods, and discuss
items that must be addressed in order to achieve this objective.
A66
Perception and Use of Adaptive Designs in the Industry and Academia:
Persistent Barriers and Recommendations to Overcome Challenges
Caroline Morgan1, Brenda Gaydos, Christopher Coffey, Yili Pritchett,
Ben Hartley, Li Chen, Judith Quinlan, Alun Bedding, Jeff Maca, Teresa Perney,
Kyle Wathen, Daniel Meyer, Martin Jenkins, Susan Huyck, William Wang
1Cytel,
Inc.
The DIA adaptive design scientific working group have conducted a survey of the perception and use of adaptive
designs (ADs) for clinical development programs in the industry and academia. In this presentation, the results
of the survey will be presented and compared to the results of a previous survey carried out by the same group
in 2008 under the auspices of PhRMA1.
The key objectives of the survey were to identify any persistent barriers to implementing such designs and provide
recommendations to overcome these challenges. The questionnaire was sent out to a wide selection of organizations in September 2011 to enquire about ADs that were planned, ongoing or completed in their organization
80
from 1st January 2008 to 1st September 2011.
In parallel, the medical and statistical literature and clinical trial registries were reviewed by the group to identify
published AD case studies and consider to what extent the literature is representative of the information gathered in the questionnaire. The results of this review will also be presented.
1
Quinlan J. et al. Barriers and opportunities for implementation of adaptive designs in pharmaceutical product
development. Clin Trials 2010; 7:167-173
A67
Challenges of Collecting Health Data and Maintaining
Contact With an Aging Study Population
Jo Ann Hartline1, Karen Anderson1, Dona Marrah1, Eric Klein2
1Seattle,
WA, USA; 2Cleveland, OH, USA
Conducting follow-up studies in older adults presents particular challenges, especially if the research is done
remotely. The SELenium and vitamin E prostate Cancer prevention Trial (SELECT) opened in 2001 and recruited
35,533 participants age 50 and older at over 400 study sites. In 2009, after study supplementation ended,
17,748 participants consented to continue follow-up by mail conducted centrally by the Coordinating Center.
Older adults may retire, travel extensively or buy second homes. Frail adults may need more supportive environments such as assisted living centers. Many face co-morbid conditions that may affect their ability to read,
understand or complete the study questionnaires. Although older adults may be reluctant to use newer data collection technology that is widely accepted in younger populations, some expect access to the study through cell
phones, email and the web. Others may have limited options for contact, such as mail or land lines. Tracking
and maintaining participant contact information requires extensive staff time.
In early 2011, we administered a mailed survey to our participants. Despite strong interest in a web data submission option, to date only 550 participants (3% of total) have accessed our website, and only 410 forms have
been submitted online. We are now pursuing various strategies to understand barriers to website use and to
encourage participants to submit data online.
Supported by NIH/NCI/DCP grant CA37429 and in part by the National Center for Complementary and Alternative
Medicine (NCCAM).
A68
Extended Follow-Up in Multi-Phase Clinical Trials
Katherine Trigiani, Johanna Sanchez, Elizabeth Asztalos
The Centre for Mother, Infant, and Child Research (CMICR), Sunnybrook
Research Institute, Toronto, Ontario, Canada
Determining the value of an intervention in a specific population, particularly in neonatal or pediatric care, often
requires extended follow- up to monitor patients for effects that may only present themselves years later. The
knowledge to be gained through extended follow-up in clinical research can be impeded by several practical difficulties associated with connecting with the original patient population. These challenges include locating past
participants, and repatriating them back to clinic. This presentation will outline strategies in extended follow-up
to mitigate these issues and maximize the potential for complete data collection.
The first step involves contacting the local Research Ethics Board or Institutional Review Board to inquire about
acceptable methods for locating patients who may have moved or lost touch with their follow-up team. Once study
approval has been granted it can be helpful to get in touch with the coordinator or staff who managed the trial
at earlier phases. These individuals may be able to share established practices and identify participants with
special circumstances; patients may also prefer this continuity of contact with the research team. Additionally,
patients several years out of the clinical setting may be reluctant to return; connecting these potential participants with familiar staff may be helpful when updating them on the aims of the current trial.
Subsequent strategies for repatriating patients to the clinic for assessment can include sending a letter outlining the next phase of the trial; following up with a phone call to address questions or concerns; and mailing out
a recruitment package to potential participants. This package can include consent or assent forms and a pre81
addressed, pre- stamped envelope to make the process of returning signed documents easier for the participant.
Finally, a follow-up call prior to the appointment to discuss logistical details and possibly offer transportation
assistance can decrease the likelihood of attrition.
A69
Issues to Consider in the Set-Up of Complex Intervention
Trials in Vulnerable Populations
Shamaila Anwar, Maria Bryant, Kayleigh Burton, Amanda Farrin, Liz Graham, Jonathan Wright
Clinical Trials Research Unit, University of Leeds, Leeds, United Kingdom
Complex intervention trials within vulnerable populations are challenging to undertake. They are often difficult to
design, implement and evaluate, and suffer from poor recruitment. Feasibility studies are key to testing the viability of trial designs, recruitment potential and other implementation aspects of larger scale trials. We illustrate
practical and logistical challenges encountered in the design and set-up of two feasibility trials: OBI (Optimised
Behavioural Intervention – in chronic low back pain patients) and WATCH-IT (a community-based obesity treatment intervention for children and adolescents). OBI is currently in recruitment, whereas the evaluation of the
feasibility of WATCH-IT is now complete . Both studies were set up to determine: recruitment rates, acceptability of randomisation, data collection, drop-out rate, optimal outcome measures, and aid robust sample size
calculation. In addition, OBI also aims to optimise the intervention and to measure its acceptability. Both trials
recruited to target and the methods of randomisation and data collection were acceptable to participants. We
found that for WATCH-IT self referral (via media promotion) resulted in a higher consent rate than professional
referral, but that this did not necessarily translate to greater participant retention. Also, calculation for ultimate
sample size was significantly greater than that reported in published trials. Importantly, WATCH-IT highlighted
how the trial impacted on service delivery which was an important lesson for the design of the phase III trial. For
OBI we found that two recruitment pathways were needed dependent on whether the physiotherapy service was
involved in assessment and diagnosis as well as treatment. In addition we found that training of therapists took
longer than anticipated and there was a paucity of therapists in general who could provide clinical cover for the
OBI therapists. Feasibility studies of complex interventions are often overlooked. However, they are essential to
assess the viability of larger definitive trials.
A70
Designing Clinical Trials for Testing DiseaseModifying Agents on Alzheimer’s Disease
Chengjie Xiong
Department of Biostatistics Washington University St. Louis, MO, USA
There are two types of therapeutic trials in the search of agents that can treat people with Alzheimer’s disease
(AD): symptomatic and disease-modifying trials. The former includes these for symptomatic agents with a primary
objective of improving cognition, function, and global measures or deferring decline over a short period of time.
The latter consists of those for disease-modifying agents which strive to show that the course of AD has been
altered and the rate of disease progression has been slowed. Randomized start and randomized withdrawal
designs are two popular designs of disease-modifying trials on AD. Crucial design parameters such as sample
size allocations and treatment switch time are important to understand in designing such clinical trials. A general
linear mixed effects model is proposed to formulate the appropriate hypothesis for the test of disease- modifying
efficacy of novel therapeutic agents on AD. This model employs a piecewise linear growth pattern for those in the
delayed treatment or early withdrawal arm, and incorporates a potential correlation on the rates of change on
efficacy outcome before and after the treatment switch. Optimum sample size allocations and treatment switch
time of such trials are determined according to the model. An intersection-union test through an optimally chosen
test statistic is used for the test of treatment efficacy. Finally, summary statistics from several reported symptomatic trials on AD in the literature are used to apply the proposed methodology for designing future optimum
disease-modifying trials on AD.
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A71
Soundness of Evidence Derived From Metanalysis of High
Quality Observational Studies. a Case in Cardiology.
Catherine Klersy, Marco Ferlini, Arturo Raisaro, Valeria Scotti,
Anna Balduini, Ezio Bramucci, Annalisa De Silvestri
IRCCS Fondazione Policlinico San Matteo, Pavia, Italy
Background. Often, despite evidence from large and/or high quality randomized clinical trials (RCT) is not available, there are numerous large, high quality cohort studies presenting adjusted risk ratio (RR). For instance, we
considered studies evaluating efficacy of intravascular ultrasound (IVUS) guidance in drug eluting stent positioning in percutaneous coronary intervention and compared evidence derived from RCT and observational studies.
Methods. We performed a literature search on Pubmed, Embase, Cinhal, Web of Science and the Cochrane
Library. Inclusion/exclusion criteria were: full-text articles in peer-reviewed journals (2003-2011), we excluded
uncontrolled studies. The search included both RCT and observational cohort studies. The following outcome was
metanalyzed: major adverse cardiac events (MACE: death, acute myocardial infarction and/or revascularization).
Pooled fixed or random effect RR and 95% confidence intervals (95%CI) were computed.
Results. Overall 217 abstract were evaluated and 26 full texts were retrieved; 17 of them were excluded,
(abstract, review, metanalysis, MACE missing, no pertinence). Of the 9 articles included in our study 1 was a
RCT and 8 were observational studies (5 with adjusted estimates). A total of 17541 patients were enrolled,
women were 28%. The median age was 64 years. Median follow-up duration was 18 months (25th-75th percentiles 12-24). The RR for the RCT was 0.92 (0.39-2.19, N=210 pts); for the ‘adjusted’ cohort studies it was 0.79
(0.69-0.91, N=15405 pts) and for the ‘unadjusted cohort” it was 0.89 (0.70-1.13, N=2286 pts).
Discussion. The small RCT does not provide sound evidence, as shown by wide 95%CIs, while the large well conducted cohort studies with adjusted estimates indicate a protective effect of IVUS towards MACE, with high level
of confidence. Being the IVUS patients more critical, its effect would be diluted in unadjusted studies. Although
large RCTs are needed to confirm IVUS role, good quality cohort studies might better reflect real life.
A72
Using Meta-Synthesis of Three Randomized Controlled Trials in
Colorectal Cancer (CRC) Screening to Inform Assumptions on
Natural History of Crc in Microsimulation Modeling
Ann Zauber, Iris Lansdorp-Vogelaar, Frank van Hees, Marjolein van Ballegooijen
Memorial Sloan-Kettering Cancer Center, New York, NY, USA; Department
of Public Health, ErasmusMC, Rotterdam, the Netherlands
Background: Estimates of the fecal occult blood test (FOBT) (Hemoccult II) sensitivity differ widely between
screening trials, and will lead to divergent conclusions on the effects of FOBT screening. We used microsimulation modeling to estimate a preclinical colorectal cancer (CRC) duration and sensitivity for unrehydrated FOBT
from the data of 3 randomized controlled trials of Minnesota, Nottingham and Funen. In addition to two usual
hypotheses on the sensitivity of FOBT, we tested a novel hypothesis where sensitivity is linked to the stage of
clinical diagnosis in the situation without screening.
Methods: We used the MISCAN-Colon microsimulation model to estimate sensitivity and duration, accounting for
differences between the trials in demography, background incidence and trial design. We tested three hypotheses for FOBT sensitivity: sensitivity is the same for all preclinical CRC stages, sensitivity increases with each
stage, and sensitivity is higher for the stage in which the cancer would have been diagnosed in the absence of
screening than for earlier stages. Goodness of fit was evaluated by comparing expected and observed rates of
screen- detected and interval CRC.
Results: The hypothesis with a higher sensitivity in the stage of clinical diagnosis gave the best fit. Under this
hypothesis, sensitivity of FOBT was 51% in the stage of clinical diagnosis and 19% in earlier stages. The average
duration of preclinical CRC was estimated at 6.7 years.
Conclusion: Our analysis corroborates a long duration of preclinical CRC, with FOBT most sensitive in the stage
of clinical diagnosis.
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A73
Combining Randomized and Observational Data Using Network Meta-Analysis
to Explore Drug Safety: The Case of Antifibrinolytics in Cardiac Surgery
Brian Hutton1, Lawrence Joseph2, Dean Fergusson3, David Mazer4, Stan Shapiro5, Alan Tinmouth6
1McGill
University, Montreal, Canada, Ottawa Hospital Research Institute, Ottawa, Canada; 2McGill University,
Montreal, Canada; 3Ottawa Hospital Research Institute, Ottawa, Canada; 4Saint Mike’s Hospital, Toronto,
Canada; 5McGill University, Montreal, Canada; 6Ottawa Hospital Research Institute, Ottawa, Canada
Background: Aprotinin was used to minimize blood loss in cardiac surgery patients before withdrawal from the
market in 2008 for safety reasons. The drug has again become available.
Methods: We performed a systematic review and network meta-analyses to estimate the relative risks of death,
myocardial infarction (MI), stroke and renal failure/dysfunction between aprotinin, tranexamic acid (TXA), epsilonaminocaproic acid (EACA), and no therapy. A 2011 Cochrane review was used to identify relevant randomized
controlled trials (RCTs), and a search of Medline, Embase and the Cochrane Register of Trials was conducted to
identify propensity matched/adjusted observational studies. Odds ratios and 95% credible intervals for comparisons between therapies were estimated, as were the average rank and probability that each therapy was most
safe. The probabilities of odds ratios excluding a null difference were also estimated. Network meta-analyses
based on RCTs were fit first, and then observational evidence was incorporated.
Results: 83 RCTs and 11 obervational studies (>41,000 patients) were included (Figure 1). Based on RCTs, TXA
was associated with a reduced risk of death versus aprotinin, while pairwise comparisons were inconclusive for
MI, stroke, and renal failure/dysfunction; point estimates and coverage probabilities of these intervals suggested
aprotinin was often associated with an elevated probability of increased risk (Table 1). When observational data
were incorporated, pairwise comparisons showed increased risks of death with aprotinin relative to TXA and
EACA, as well an increased risk of renal failure/dysfunction relative to all comparators. There were also probabilities suggestive of increased risks of MI with aprotinin compared to TXA and EACA (Table 1).
Conclusions: Data suggests there remains reason for concern regarding aprotinin safety. While meta-analyses
of RCTs can lack sufficient sample size to definitively identify harms imbalances, appropriate incorporation of
observational evidence and use of network meta-analysis can help reduce uncertainty in analyses of such data.
A74
The Publication of Preclinical Evidence Supporting
Translation of New Drugs: an Empirical Analysis
Carole A. Federico, Jonathan Kimmelman, Dean A. Fergusson, Margaret Sampson
Department of Biomedical Ethics, Faculty of Medicine, McGill University, Montreal, Canada
The success of translational research requires sound judgment in the planning and implementation of trials. Such
planning involves synthesis of previous literature. We sought to determine the accessibility of preclinical efficacy
studies in a cohort of novel investigational agents entering clinical development between 2000 and 2003. A
cohort of initial human trials of new agents reported as full journal publications was identified through systematic searches of MEDLINE and EMBASE. The cohort included 100 investigational agents, spanning 10 different
indications. Identified agents were linked to preclinical studies by a search of references, EMBASE and PubMed.
Preclinical evidence was considered published if at least one full journal article reported disease response in
live, non-human animals. Of the 100 agents, 89 had published preclinical work, 80 of which tested the identical
intervention and another 9 of which were based on closely related agents. Thirteen percent of agents published
preclinical studies only after the initial human trial publication. Fifty-five percent of initial human trial articles
referenced published animal work. Of the 89 agents, 57% had five or more animal studies available, 33% had
between 2-4, and 10% had one preclinical study available. Of the 13 investigational agents that received eventual FDA approval, 12 had five or more preclinical studies available in the published record. The probability that
preclinical evidence was publicly reported in more than five reports was significantly greater for FDA approved
drugs than for drugs that did not receive licensure (85% vs. 38%; Yates’ chi-squared test, p=0.002). This work
demonstrates that a large proportion of investigational agents had at least some preclinical studies available.
This suggests that preclinical knowledge synthesis for many new drugs is feasible—especially for those receiving licensure. However, we are unable to estimate what proportion of preclinical efficacy studies go unpublished.
84
A75
Can Exercise Enhance Smoking Cessation Outcomes? A Pragmatic
Randomized Controlled Trial (fit2quit Study)
Yannan Jiang1, Ralph Maddison1, Hayden McRobbie2, Chris Bullen1,
Vaughan Roberts1, Marewa Glover3, Midi Tsai1, Joy Jiang1, Harry Prapavessis4
1Clinical
Trials Research Unit, University of Auckland, Auckland, New Zealand; 2Barts
& The London School of Medicine and Dentistry, University of London, London, United
Kingdom; 3Centre for Tobacco Control Research, University of Auckland, Auckland, New
Zealand; 4School of Kinesiology, University of Western Ontario, Ontario, Canada
Smoking is directly responsible for 4500 deaths each year in New Zealand (NZ) including 22% of all Maori deaths.
Despite the proven efficacy of various cessation approaches, long-term cessation rates are still below 25%.
Quitline is a national smoking cessation service that offers telephone delivered behavioral support (3 sessions)
and an eight-week supply of nicotine replacement therapy (NRT) at a subsidized rate for smokers in NZ. The
Fit2Quit trial aims to determine the effects of a home and community-based exercise intervention on increasing
smoking cessation rates at six months when added to usual care.
A two-arm parallel randomized controlled clinical trial was conducted in 2010-11. Eligible participants were
recruited through Quitline who were interested in quitting, had their first cigarette within 30 minutes of waking,
aged 18 years and over, and wanted to be physically active. The intervention group received telephone-based
exercise counseling programme delivered by existing Green Prescription (GRx) services over six months, in addition to usual smoking cessation support. The control group received usual care alone. Self-reported smoking
abstinence, mood and physical symptoms (MPSS), and physical activity level (IPAQ) were assessed at 8 and 24
weeks. The primary endpoint was self-reported point-prevalence at 24 weeks, confirmed by salivary cotinine reading. Treatment evaluations were performed on the principle of intention-to-treat assuming missing as smoking.
Sensitivity analyses were also conducted.
A total of 906 smokers were randomized (intervention N=455; control N=451). Participants were aged 37 years
(18-78yrs), 31% Maori, 46% males, 83% smoked >10 cigarettes per day, 79% made previous quit attempts, and
55% didn’t use NRT at baseline. Relative risk and adjusted odds ratio were calculated to assess the smoking
abstinence. Repeated measures models were used to evaluate change in MPSS and IPAQ total score between
groups. Statistical analyses and full trial results will be presented and discussed.
A76
Group-Based Trajectory Models in a Clinical Study in Nutrition
Yassin Mazroui1, Jérôme Tanguy2, Sébastien Marque2
1Université
2Danone
Bordeaux Segalen, Bordeaux Cedex, France;
Research, Centre Daniel Carasso, Palaiseau Cedex, France
Trajectory-based models are increasingly applied in clinical research to understand the etiology and developmental course of different types of disorder [1, 2, 3]. More recently, the range of applications has been extended to
capture heterogeneity in treatment responses to clinical and randomized trials [4, 5].
A double-blind, randomized controlled clinical trial in nutrition was carried out on 197 subjects to investigate
whether the consumption of an active dairy product can improve different clinical parameters, such as well-being
scores. For exploratory purpose Group-based trajectory models (GBTM) [6] were used to map the developmental
course of these distinct but related outcomes individually, and then according to a joint approach. The statistical analysis was performed with the Proc Traj [7] with SAS® software release 9.2 (SAS Institute, Inc, Cary, NC).
GBTM provided empirical ways of identifying clusters of individuals in response of the product intake, following
both typical and atypical courses of development. Overall, results suggested that the active product was associated with trajectories relating clinical improvements. In this application, GBTM also allowed to highlight different
responders’ patterns in the active product group by identifying developmentally meaningful subgroups in the
population for whom product effects vary.
In this communication, authors will discuss the results of applying such methods to a clinical trial in nutrition.
Strengths and limits associated to this approach as well as the interpretation will be further detailed.
85
A77
The Life Study Outcomes Management Tool
Lea N. Harvin1, Cynthia L. Stowe1, Ching-Ju Lu2, Thomas Gill3, Michael E. Miller1
1Wake
Forest University School of Medicine Department of Biostatistical Sciences
Division of Public Health Sciences Winston-Salem, NC, USA; 2University of Florida
Gainesville, FL, USA; 3Yale School of Medicine New Haven, CT, USA
The Lifestyle Interventions and Independence for Elders (LIFE) Study is a Phase 3, multi-center randomized controlled trial (RCT) designed to compare a moderate-intensity physical activity program to a successful aging health
education program in 1,600 sedentary older persons, age 70-89 years, across eight field centers. The primary
outcome is major mobility disability, defined as the inability to walk 400 meters. Secondary and tertiary outcomes
include serious fall injuries, pulmonary events, and cardiovascular events. Given the number of participants and
their age range, we expect to collect data on many outcomes throughout the length of the trial. The need for a
central tracking and monitoring system initiated the construction of the Outcomes Management Tool (OMT).
The OMT allows the Data Management and Quality Control (DMAQC) Center to centrally track status of outcomes,
compile cases for assignment to adjudication committee members, and track the adjudications via an online
interface system. The web system registers each outcome reported, eliminates duplicate events identified, and
enables field centers and the DMAQC to track outcomes as they move through the outcomes process. Making
this process accessible on the web is efficient for real-time reporting, gives administrators the ability to manage documents, assign adjudicators, monitor active adjudication status, communicate with adjudicators when
needed, and provides a central repository for outcome details.
Generating outcome events from participant reports begins with the data entry of a case report form (CRF). Upon
submission of the CRF, if specific criteria are met, this triggers the creation of a unique outcome ID for each event
reported by the participant and initiates the tracking of outcomes. This utilizes IBM’s WebSphere ILOG-JRules
business management system for rules validation and event provocation.
This presentation will outline the flow of outcomes in the Outcomes Management Tool from the entry of the CRF
to the final adjudication.
A78
Improving Data Quality Using Quality Improvement
Michael Kappelman1, Melissa Disorda2, Jesse Pratt3, Eileen King3
1University
of North Carolina, Chapel Hill, NC, USA; 2University of Vermont, Burlington,
VT, USA; 3Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
Patient registries may support a variety of functions, ranging from clinical care to quality measurement and
reporting, to clinical and translational research. Compared to clinical trials, quality reporting registries typically
involve more data collection (all patients and all visits within a set of practices), often with fewer resources (funding, personnel). Data coordinating centers for registries must be aware of these differences, assist practices in
embedding data collection into clinical care, and provide time-efficient resources for monitoring and improving
data quality.
To support ImproveCareNow, a quality reporting registry for pediatric IBD, we worked with an established multicenter network to standardize data definitions and review their processes of data collection and capture.
Additionally, we developed a set of data quality metrics to define areas where data quality is critical to desired
outcomes or known areas of deficiencies for the registry. Among the measures of interest are:
• proportion of patients enrolled in the registry -proportion of visits captured in the registry • proportion of visits with all critical data elements captured -proportion of visits entered in the registry
within 30 days of visit date
• proportion of visits where data values are suspicious, based on inter or intra-visit inconsistencies
We also developed a pair of data quality reports-- a set of run charts that allow sites to track data quality metrics
over time and a report that allows sites easily identify potential errors to a level of detail that allows for quick
updates to be made to the registry. These reports were designed to have a look and feel similar to tools already
in use by these sites to increase the probability of their integration into normal clinical practice. Analysis of the
effectiveness of these strategies is ongoing. Preliminary results show an increase from 80% to 89% of visits with
all critical variables recorded.
86
A79
Streamlining Data Collection and Flow for Central
Units in Large Multi-Center Clinical Trials
Pam Mangat, Ella Temprosa, Sharon Edelstein, Hanna Sherif
George Washington University Biostatistics Center, Rockville, MD, USA
One major aspect of multi-center clinical trials coordinating centers includes the work, data flow and monitoring
of central units which analyze samples and transmit data to the coordinating center. These include laboratories
for blood samples and reading centers for electrocardiographs, retinal photos, CT scans, DEXA scans, etc. Data
travels from clinical site to collection site (e.g. scan center) to central reading center and finally to the coordinating center. It is critical to ensure the integrity of the data while streamlining the process when data collection
and management can be challenging. The first step in the design process is planning the methods of participant
flow from clinical site to collection site, including obtaining informed consent, verifying eligibility and participant
scheduling. The second step is developing the method of data flow from collection site to reading center using
tools such as web-based portals, transmission software or courier services. The third step is for the reading center to securely transfer the data to the coordinating center. Data transmissions should have preapproved formats
and sets of components for consistency and accuracy such as dates of analysis and receipt, and unique identifiers for the individuals performing the analysis and the specific image or sample. The fourth step is to develop
methods for data validation to ensure the correct attribution of assessment to the corresponding participant. The
coordinating center should have a checklist for the incoming central unit data where the data must check and
pass each step before moving to the next step. Finally, a process for the reporting of alert values to sites in a
timely manner must be developed. Several options for these processes will be described and various methods
in which data is collected and transferred from reading centers to coordinating centers will be compared, and
future suggestions will be discussed.
A80
Design of a Comprehensive Rule-Based, Real-Time Data Validation
Function in a Web-Based Clinical Trial Management System
Keith Pauls, Jaemyung Kim, Wenle Zhao
Medical University of South Carolina, Charleston, SC, USA
With the popularity of electronic data capture (EDC) increasing in clinical trials, there is a growing demand for
stronger and more efficient data validation tools. Traditionally, online single field range checks and batched
offline logic checks performed by statisticians are used to identify data issues related to data transcription errors
and protocol compliance discrepancies. Our home-grown, web-based Clinical Trial Management System (CTMS) is
equipped with a database driven data validation process to perform rule-based data checks at the time of data
entry. This process uses a centralized database table to manage all data validation checks for all Case Report
Forms (CRFs). Initial data checks against invalid data types, missing required data items and impossible data
values are performed prior to saving the record to the database. Records that pass this initial process are saved
to the database and further data validation is performed by using database queries involving one or more related
data items to ensure sound data collection logic is enforced. Depending on the sources of these data items,
such data validation queries can be defined within the current data record, across multiple records within the
same data table, or across multiple records from different data tables. Violations of these data checks will be
saved in a central rule violation table along with the values of the associated data items. Based on the level of
the violation, an alert, warning, or rejection flag will be placed on the data form as an indicator for users to take
the next appropriate action. Our data management experiences for more than ten large, multi-center phase III
clinical trials demonstrated that this comprehensive, real-time data validation function has significantly reduced
data errors occurring during the data entry process and shortened the time required for data cleaning and database lock.
87
A81
Survey of the Current Beliefs and Attitudes of the Canadian Critical
Care Trials Group Regarding Source Data Verification
Dean Fergusson, Kusum Menon
The Ottawa Hospital Research Institute, Clinical Epidemiology Program,
Children’s Hospital of Eastern Ontario, Canada
Background: Source data verification is the process of comparing information on source records to data recorded
in a Case Report Form as part of a research study. Researchers are required to perform source data verification
in order to comply with National Regulations and Good Clinical Practice Guidelines. There is little guidance for
researchers as to the amount and frequency of this process or the effect of source data verification on study
outcomes. Recently there has been debate regarding the value of source data verification on data quality. There
is little research on the beliefs and attitudes of Investigators and Research Coordinators regarding the amount,
frequency, value and effect of source data verification and how it may be optimized. This project is part of a
research program to determine the effect of source data verification on study outcomes and the amount of
source data verification that should be done.
Objectives: The primary objective is to describe the current beliefs and attitudes regarding source data verification of members of the Canadian Critical Care Trials Group.
Methods: We developed a self-administered on-line survey using focus groups of Critical Care Investigators and
Research Coordinators. The survey has been pilot tested and is undergoing clinical sensibility and reliability testing. The final survey will be sent electronically to the 330 members of the Canadian Critical Care Trials Group
between December 2011 and February 2011. Results: We will present descriptive summaries for all items and
then separately for Investigator and Research Coordinator groups. We will evaluate associations between variables.
Significance: The survey results will provide general guidance to adult and pediatric critical care researchers in
determining data quality assurance procedures and will inform the next phase of the research program: assessing methods of source data verification and its effect on study outcomes in Canadian Critical Care research.
A82
Reproducible Research and Clinical Trials
Paul A. Thompson, Ph.D.
MADA Center Sanford Research/USD Sioux Falls, SD, USA
The concept of reproducible research was introduced in the computational sciences some time ago, but has
begun to be considered in biostatistics, bioinformatic, and other areas of medically related data analysis.
Reproducible research, in this context, involves performing data analysis and statistical evaluation of data in a
manner in which the relevant results (tables, figures, incidental text) can be recovered with minimal effort, analyses can be conveyed to data repositories with minimal effort, and analyses can survive the inevitable changes
in personnel at the data management center. This has strong implications for clinical trials, which are usually
conducted in a “reproducible research” concept, but which are not always analyzed in this manner. From the
perspective of data analysis in SAS (a dominant tool in the clinical trials field), structural approaches to project
setup, disciplined and consistent uses of macros, and archival approaches to manuscript construction are the
first steps to reproducible research. These will be discussed and illustrated with several examples.
88
A83
The Use of Ancillary Data Capture Systems in Clinical Trials
Colleen Allen, Paul Van Veldhuisen
The use of technology in clinical trials is increasing where ancillary software is utilized to capture data beyond
that typically collected via case report forms in an electronic data capture (EDC) system. In recent studies by the
Clinical Trials Network of the National Institute on Drug Abuse, software systems have been used to administer
and monitor adherence to trial interventions and perform study assessments. Utilization of ancillary systems
requires appropriate advanced planning to address key issues.
Ancillary systems vary in complexity and sophistication, ranging from simple and home-grown to complex and
well-validated. Upon identifying systems deemed necessary for the trial, a communication plan should be developed outlining expectations for software developer support, as well as the workflow and timeline for identifying
and resolving issues. The software and hardware needed for hosting and using the system must be identified
and procured.
Understanding the structure of the data collected in the system, which is facilitated by obtaining a system
diagram and data dictionary, is key. If the system will be used to capture data for analysis, it is important to
verify that those data are collected and identifiable in the system. The data dictionary can assist in identifying
if protected health information is being collected and if so, to develop appropriate security measures, such as
encryption. It is also important to explore whether the system can communicate with the EDC system, or at a
minimum that the data captured in the system can be linked to those from the EDC system.
Finally, a plan for providing initial and ongoing training in the use of the system must be established. The plan
should outline who is responsible for the training, the method of training (e.g., face-to-face, webcast), and the
development of a user’s guide.
A84
Electronic Patient Reported Data for Risk Screening in
Primary Care Clinics Using Openclinica and Cdisc Odm
Cal Collins
OpenClinica, LLC, Waltham, MA, USA
Despite best practice guidelines, patients presenting for primary care are often not screened for medical issues
other than the presenting problem due to time and personnel constraints. This presentation details an electronic
screening protocol and technology platform that: a) allows patients to complete a brief screening form prior to
their appointment, and b) provides immediate feedback on health risks and conditions for clinicians to use in
the patient visit.
Patients presenting at the primary care clinic self report via a Comprehensive Primary Care Screening (CPCS)
instrument using Android-based tablets. The CPCS assesses risks related to falls, colon cancer, sexual health,
domestic violence, oral health, alcohol, depression, and basic needs. Responses are entered via a touch-screen
interface in English or Spanish, or via audio versions of the instrument. It incorporates dynamic branch logic
to capture detailed information where needed from patients. Upon completion, data is saved into a EDC database where it is scored and analyzed for recommendations, including referrals and standing orders. Results
are immediately accessible for physician use; scores and raw data may also be extracted for incorporation into
de-identified research datasets.
We use a CDISC ODM-based form definition created using the OpenClinica open source EDC platform. The CDISC
ODM protocol and data capture definitions are automatically transformed into to XForm definitions that are rendered via an open source medical data capture “app” on the tablets for patient entry and physician retrieval. The
EDC engine provides data storage, validation, scoring, reporting, and analysis capability.
The project objectives are to: - increase referrals for health risks and conditions, - increase access to and use
of de-identified screening results by researchers, and - promote adoption, dissemination, and adaptation of the
screening tool by using reusable, configurable open source platform.
89
A85
Implementation of Digital Pen Technology to Capture Clinical Trial Data
Devin Hunt, Nicole Close
EmpiriStat, Inc., Mt. Airy, MD, USA
The methods for data capture have advanced as technology has evolved. Often studies utilize an Electronic Data
Capture (EDC) system, but many studies may still only be paper based. The costs and regulatory requirements
of deploying an EDC system may not outweigh the benefits of conducting a paper based study through the use
of fax forms, scanning optical character recognition software, telephone data entry, bubble forms, or digital pen
capture. However, these methods are thought of as “old technology,” but with the proper technical approach, a
paper based study may actually be more efficient and productive.
A model project was conducted in which digital pen data collection technology was examined for benefits and
drawbacks. The digital pen was used by study staff members and/or subjects to complete CRFs, the pen is
docked in a docking station attached to a computer, and data is uploaded to the data coordinating center. After
project evaluation, it was found that the use of digital pen technology to instantly generate electronic copies of
paper CRFs benefited the study by:
1. eliminating the need to ship completed CRFs,
2. eliminating the need to scan paper forms for electronic storage and transmission,
3. dramatically reducing data collection training for staff,
4. using a source document as a CRF, and
5. having the ability to track CRF completion virtually.
While there are multiple ways to implement digital pen technology, each with their own drawbacks, this project
found that data still had to be entered into an electronic database manually, printing CRFs required using print
vendors with previous experience with the software, and a method to transfer and track files and store back-up
copies was needed. These lessons learned will only benefit future studies using digital pen technology corporately, and help reduce Sponsor costs for paper based studies.
A86
Responding to the Growing Need for Alternative Platforms
for Collecting Clinical Research Data
Milena Silverman, Dawn Caron, Marcia Latif, Kristopher Kaufman, Kai-Hsiung Lin,
Yu-Ming Chang, Wes Fang, Rita Krishtul, Roberto Martin, Tz-Yang Tang, Jun Yan
Memorial Sloan-Kettering Cancer Center, New York, NY, USA
The technology of personal computing has undergone great changes the last few years. Naturally, those conducting clinical research would like to take advantage of these advancements.
The Clinical Research Database (CRDB) at Memorial Sloan-Kettering Cancer Center (MSKCC) was created as a
client server application in 1992. In 2003, the first web based platform was made available to facilitate data
entry from remote locations. During the past year, it became necessary to expand our application scope to keep
up with the latest needs of the researchers. There are two main areas of our system expansion: 1) the multicenter internet platform and 2) mobile devices.
Historically at MSKCC, data management for our multicenter protocols was mainly a paper based system. It
became evident that participating sites needed access to CRDB to enter data directly. This brought about security and privacy concerns beyond what was needed for an internal database. The conversion to a new external
platform to deal with these concerns brought its own set of challenges.
In parallel, a mobile option was needed for survey completion by participants in clinic because desktop computers are not always available. However, CRDB was designed for data entry by clinical research professionals, not
participants. We were able to design a tablet survey that addressed this as well as other concerns.
In this presentation, we will review the need for alternative platforms for collecting clinical research data. We will
also address the various challenges we faced while expanding our system from the traditional data entry model,
as well as our suggested solutions.
90
A87
Challenges and Implications of Patient Reported Clinical
Outcomes for Randomised Controlled Trials
Suzanne Breeman, Alison McDonald, Gladys McPherson, John Norrie,
Graeme MacLennan, Marion Campbell, Kath Starr, Seonaidh Cotton
University Of Aberdeen, Aberdeen, UK
Clinical outcomes are an important component of randomised controlled trials (RCTs) and are often used to
complement patient reported outcome measures such as health-related quality of life. Although clinical outcomes
were traditionally collected through clinical examination or laboratory results, routine data sources and selfreporting by patients are increasingly used.
We examined four RCTs that collected patient reported clinical outcomes through postal questionnaires. In each
RCT the patient reported clinical outcome was verified using either medical records, routine data sources or by
contacting the patient’s family doctor or hospital physician to ascertain the accuracy.
The accuracy of patient reporting of clinical outcomes is dependent on a number of factors including the nature
and timing of the clinical outcome and the phrasing of the clinical questions. For example, it may be easier for
a patient to report a knee-related hospital re-admission than self-report a urinary tract infection. Nevertheless,
approximately 15% of patient reported knee- related hospital re-admissions (collected through annual postal
questionnaires) could not be verified through routine data sources and/or medical records. Such inconsistencies
were shown to be a combination of misunderstanding by the patient and inaccuracies of the routine data sets.
Obtaining clinical information from patients is feasible, especially if the outcome of interest is a symptomatic
one. However with the potential inaccuracies associated with patient reporting of clinical outcomes, it may be
necessary to consider verifying such outcomes with medical professionals and/or routine data sources. Such a
strategy has implications in terms of staff time and cost and therefore has to be considered during the design
stage of the RCT.
We will discuss some challenges and inconsistencies between self-reporting and medically confirmed clinical
outcomes. We will highlight processes involved in verifying patient reported clinical outcomes and how adopting
such a verification strategy may impact on the overall trial results.
91
A88
Electronic Patient-Reported Outcome (ePRO) Assessment in Clinical
Trials: Strategies for Preserving Statistical Power
Antonia Bennett, AJ Vickers, EM Basch
Background: The availability of platforms and devices for electronic data capture has been a major step forward
for the assessment of patient-reported outcomes (PROs) in clinical trials. The advantages of electronic PROs
include real-time tracking of compliance, automated patient reminders, and date-time data for individual assessments. Multiple modes of ePRO data capture (e.g. PC/tablet, handheld, automated phone survey) allow flexibility
in clinical trial design. This has raised the question of whether use of multiple modes in a single trial might affect
statistical power.
Methods: We review the growing body of research on the measurement reliability across modes, and estimate
the effect on statistical power in several common PRO endpoint analyses. We consider this effect compared to
other common and PRO-related threats to power.
Results: Peer-reviewed studies indicate the measurement reliability across modes of administration is high
(approx 0.90) and consistent with the test-retest reliability of individual modes. We have calculated that even
if measurement reliability were more moderate (0.70 – 0.80), effects on statistical power would be small. The
estimated reduction in statistical power from using multiple modes of data collection is dwarfed by the estimated
loss of power associated with missing data (which can be prevented by allowing a second mode as alternate or
backup). The threat of multiple modes to power is also far less than mis-estimation of variance in sample size
calculation or use of PRO measures with low responsiveness.
Conclusions: Very small reductions in measurement reliability from the use of multiple modes of ePRO are outweighed by the advantage of data completeness. To preserve power in clinical trials, researchers would be better
off focusing on well-established areas of methodologic concern, such as accurate estimation of variance and
choice of responsive outcome measures.
A89
Randomized Decision Designs When the Number of Available
Subjects Precludes a More Standard Study Design
James R. Anderson and Lynette Smith
University of Nebraska College of Public Health, Omaha, NE, USA
Suppose a limited number (N) of patients is available for study and the traditional randomized trial design comparing ‘standard’ to ‘new’ is not feasible. This work was motivated by an interest in comparing two treatments
for recurrent Wilm’s tumor, where about 40% of patients are event-free long- term with standard treatment. One
option is a study design which seeks to maximize the number of study subjects receiving the better treatment.
Consider a design for which n1/2 patients are randomized to each of 2 treatments and then time-to-event is
compared using the log-rank test. All remaining (N-n1) patients are then assigned treatment 1 (treatment 2)
based on whether the log-rank test is positive (negative).
We assumed an available sample size of 100. For exponential failure-time distributions with a baseline ? of
0.50 to 0.75, and for a range of relative risks from 0.65 to 0.80, the design which maximized the number of
subjects receiving the better treatment was to randomize about 40 patients (having observed about 20% of the
total expected information) and then assign the remaining 60 patients to the regimen with the better observed
outcome.
We hypothesized that, in other settings, the n1 corresponding to observing about 20% of the expected information
would be optimal. We ran simulation studies assuming a cure model outcome: S(t) = 0.4 + (0.6)*exp(- 0.75t).
We simulated studies of 100 patients, with n1 values from 20 to 80 and cure rate increases corresponding to
relative risks from 0.65 to 0.80. The number of study subjects receiving the better treatment was maximized at
an n1 value of 40-45 (corresponding to 17- 20% of the total expected number of events).
92
A90
Bio-Creep Under Serial Use of Non-Inferiority Trials
Designed for Preservation of Effect
Katherine Odem-Davis, Thomas R. Fleming
University of Washington and Fred Hutchinson Cancer Research Center, Seattle, WA
In non-inferiority (NI) trials, the evaluation of the efficacy of a new experimental treatment allows for some defined
level of reduced effect as compared to an active control standard. Serial use of NI trials may lead to erosion in the
level of improvement provided by newly approved therapies; this phenomenon is called ‘bio-creep’. Simulations
were designed to facilitate understanding of bio-creep risk when approval of a new treatment with efficacy less
than some proportion of the effect of the active control treatment would constitute harm, such as sulfonamides
or penicillin for treatment of Community-Acquired Bacterial Pneumonia. In this setting, risk of approval of insufficiently effective therapies may be great, even when the standard treatment effect is ‘constant’ across trials.
Among the many possible factors contributing to this manifestation of bio-creep, the most influential were the
method for selecting the active control, the choice of non-inferiority margin, and bias in the active control effect
estimate. Therefore, when non-inferiority testing is performed, margins should be based upon the estimated
effect of the active control, should account for the variability and for likely sources of bias in this estimate, and
should address the importance of preservation of some portion of the effect of the standard.
A91
Standard Deviation Choice and Sample Size Calculation in Clinical Trials
Henian Chen, Sophie Chen
Henian Chen, Department of Epidemiology & Biostatistics, College of Public Health,
Clinical and Transitional Science Institute at College of Medicine, University of South
Florida, Tampa, Florida, USA. Sophie Chen, Health Canada, Ottawa, Canada
Purpose: This study demonstrates how errors in estimating the SD of a population can lead to inaccurate
sample sizes and underpowered studies, and offers recommendations for maximizing the likelihood of achieving
adequate statistical power.
Results: Our simulated data show that greater sample size provides a more reliable estimate of the SD of the
population than a smaller one. All minimal and 25th percentile sample SDs fell below 44 (the population SD) no
matter how big the sampling sample size (from 2 to 100). For samples sizes 10 and 100, the minimum sample
SDs underestimate the population SD by 47.1% ([44 – 23.27] / 44) and 18.3% ([44 35.93] / 44), respectively.
For all sample sizes below 40, the mean sample SDs fell below the population SD; for sample sizes of 40 or
greater, the mean sample SDs were close to the population SD. All maximum and 75th percentile sample SDs
exceeded the population SD. Based on a published underpowered trial (n1=13, n2=17 and power < 30%), we
found the reported SDs ranged from 1.8 to 9.3 from the literature, with a weighted average SD of 8.1. This study
needs to have n=66 for each group to reach a power of 80% according to our calculation.
Conclusion: No explicit guidelines have been available for choosing an appropriate SD to use in the calculation
of sample size for a clinical trial. To remedy this problem, we have developed an algorithm and recommendations
for making a judicious choice intended to minimize the risk of conducting an underpowered study.
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A92
Measurement Issues in the Hamilton Rating Scale for Depression May
Conceal Positive Findings in Clinical Trials for Major Depression
Chengwu Yang1, Wenle Zhao2
1Pennsylvania
2Medical
State University College of Medicine, Hershey, PA, USA;
University of South Carolina, Charleston, SC, USA
Many depression trials used the Hamilton Rating Scale for Depression (HRSD) as the primary measure of depression, although its severe measurement issues had been well-known. In a trail (Kellner, Kanpp, et al., 2006) that
compares continuation electroconvulsive therapy (C-ECT) vs. Pharmacotherapy (C-Pharm) for relapse prevention
in major depression, the total score of the 24-item HRSD (HRSD24) was used to define relapse or remission.
That trail found no statistically significant differences between the two arms. However, the results might be
misleading, simply because the uni-dimensional assumption made for the HRSD24, i.e., all of the 24 items are
measuring a single domain (depression) and therefore the 24 item scores can be summed to a single total score
as a measure of depression, might be wrong. In this study, the original data from that trial (201 patients with
98 C-ECT, 103 C-Pharm) were utilized to investigate measurement issues in the HRSD24. Confirmatory factor
analyses (CFA) for the uni-dimensional assumption of the HRSD24 were implemented on the data at visits 1, 2,
3, and 4. Results showed that this uni-dimensional assumption failed at each of the 4 visits. This indicated that
the single total HRSD24 score should not be used as the defining variable for relapse or remission at any of
the visits, thus the analyses using this total score was misleading, and may conceal some true positive findings
in that trial. Exploratory factor analysis (EFA) on all of the 24 items failed to yield a consistent factor structure
across the 4 visits. Then item-level analyses of the 24 items were implemented, and results showed that statistically significant differences exist on 3 of the 24 items between the two arms. It might be worthy to re-investigate
the findings from some of the large depression trials that used the HRSD, especially those with negative findings.
A93
Lasso Tree for Cancer Stage Grouping
Yunzhi Lin, Sijian Wang, Rick Chappell
Department of Statistics, University of Wisconsin - Madison, WS, USA; Department of Biostatistics
& Medical Informatics, University of Wisconsin - Madison, WS, USA; Department of Biostatistics &
Medical Informatics and Department of Statistics, University of Wisconsin - Madison, WS, USA
The tumor-node-metastasis (TNM) staging system has been the lynchpin of cancer diagnosis, treatment, and
prognosis for many years. For meaningful clinical use, an orderly, progressive grouping of the T and N categories
into an overall staging system needs to be defined, usually with respect to a time-to-event outcome. This can be
reframed as a model selection problem for a censored response grouped with respect to features arranged on
a partially ordered two- way grid (the TN table), and a L1 penalized regression method is proposed for selecting
the optimal grouping.
Instead of penalizing the L1-norm of the coefficients like lasso, in order for the grouping to occur, we place
L1 constraints on the differences between neighboring coefficients. The underlying mechanism is the sparsityenforcing property of the L1 penalty, which is expected to give a reduced number of unique coefficients that represent different groups. A partial ordering constraint is also required as both the T and N categories are ordinal.
A series of optimal groupings with different numbers of groups can be obtained by varying the tuning parameter.
This gives a tree-like structure for partitioning the TN table, and thus offers a visual aid on how the groupings are
made progressively. We hence call the proposed method the lasso tree.
We illustrate the utility of our method by applying it to the stage grouping of colorectal cancer. Simulation studies
are carried out to examine the finite sample performance of the selection procedure. We demonstrate that the
lasso tree is able to give the right grouping with moderate sample size, is robust with regard to changes in the
data, and is not affected by random censorship.
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A94
Some Strategies for Defining Non-Inferiority Bounds in Active-Controlled
Trials With No Placebo-Controlled Data for the Active Comparator
Aditi Sapre, Uma Kher
Merck, Whitehouse Station, NJ, USA
Non-inferiority trials are appropriate when there is clear clinical rationale that a placebo cannot be used, and
inference needs to be made to a putative placebo group to ensure the test compound is effective. However,
with the development of drugs that have greater efficacy than the existing gold standard therapy, the use of this
standard as a comparator treatment in future trials with new novel drugs may be inappropriate. This is particularly
true in the area of antithrombotics for stroke prevention in patients with atrial fibrillation. With the existing gold
standard, Warfarin, likely to be replaced by one of possibly three new compounds in coming years, newer drugs
for the treatment of SPAF will be faced with the challenge of showing non-inferiority to a new gold standard, that
was never tested in a placebo-controlled setting. This leads to the challenge of defining a NI bound based on
preserving a certain percentage of the placebo effect, where no placebo-controlled studies exist. We propose a
strategy that incorporates placebo controlled data for the existing gold standard (warfarin) and warfarin controlled
data for the new gold standard in defining the NI bounds for a time to event endpoint.
A95
Use of Routinely Collected Data Within Primary Care Medical Centre-Based Trials
Nicola Greenlaw1, Richard Lowrie2, Frances S. Mair1, Paul Forsyth2,
Pardeep S. Jhund1, Alex McConnachie1, Brian Rae2, John J.V. McMurray1
1University
of Glasgow, Glasgow, Scotland, UK; 2NHS Greater Glasgow and Clyde, Glasgow, Scotland, UK
Interventions to improve patient care are sometimes delivered to whole primary care medical centres. In such
instances, it is natural to use a cluster randomized clinical trial design to test the intervention effect. Ideally,
outcome data are collected at the individual level, though follow-up rates can be poor, particularly for patients in
non- intervention centres who may have little involvement with the study beyond providing data. However, after
an initial contact with patients to obtain consent and baseline information not otherwise available, utilization of
routinely collected data, in the form of medical centre records, allows for near complete follow-up at an individual
level with minimum additional contact. In Scotland, data on all hospitalizations and deaths are also routinely
collected and can be linked to individual patients, allowing for long-term passive follow-up. These data include
reasons for hospitalization, length of hospital stay, and causes of death.
There are several advantages to cluster randomized studies, such as simplified trial organization and reduced
contamination between intervention groups. Disadvantages include the increased sample size required for the
same statistical power and the need for more complex analyses. Use of routinely collected data is advantageous
for several reasons, including reduced trial costs and maximization of follow-up, though limitations include the
accuracy and completeness of the data collected.
These issues will be discussed in relation to the Heart failure Optimal Outcomes from Pharmacy Study (HOOPS),
recently completed in Glasgow, Scotland, which used primary care medical centres to recruit patients with left
ventricular systolic dysfunction, and to deliver an intervention of pharmacist-led medication review, to optimize
the use of evidence-based medicines. Details of medication use up to two years post- randomization were collected through medical centre records. Routinely collected national hospitalization and death records were also
used to follow patients up for a median of 4.7 years.
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A96
Routine Data – Is It Good Enough for Trials?
Alex Wright-Hughes1, Liz Graham1, Amanda Farrin1, David Cottrell2
1Clinical
Trials Research Unit, University of Leeds, Leeds, UK; 2School of Medicine, University of Leeds, Leeds, UK
We explore the possibility of obtaining routinely available data for use in clinical trials, the reliability of this data,
and the benefits of this approach if found to be successful.
The SHIFT Trial (a randomised controlled trial of family therapy vs. treatment as usual for adolescents following
self-harm) is used to illustrate the process. The Trial’s primary endpoint (repetition of self-harm leading to hospital attendance) requires timely and regular collection of hospital attendance data to inform the timing of analysis,
and is thus a resource intensive task requiring researcher visits to Hospitals to interrogate local medical records.
We are exploring the feasibility of collecting this data from a central source, the NHS Information Centre (IC). The
IC holds data provided periodically by English Hospitals, their main aim being to provide England-wide statistics
to inform frontline decision makers. However we wish to assess whether this is also a complete and reliable
means of acquiring data for research. Benefits include: a) Regular, fast England-wide data retrieval rather than
collection from an identified, limited hospital ‘pool’; b) avoidance of potentially biased data collection due to, for
example, more frequent visits to some Hospitals than others; and c) to free up researcher resources.
After comparing data gathered by the Researchers from pre-identified, representative Hospitals with data retrieved
from the IC, a change to the method of primary outcome data collection may be instigated after consideration
of: a) The percentage of self-harm episodes recorded & coded appropriately; b) The percentage of required data
items retrieved for each episode; c) Data quality for Hospitals with diverse catchment areas - to ensure recommendations for appropriate methods of data collection can be made at a study level and a site level.
Preliminary findings relating to the reliability of routine data for use in clinical trials will be presented.
A97
Contemporary Clinical Research in Adult Cardiovascular
Medicine: a Perspective From Clinicaltrials.gov
David F. Kong, Karen P. Alexander, A. Zoe Starr, Judith M. Kramer, Karen Chiswell, Robert M. Califf
Duke Clinical Research Institute, Durham, NC, USA; Duke Translational Medicine Institute,
Durham, NC, USA; Clinical Trials Transformation Initiative, Durham, NC, USA
To describe the broad portfolio of cardiovascular clinical research, the Duke Clinical Research Institute (DCRI) and
the Clinical Trials Transformation Initiative (CTTI) derived a dataset for aggregate analysis from ClinicalTrials.gov.
We identified 40,970 clinical research studies registered after September 2007 where human subjects received
diagnostic, therapeutic or other interventions per protocol. By analyzing 18,491 descriptors from the National
Library of Medicine’s Medical Subject Heading (MeSH) thesaurus and 1,220 free-text terms, we included only
studies related to the diagnosis, treatment or prevention of diseases of the heart and peripheral arteries which
enrolled adults ?18 years (N=2,325 studies). The identified studies were 74% ongoing, 22% completed, and
4% terminated, withdrawn, or suspended. The study intervention was drug in 45%, device or procedural in 39%,
behavioral in 8%, and biologic or genetic in 3%. Development phase was Phase 4 in 25.6% , Phase 3 in 19.1%
, Phase 2 in 15.9%, Phase 0 or 1 in 4.9% , and inapplicable in 34.5%. Many studies (46.3%) anticipated enrolling fewer than 100 subjects. Only 16.8% of phase 3 studies anticipated more than 1,000 subjects. In phase
3 studies, the median anticipated enrollment was 200 subjects. Most studies had one (26.8%) or two arms
(59.9%); 94.7% of studies with two or more arms were randomized. Only 32.0% were double blind, 15.1% were
single blind, and 52.9% were open label. Industry was the most frequent sponsor overall (32.0%) and across
development phases. Non-US oversight authority was listed for 60% of studies. Of studies with US oversight,
47.9% reported FDA oversight. Cardiovascular medicine is widely regarded as a vanguard for evidence-based
drug and technology development. This survey of cardiovascular studies reported in the clinicaltrials.gov registry
reveals substantial heterogeneity in study design and sponsorship. The preponderance of small trials represents
an opportunity to encourage collaboration and foster research networks.
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A98
The Clinicaltrials.gov Results Database as a Resource for Designing Clinical Trials
Elizabeth C Wright
National Institute of Diabetes Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
Background: Many clinical trials have endpoints that are changes in a measurement over time. An example is
change in kidney function as measured by glomerular filtration rate (GFR). Sample size and power depend on
the standard deviation of the change, but this is difficult to estimate from published data. ClinicalTrials.gov now
requires the submission of results for completed trials. The objective of this analysis is to determine the number
of trials with GFR as an outcome, the number with results, and the usefulness of the results data for planning
new trials.
Methods: A search was performed on November 10, 2011 using the terms “(NOT epidermal growth factor receptor) [ALL- FIELDS] AND (NOT cancer) [DISEASE] AND (gfr OR creatinine clearance OR egfr) [OUTCOME]”. SAS data
sets were created from protocol descriptive data downloaded from ClinicalTrials.gov. These data sets were used
to classify the protocols and to identify the outcome variables. Posted results data were reviewed and coded and
publications were identified by searching for the NCT number.
Results: Of 584 interventional studies that met the above criteria, 122 had completion dates in 2008-2009 and
results were posted for 39 (32%). Results were more likely to be posted for studies funded by industry (35/75
versus 4/47), p<0.0001. In total, 61 studies had results and change in GFR was an outcome for 22 of these (6
kidney disease, 9 post- transplant, and 7 other diseases). The duration of follow-up ranged from 24 hours to 5
years and the SD ranged from 3 to 35. Thirteen of the 61 studies had publications that included the NCT number.
Conclusions: Only 32% of eligible trials have results at this time. Review of results is time- consuming and baseline data are often incomplete, but the results database should be a useful resource in the future.
A99
Supplementing the Design of Comparative Binary Outcome
Trials With Sequential Meta-Analyses
Mireya Diaz
Detroit, MI, USA
Sequential meta-analyses, those in which power is determined via group sequential boundaries, have been suggested as a method to evaluate the status of the current evidence as well as tools for the trial planning process.
Regarding the latter, some may consider counterproductive to use design parameters from a meta-analysis
rather than from conventional sample size calculations. Here we examine conditions under which this could be
actually of gain. The minimum sample size for a target effect size of small magnitude (odds ratio up to 1.5) was
estimated using conventional formula for superiority and equivalence, considering alpha=0.05 and 80% power.
This size was estimated for a minimal proportion varying between 0.1 and 0.9, and adjusted for various values
of the inconsistency across studies in the meta-analysis ranging between 0 and 0.5. Meta-analyses subjected
to sequential monitoring with 5 and 20 studies were considered.
For a hypothesized difference of 20%, the average sample size for the trial ranges between 112 and 224 for
superiority and 206 and 412 for equivalence (a 95% reduction) within a meta-analysis of 20 studies. Likewise,
for a difference of 50% the average sample size for the trial ranges between 92 and 184 for superiority and 170
to 338 for equivalence (an 80% reduction) within a meta-analysis of 5 studies. The smaller the target effect size,
the greater the number of studies required in the meta-analysis. It is important to highlight that the individual
trial at this reduced sample size is underpowered but not the meta- analysis that will include it.
Here it is shown that incorporating meta- analytic information in trials comparing binary outcomes may be beneficial in cases where the target effect size is small as well as when heterogeneity of estimates across studies
is moderate. This is true from both superiority and equivalence points of view.
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A100
Developing Stop-Go Criteria for Pilot / Feasibility Studies to Continue to Full Trials
John Norrie
Centre for Healthcare Randomised Trials (CHaRT), Health Services
Research Unit, University of Aberdeen, Scotland, UK
Randomised trials are difficult to design, expensive to conduct, and frequently fail to deliver precise enough
answers to relevant healthcare questions. Particularly for complex intervention studies, in which there may be
poorer background knowledge going into the trial, being confident that all design elements (PICO - Population,
Intervention, Control, and Outcomes) are properly understood and optimised is a considerable challenge. In addition, the majority of trials struggle to recruit on time and to budget, and there are often issues of retention that
can undermine a trial.
Increasingly public funders (e.g. UK NIHR HTA/MRC) are requiring reassurance on many of these issues via an
internal pilot or feasibility study, before releasing funding for the full trial. Although there has been an explosion
of interest in adaptive designs, much of this has been from a theoretical statistical perspective, without so far
corresponding attention paid to the practical challenges of how you embed such design flexibility into a real trial,
and make reliable decisions on the basis of an often small amount of information of uncertain quality, probably
tainted by many sources of bias as the trial struggles to get itself established.
This talk will discuss the issues around developing ‘stop-go’ criteria to confirm whether a trial should expand
to a full trial. These usually include performance metrics for recruitment, but may also include fidelity to the
randomised intervention, completeness of follow up (retention), and cost profiles. This will be from a practical
perspective and use real examples of such ‘stop-go’ criteria from publicly funded trials. It will contrast ‘information’ (waiting until a pre-specified level of information is accrued) vs. ‘time’ (information accrued in a fixed time)
approaches to stop-go algorithms, and will emphasise the need for careful interpretation of the signals from a
pilot/feasibility study to inform progression to full trial.
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P01
Working With At-Risk Populations
Allison Caban-Holt, Cecil Runyons, Josh Turner, Korey Vallance, Sarah Hatcher
University of Kentucky Sanders-Brown Center on Aging, Lexington, KY, USA
Introduction: Conducting research with an aging population in a longitudinal clinical trial can pose unique challenges, particularly when cognitive decline is the primary endpoint. Unanticipated issues can arise due to use
of data gathering methods that may be routinely used with younger research participants, but are less effective
when used with older adults. Such differences may lead to false impressions of participant status and incidence
of endpoints. The analysis of procedural methods that may disproportionately affect older adults is of critical
importance at this time when many clinical trials are being undertaken to investigate interventions aimed at the
older adult population.
Further, research challenges can be magnified when a clinical trial is undertaken as an ancillary study to another
larger trial. The directions of the larger study affect the ancillary study in profound ways that may also lead to
dramatic changes in research procedures.
The NIA-sponsored PREADViSE study is an ancillary study of the prostate cancer prevention trial, SELECT. The
goal of PREADViSE is to examine the effectiveness of the antioxidants Vitamin E and Selenium in preventing
Alzheimer ’s disease in older men in the United States, Canada, and Puerto Rico.
Objectives: The purposes of this poster are to: 1. Discuss challenges facing an ancillary clinical trial when the
parent study undergoes major changes. 2, Elucidate some of the challenges encountered with cognitive evaluations of older men via telephone contact. Such as:
a) Logistics of contacting aging men who are still actively working outside the home b) Obtaining meaningful
test results from participants who have sensory deficits c) Recognizing the impact of health issues, including
recent surgery, chemotherapy, or serious illness on cognitive measurement d) Accelerated lost-to-follow-up, due
to death, chronic illness, or placement in a nursing home.
P02
Interobserver Reliability of Tongue Diagnosis Using
Traditional Korean Medicine for Stroke Patients
Mi Mi Ko, Ju Ah Lee, Myeong Soo Lee, Byoung Kab Kang, Tae Yong Park
Brain Disease Research Center, Korea Institute of Oriental Medicine, Republic of Korea
Background: In Korea, many stroke patients receive traditional medical care because the country has its own
system of traditional alternative medicine called Traditional Korean Medicine (TKM). Observation of the tongue,
also known as tongue diagnosis, is an important procedure in diagnosis by inspection in TKM. However, the
clinical competence of tongue diagnosis was determined by the experience and knowledge of the clinicians who
used tongue diagnosis. Much of the experiences in traditional tongue diagnosis have not been verified scientifically or quantitatively. We investigated the reliability of TKM tongue diagnosis in stroke patients by evaluating
interobserver reliability regarding tongue indicators as achieved by TKM practitioners.
Methodology/Principal Findings: A total of 658 patients with stroke admitted to 9 oriental medical university
hospitals participated in this study between February 2010 and December 2010(Figure 1). Each patient was
independently seen by two experts from the same department for an examination of the status of the tongue.
Interobserver reliability was measured in three ways: simple percentage agreements, Cohen’s kappa coefficient
and Gwet’s AC1 statistic. Interobserver agreement for the tongue indicators among all subjects (n=628) was
generally high, ranging from “moderate” to “excellent” (AC1=0.43~0.97), while the interobserver agreement
about subjects regarding pattern-identification with the same opinion between the raters (n=451) was also generally high, ranging from “moderate” to “excellent” (AC1=0.5~0.98). Interobserver agreement was nearly perfect
for certain signs of special tongue appearance (mirror [AC1=0.95~1], spotted [AC1=0.96~0.98], bluish purple
[AC1=0.85~0.95]), poor for one of the tongue colors (pale [AC1=0.32~0.66]) and moderate for others (Table1,
Table2).
Conclusions: Clinicians displayed measurable agreement regarding tongue indicators via both observation and
pattern identification consistency. However, interobserver reliability regarding tongue color and fur quality was
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relatively low. Therefore, it is necessary to improve objectivity and reproducibility of tongue diagnosis through the
development of detail- oriented criteria and enhanced training of clinicians.
P03
Factors That Affect Men’s Feelings About Their Urination: Findings From a MultiCenter Clinical Trial of Phytotherapy to Treat Lower Urinary Tract Symptoms
Alan Cantor, Michael Barry, and Claus Roehrborn for the CAMUS Study Group
University of Alabama Birmingham, Birmingham, AL, USA
INTRODUCTION AND OBJECTIVES: Saw palmetto (SP) extracts are widely used by men as phytotherapy for lower
urinary tract symptoms (LUTS). Factors associated with perceptions about their urinary function in men who use
phytotherapy for their LUTS have not been well described.
METHODS: The Complementary and Alternative Medicine for Urologic Symptoms (CAMUS) trial was a randomized,
placebo- controlled double blind multi-center trial of 369 men ? 45 years of age with AUA (American Urological
Association) symptom index score ? 8 and ? 24 at study entry who were treated with SP at single, double, and
triple usual dose or placebo (P). Assessments were made at baseline and at 24, 48 and 72 weeks after randomization. These included questions about how the participant felt about his urinary function. We used multivariate
ordinal logistic regression to assess the effects of changes in AUA Symptom Index score, quality of life (QOL),
and BPH (benign prostatic hyperplasia) Index Score, age, and randomized treatment assignment on the participants’ perceptions of their urinary function.
RESULTS: Improvement of AUA Symptom Index Score, QOL, and BPH Index Score were associated with subjects’
perceptions of better urinary function from baseline to weeks 24, 48 and 72 (Table, change at 24 weeks shown).
Older age at enrollment was associated with more negative perceptions about the participants’ urinary function.
Randomized treatment assignment was not associated with these perceptions.
Conclusion: The main determinants of improved perception of urinary function seen in the CAMUS study were
improvements in AUA Symptom Index Score, BPH Index, and QOL. Older age was marginally associated with poor
perception after adjusting for these other factors. Treatment with saw palmetto was not associated with better
perceptions about their urinary function.
P04
Compliance Assessment for Eligibility in a 1-Year-Long
Ophthalmic Clinical Trial Investigating Eye Drops
Talat Almukhtar for the Diabetic Retinopathy Clinical Research Network
Jaeb Center for Health Research, Tampa, FL, USA
Purpose To present an objective and relatively straightforward method of assessing compliance in a randomized
clinical trial using eye drops.
Background Achieving good compliance is of crucial importance to success of clinical trials. Various methods
have been used to assess compliance with eye drops in ophthalmic studies. Subjective methods, such as patient
questionnaires or diaries, are prone to bias. Objective methods like digital monitoring devices require additional
resources and logistics to implement.
Design The topical non-steroidal anti-inflammatory drugs for non-central diabetic macular edema study is a 1-year
phase II randomized trial evaluating effects of 3-times daily nepafenac ® 0.01% drops compared with placebo.
In an attempt to minimize the number of poorly-compliant participants randomized, a run-in phase for 30-60 days
prior to randomization was implemented to assess compliance. At the end of the run-in phase only participants
who achieved 80% or more compliance were randomized (provided other eligibility criteria were met).
Each study bottle was weighed using a calibrated sensitive scale prior to dispensing to participants, and at each
follow-up visit after use. Since the length of the run-in phase will vary, a database of expected bottle weight after
each required dose was created. A compliance formula that takes the following into consideration was defined:
expected initial bottle weight, expected follow-up weight, observed initial bottle weight, observed follow-up weight.
Based on previous reports, 80% was chosen as the compliance threshold below which participants would not be
eligible for randomization.
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This approach has many limitations; for example, weight change may not necessarily reflect the proper dosage
or installation timing of drops. Furthermore, short-term compliance may not necessarily translate into long-term
compliance.
Conclusion Compliance with study drops poses challenges in ophthalmic clinical trials. We present an objective
and relatively easy method to evaluate compliance that may help exclude potentially non-compliant participants.
P05
Strategies Implemented to Ensure Data Accuracy for Final Analysis
Kathryn Mangoff, Dalah Mason, Sonya Mergler, Johanna Sanchez, Jon Barrett, Elizabeth Asztalos
The Centre for Mother, Infant, and Child Research, Sunnybrook Research Institute, Toronto, Ontario, Canada
The Twin Birth Study (TBS) is an international multicentre randomised controlled trial that recruited 2804 patients
from 106 centres in 27 countries. TBS seeks to determine, in women expecting twins, whether a policy of
planned Caesarean section decreases the likelihood of perinatal or neonatal mortality or serious neonatal morbidity, compared to a policy of planned vaginal birth. Recruitment for the trial ended in April 2011 and the final
analysis is scheduled to be completed by January 2012.
In order to prepare for the final analysis and answer this important research question, an intensive process of
cleaning the data began. In May 2011, specific processes were implemented to facilitate the data cleaning. All
the raw data was extracted from the database and multiple reports were compiled to ensure that all missing
answers had been queried. In addition, multiple data reviews were scheduled, to analyse the data by the allocated groups according to the analysis tables. Outliers and missing variables were reviewed, and centres were
asked to confirm or correct their responses. To keep centres informed of the status of their data, a “Complete
and Clean” report listing the percentage of data forms returned and queries resolved were emailed to each
centre. An “Overdue Primary Queries” report was sent monthly to the centres listing the queries that were still
outstanding. These strategies led to TBS achieving 99.6% clean data for the final analysis, as of November 30,
2011.
This presentation will share data cleaning strategies implemented by TBS to ensure data accuracy for the final
analysis.
P06
Integration of Data Management Systems for Large
International Randomised Controlled Trials
Michael X. Shi, Johanna Sanchez, Elizabeth Asztalos
Sunnybrook Research Institute, Toronto, Ontario, Canada
The Centre for Mother, Infant, and Child Research (CMICR) is the coordinating centre for several large, international randomised controlled trials (RCTs). To streamline data collection in the clinical trials, a web-based
Electronic Data Capture (EDC) system was acquired and implemented. To facilitate the operational side of clinical
trials, CMICR has been developing in-house data management systems, including a clinical trial management
system (CTMS), an interactive web response randomisation system (IWRS), and a drug supply management
system (DSMS).
One of the biggest challenges of leveraging the new EDC technology is having it be able to interchange and integrate data with CTMS, IWRS, DSMS and other technologies being used in the studies. Data integration is vital
for large RCTs because of the volume of data generated. The integrated data provide a more comprehensive
overview of trial progress, allow a closer monitoring of recruitment and data collection, improve trial analysis and
allow for better-informed decisions across the variety of tools and sources of information. From a data-handling
perspective, integration reduces redundancies and improves data consistency and quality through less human
interaction.
This presentation will discuss the design and implementation of the system integration and data exchange
between the different management systems. It will describe and demonstrate the use of the “interfacing”
approach that allows the flexibility and scalability to incorporate new components into data management systems.
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P07
Improving Data Management Through Data Tranfer
Janice Kwok, Michael Shi, Elizabeth Asztalos
The Centre for Mother, Infant, and Child Research (CMICR) is the data and clinical coordinating centre for several
multi-centre, international randomised controlled trials (RCTs). CMICR uses a web-based Electronic Data Capture
(EDC) system to collect study data on electronic Case Report Forms (eCRFs).The EDC system has a summary
screen that displays the status of each eCRF. Each eCRF has a scheduled timeframe for when it should be
completed, and those completed outside the timeframe are considered overdue or invalid if completed too early.
The EDC summary screen does not display the date when the eCRF was completed. To view the eCRF completion date, the user must go through the time-consuming task of opening each eCRF. The date is then manually
entered into a standalone Access database to track the completion status each eCRF. This method can be both
labor intensive and error-prone. Therefore, a method to accurately and efficiently track each eCRF completion
date was needed.
A solution to this problem was to develop a process to automate the transfer of data from the EDC system to
the Access database. The process involved downloading the data from the remote EDC system to a local copy of
the EDC database, on weekly basis. This local database was then directly linked to the Access database, allowing the data to by automatically transferred. This allowed the eCRF completion date to be automatically entered
while also eliminating the potential security risk of directly linking the EDC system to the Access database.
The introduction of this new process has eliminated the need to manually enter the date into the Access database. It has increased efficiency at the coordinating centre by ensuring that accurate records of the eCRF completion date are being kept, ultimately allowing for more effective data management.
P08
Adjudicating Life Study Outcomes Through the Outcome Management Tool
Cynthia L. Stowe1, Lea N. Harvin1, Ching-Ju Lu2, Thomas Gill3, Mary
McDermott4, Anne Newman5, Carlos Fragoso3, Michael E. Miller1
1Wake
Forest University School of Medicine, Winston-Salem, NC, USA; 2University of
Florida, Gainesville, FL, USA; 3Yale School of Medicine, New Haven, CT, USA; 4Northwestern
University, Chicago, IL, USA; 5University of Pittsburgh, Pittsburgh, PA, USA
The Lifestyle Interventions and Independence for Elders (LIFE) Study is a Phase 3, multicenter randomized controlled trial (RCT) designed to compare a moderate-intensity physical activity program to a successful aging health
education program in 1,600 sedentary older persons, age 70-89 years, across eight field centers. The primary
outcome is major mobility disability, defined as the inability to walk 400 meters. Secondary and tertiary outcomes
include serious fall injuries, pulmonary events, and cardiovascular events. Given the number of participants and
their age range, we expect to collect data on many outcomes throughout the length of the trial. These outcomes
require central adjudication. The need for a central tracking and monitoring system initiated the construction of
the Outcomes Management Tool (OMT) Adjudication System.
While the OMT manages and tracks outcomes, it also supports central adjudication of those outcomes. The
Adjudication System is an online system which tracks adjudicator assignments, allows medical records to be
reviewed online, allows voting by assigned adjudication committee members, and allows tracking of full committee votes. Administrators at the Data Management and Quality Control (DMAQC) Center also have the ability
to assign specific cases to adjudicators on a predetermined date and assign the full committee access to the
case, if required.
The final adjudication of the LIFE outcomes is made by the central adjudication committee based on satisfaction
of diagnostic criteria delineated in adjudication report forms. The electronic access allows adjudicators the freedom to review records online, communicate with administrators, and vote without being tied to a stack of papers.
This presentation will highlight the flow and functions of the Adjudication System within the Outcome Management
Tool.
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P09
Implementation of a Drug Management Utility in a MultiSite, Randomized, Double-Blinded Study
Jennifer Bacik McCormack, Colleen Allen, Maria Figueroa, Scott McCrimmon,
Mahesh Mutham, Glenn Tucker, Aimee Wahle and Paul VanVeldhuisen
Management of drug inventory in a multi-site, randomized, double-blinded study is of utmost importance. In many
traditional settings, a plentiful amount of drug kits are shipped to each participating site, with the expectation
that few drug shipments will be performed during the study. When the study drug(s) has short expiration dates, is
in short supply, is expensive to manufacture, or accrual rates are difficult to predict, careful monitoring of sites’
inventory is necessary to avoid study drug shortage or wastage. As the Coordinating Center (CC) of two studies
with some or all of these features, we integrated a utility for managing drug inventory into the enrollment module
of our electronic data capture (EDC) system.
In both studies, a master treatment table (MTT) houses the sequence in which treatments are assigned and a
kit inventory table (KIT) houses the kit numbers, their corresponding treatment group and availability status. An
EDC user interface allows the CC to request the number of drug kits to be shipped to a site. An email requesting
shipment of drug is automatically sent to the drug supplier. As shipments occur, the KIT is updated to indicate
that requested kits have been allocated to a particular site and are available for randomization. As randomization occurs, the enrollment module accesses the drug utility tables to provide the appropriate blinded treatment
assignment to the enrolling site.
An additional feature of the utility for the second study is an automated nightly process in which site inventory
levels and expiration dates are monitored and when pre-defined thresholds are crossed, a shipment request is
emailed to the drug supplier.
The benefits and risks of implementing a complex drug utility within an EDC deployment will be discussed, along
with the technical challenges, role of the drug supplier and necessary elements to make it successful.
P10
Conquering the Challenges of Conducting a Trial’s Central Initial Training at an
O’hare Hotel: The Blood Pressure in Hemodialysis (BID) Pilot Study Experience
Kimberly Wiggins1, Jennifer Gassman1, Karen Brittain1, Jack Mackrell1, Susan Sherer1, Joan Alster1,
Serena Cumber3, Susan Paine3, Katie Knipscher4, Shana Haynes4, Dana Miskulin4, Phil Zager3
1Data
Coordinating Center, Cleveland Clinic Quantitative Health Sciences, Clinical Trials Design & Analysis
Section, Cleveland Clinic, Cleveland, OH, USA; 2DCI Database, DCI Inc., Chicago, IL, USA; 3Clinical Coordinating
Center, University of New Mexico, Albuquerque, NM, USA; 4Tufts Medical Center, Boston, MA, USA
The BID Pilot Study is the test phase of a randomized clinical trial comparing effects of two levels of blood pressure control. Sixteen dialysis units at 5 participating sites will participate. This study is funded jointly by NIH/
NIDDK via R01 and the non-profit Dialysis Corporation Inc.
Because the study’s protocol requires standardized blood pressure measurements and data acquisition by distributed data entry, trial leadership determined that face to face training was required before patient enrollment
could begin. Minimal funding was available. Starting the training session at 11 am near an O’Hare airport saved
money on air fare, let most attendees find direct flights, and allowed same-day fly in.
Since the coordinators attending training needed to learn standardized blood pressure measurement, ABPM, and
calibration of the machines used for both types of measures, staff needed to bring multiple pieces of equipment.
Planning training for data entry was challenging. BID Coordinators use the internet to access Oracle forms
housed in an Oracle 10g database at the DCC. A location with strong and reliable but inexpensive wireless in
the meeting room was required.
Each coordinator needed a laptop computer with java installed. The system did not support Apple Macintosh
computers. Because several coordinators did not have laptops, we brought loaners from the DCC.
The training session, held in October 2011, successfully trained staff in blood pressure measurement, equip103
ment calibration and online data entry and data discrepancy resolution. Only two glitches occurred: 1) the team
could not find a soda can needed for a calibration procedure and 2) one coordinator brought a laptop running
Windows Vista and had to use a DCC staffer’s 10-inch netbook. The training session was judged to be cost- effective and highly successful. Patient enrollment began in November 2011.
P11
Integrating Data From Disparate Sources Into a Central Database in Trial
With Hybrid Funding: the Blood Pressure in Hemodialysis (bid) Pilot Study
Jennifer Gassman1, Kim Wiggins1, Jack MacKrell1, Karen Brittain1,
Susan Sherer1, Pramen Applasamy2, Serena Cumber3, Susan Paine3,
Rodrigo Madero3, Katie Knipscher4, Shana Haynes4, Dana Miskulin4, Phil Zager3
1
Data Coordinating Center, Cleveland Clinic Quantitative Health Sciences, Clinical Trials Design &
Analysis Section, Cleveland Clinic, Cleveland, OH, USA; 2DCI Database, DCI Inc., Chicago, IL, USA; 3Clinical
Coordinating Center, University of New Mexico, Albuquerque, NM, USA; 4Tufts Medical Center, Boston, MA
BID is the pilot for an RCT comparing two levels of blood pressure control. Sixteen dialysis units at five sites
began enrollment in November 2011, collecting extensive data on safety, feasibility, and optimal use of four
blood pressure estimates (dialysis machine, standardized, home, and ambulatory blood pressure measurement).
Efficiently integrating data from disparate sources maximizes data quality and minimizes cost.
Patients are identified by ID and a random alpha code, and the DCC is blinded to patient names. Site study
coordinators enter blood pressure data, oral medications, dialysis details and other clinical information via
Oracle forms to the Oracle 10g database at the DCC. Central MRI personnel similarly enter cardiac MRI results.
Extensive edit checks are applied at the data entry level.
BID is funded by NIH/NIDDK and Not for Profit Dialysis Clinic, Inc. (DCI), facilitating access to laboratory, dialysis
dose, and injectable medication data stored by DCI ID in DCI’s Nashville medical information system DARWIN. As
patients enroll, participating sites securely notify the Clinical Coordinating Center (CCC) staff, who then securely
provides the DARWIN database team a link between DCI ID and the BID ID and alpha code. Once a month, each
BID patient’s new data are securely transmitted to Cleveland for batch loading into the DCC database.
Data files from ABPM devices are securely transmitted from participating sites to the CCC, where data are
cleaned, formatted, and then securely transmitted to Cleveland for batch loading into the DCC database.
These batch loading processes save coordinators time and motion and increase data quality since coordinators
do not need to enter data that was previously machine-generated and stored.
The DCC emails weekly reports to Steering Committee members and participating sites showing the status of
missed visits, missing forms, missing data, and discrepant data. Thus, data acquisition is continually monitored.
P12
The Italian Register for Clinical Trials; the “Unique” E-Access for
Regulatory, Submission and Management of Clinical Trials
Carlo Tomino
Italian Medicines Agency, Rome, Italy
In accordance with the provisions of the national legislation issued in 2007, the National Monitoring Centre for
Clinical Trials - OsSC (http://ricerca- clinica.agenziafarmaco.it/en/node/22 ) supervised by the Italian Medicines
Agency (AIFA) has become a legally binding tool for applicants who wish to submit a clinical trial application to the
Regulatory Authority and the Ethics Committee. Within 2012 a switch over from paper to electronic submission is
expected. A Telematics Implementation Group (TIG) chaired by AIFA has been set up in 2008. In the TIG are represented Ethics Committees, National Regulatory Authorities, sponsors (both commercial and non commercial)
and CROs. The TIG has the mandate of defining user requirements with respect to e-submission; validate software development through user acceptance testing; actively participate in the pilot phase of the project; provide
support to AIFA initiatives to promote harmonization and guidelines in compliance with the EU legislation. The
user requirements and technical specifications of the single portal have been agreed and the software development and testing is on-going (Beta-version). Within 2011 a pilot phase with the participation of the TIG delegates
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has been completed. Either the initial clinical trial application and the substantial amendment module of the
single portal are being extensively tested in terms of functionality, reliability and performance. The new portal is
expected to be launched in early 2012 with the ultimate aim of reducing bureaucracy, harmonize procedures and
shortening delays in the assessment process of clinical trials with investigational medicinal products. This tool
will represent the unique access point for all the parties involved managing clinical trials on medicines in Italy.
P13
An Efficient and Inexpensive System for the Distribution and Tracking
of Investigational Medicinal Products in Clinical Trials
Patrick G. McDonnell, Thomas M. MacDonald, Isla S. Mackenzie, Robert Flynn
Medicines Monitoring Unit (MEMO), University of Dundee, Dundee, United Kingdom
Purpose: The efficient distribution and tracking of Investigational Medicinal Product (IMP) and Non-Investigational
Medicinal Product (NIMP) in clinical trials confers certain legal requirements together with meticulous recordkeeping. Manual systems that update a paper record each time a product shipment arrives, is supplied to a study
participant, or is returned for reconciliation and destruction are time consuming, prone to errors and expensive.
Implementing a system whereby records are maintained electronically and updated automatically can reduce
costs whilst improving record-keeping.
Methods: We examined state-of-the-art in pharmacy systems and concluded that a barcode-based product
tracking system was the most practical solution. Each IMP and NIMP are bar-coded and products are tracked
from arrival at the dispensary storage facility, supplied to patients, unused drugs returned with tablet counts
and destruction records. The system is integrated into the electronic Clinical Report Form (eCRF) and study
web portal from which regimen changes can be made. The system also produces bespoke medication labels,
Patient Information Leaflets (PILs), and other paperwork, both in English and other languages to be dispatched
to patients. Packages are also bar-coded to facilitate identification. Technicians assemble distribution packs in
one work-stream and then check packs in another work-stream to reduce errors.
Results: We have built an inexpensive, robust and legally-compliant system of managing supply of medication
to study participants. The system is currently being used in one large multi-national multi-centre study with a
complex IMP and NIMP regimen.
Conclusions: We have produced a semi-automated system for drug distribution that we predict will reduce cost,
errors, provide a robust audit trail and improve the quality and efficiency of drug supply in the clinical trial setting.
P14
Gynecolgic Oncology Group (GOG): Making a Web-Based Cardiff Teleform Generated
PDF Patient Clinical Reporting Form Dynamic With the Use of Adobe Fdf Files
Karen Puehn, Quang Le, Susan Klier, Bill Elgie
GOG Statistical and Data Center, Buffalo, NY, USA
Gynecologic Oncology Group Statistical & Data Center, Buffalo, New York The GOG Statistical and Data Center
(SDC) developed the SDC Electronic Data Entry System (SEDES) to capture clinical data electronically via a
secure website. Over 800 sites have used SEDES to enter and amend over 500,000 electronic Case Report
Forms (eCRFs). One of the foundations of this dynamic database driven application is the use of proprietary
Adobe Forms Data Format (FDF) files to programmatically manipulate the Adobe Acroform pdf web-based eCRFs
created with Cardiff Teleform software. FDF files can be used to import data into a pdf form. The SDC chose to
use static FDF files created and stored on the server to import patient database data into eCRFs stored on the
server. These FDF files contain the eCRF’s form field names and values to be imported as well as the web link to
the pdf form. A patient registered to a GOG Protocol has a set of study specific expectations assigned and accessible as links in an electronic Patient Form Schedule available via SEDES. Clicking on an eCRF link generates a
FDF file on the server for that patient and form type which in turn automatically opens the semi-prefilled eCRF
allowing the user to complete and submit the data for processing and storage. The FDF file minimally consists
of data needed to prefill the form header with patient study identifier, today’s date and web account username.
Upon submission, data are immediately available for use through the same process via a FDF file generated from
the submitted data prefilling the eCRF for updating.
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P15
Eosinophilia as a Potential Surrogate for Definitive Diagnosis of
Strongyloidiasis in an Immigrant Population at a Community Clinic
Kathryn E. Spates1, Nicole C. Holland2, Amara G. Pabon3, JeanAnne M. Ware4, Thomas B. Nutman5
1Laboratory
of Parasitic Diseases, NIH, SAIC-Frederick, Inc., NCI-Frederick, Frederick, MD, USA; 2Laboratory
of Parasitic Diseases, NIH, SAIC-Frederick, Inc., NCI-Frederick, Frederick, MD, USA; 3Laboratory of Parasitic
Diseases, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD, USA; 4Laboratory of
Parasitic Diseases, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD, USA; 5Laboratory
of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD, USA
Determining the cause of persistent eosinophilia in immigrants to the United States can be hampered by costs
needed to evaluate suspected parasitic infections. Thus, diagnosing eosinophilia- causing helminth infections
by stool examination or serology is often beyond the means of community health clinics that commonly serve
immigrant populations. To define the causes of persistent eosinophilia among an immigrant population seen at
a single community free health clinic, 41 patients (originally from Central and South America, Africa, Asia and
the Middle East) -- who arrived in the United States 1-27 years (median 7 years) previously--were found to have
an absolute eosinophil count (AEC) >500/uL and were referred to the National Institutes of Health for further
testing. Of the 41 referred patients, 33 (80.4%) had positive Strongyloides stercoralis-specific serology. Nine of
these 33 (27%) also had schistosomiasis (n=6) or hookworm (n=3) infection. Although there was no statistical
difference (p=0.15) in the baseline eosinophil levels between those with strongyloidiasis and those without,
serum IgE levels differed dramatically between the two groups (geometric mean levels 74 U/ml vs. 566 IU/ml,
p<0.01). Interestingly, 16/33 (48.7%) Strongyloides positive patients had an AEC greater than 1000/uL during
screening, whereas only 2/8 (25%) without Strongyloides had eosinophil levels that exceeded 1000/uL. All 33
patients with a definitive parasitologic diagnosis received ivermectin and (when appropriate praziquantel and/
or albendazole) treatment; 11 have been evaluated one-year post treatment. Not unexpectedly, there was a dramatic and significant (p<0.01) decrease in AEC following treatment, with all returning to normal levels. IgE levels
also fell dramatically following treatment. Thus, in community clinics that provide health care to immigrants well
after arrival in the United States, an AEC can be used as a surrogate for stool examination and serology and may
be a trigger for empiric treatment when testing is limited by cost.
P16
Posting Study Results to Clinicaltrials.gov: Effective Tools and Lessons Learned
Elizabeth Paynter, Heather Kopetskie, Gary Johnson
Rho, Chapel Hill, NC, USA
The Food and Drug Administration requires most clinical trials to post results to ClinicalTrials.gov within one year
after completion of data collection for the study’s primary endpoint measure. The study’s sponsor is responsible
for posting results to ClinicalTrials.gov, however the statistical and data coordinating center at Rho has been
employed to help with this process. Novice users may find the system difficult to navigate. Often users are
unsure of what information is required or allowable. Additionally, many study teams want to review and approve
results before they are posted. In an effort to help both the person posting results and the reviewer(s), Rho created a fill-able Word template. This template provides instruction and structure for the person posting results.
The template also informs the user of character limits, possible selections, what information is required versus
optional, and guidance on typical entries. For the reviewer(s), the template provides a means to see the results
without having to be given login-access to ClinicalTrials.gov. Additionally, the reviewer can see the system limitations and what options are available, which can aide in constructive feedback. Part of posting study results to
ClinicalTrials.gov is to post adverse events. Hand-entering adverse events for most trials can be a tedious task.
ClinicalTrials.gov allows results to be uploaded in a prescribed XML format. Software developers at Rho created
a program that will take a SAS® data table and convert it into an XML file that is compatible with the structure
provided by ClinicalTrials.gov. Once study results are released to ClinicalTrials.gov, the website staff review study
entries and provide feedback and suggestions. During this process we have modified our tools to better meet
those expectations. From the lessons learned in the development of results for ClinicalTrials.gov, our new tools
can greatly aid and expedite the process of posting study results.
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P17
Changing Directions in the Antihypertensive and Lipid-Lowering
Treatment to Prevent Heart Attack Trial – Involving Outside
Investigators in Manuscript Preparation and Ancillary Studies
Sara L. Pressel, Barry R. Davis, Linda B. Piller, Lara M. Simpson,
Charles E. Ford, Jose-Miguel Yamal, Ellen Breckenridge, Jeffrey L. Probstfield
University of Texas School of Public Health, Houston, TX, USA
The leadership of most clinical trials, including the Antihypertensive and Lipid- Lowering Treatment to Prevent
Heart Attack Trial (ALLHAT), facilitate manuscripts and ancillary studies by investigators within the study. To
enable data use by outside investigators, studies sponsored by the National Institutes of Health provide a
limited-access public use data set, and ALLHAT has done this. Additionally, ALLHAT policies allowed outside
investigators to submit data requests directly, but limited the releases to those data that were already publicly
available or not being pursued by its investigators.
To facilitate and encourage use of ALLHAT’s dataset by outside investigators, the National Heart, Lung, and
Blood Institute has funded a new phase entitled ALLHAT Continuation and Outreach. Its purposes are to:
(1) develop processes that assure optimal scientific contributions, build on to- date publications and explore new
areas, in part through involving appropriate consultants as leaders of relevant scientific areas; (2) encourage
productive interdisciplinary collaboration and mentor early-stage investigators from a diverse set of institutions,
especially investigators with no recent history of participating in ALLHAT; and (3) promote awareness of the
ALLHAT resources among research and clinical communities.
This represents a change in direction for ALLHAT. Previous ALLHAT policies protected the interests of study
investigators and reserved most Coordinating Center resources for study investigators. ALLHAT’s new phase will
widen participation in paper- writing and ancillary studies to investigators within and outside of ALLHAT. It also
represents a new approach among clinical trials. While several epidemiologic studies have successfully adopted
such an approach, ALLHAT will be the first clinical trial to do this.
Additional details of the rationale for ALLHAT’s new phase will be discussed, as well as details of the new study
governance structure and the Engagement Plan, which provides guidance for achieving the above aims.
P18
The Global Obstetrics Network (GONET): an International Collaborative Group
Elizabeth Thom and Ben Willem Mol for the Global Obstetrics Network
Rockville, MD, USA; Amsterdam, The Netherlands
Background: Multiple groups conduct national and international clinical trials in obstetrics. The rarity of the most
compelling outcomes, such as maternal or neonatal death and childhood disability, at least in developed countries, has led to the use of less compelling outcomes and/or lower power. Meta-analyses are often employed in
this field but these are challenging when different definitions of outcomes are used or different data fields collected. In addition, trials have been unwittingly duplicated, leading to a poor use of global resources. For example,
seven large overlapping trials of antioxidants to prevent preeclampsia were conducted — all were negative. The
process of setting up an international collaboration to address these issues is described.
Methods: In 2010, investigators representing different study groups met for the first time, and formed a core
group who defined the goals of the collaboration. These include developing a database of ongoing and planned
trials, harmonizing obstetrical terms and definitions, defining common endpoints, coordinating study protocols to
facilitate meta-analyses, setting up an education program on trial design and performance, establishing priority
areas for future trials, and obtaining funding to support all activities including international collaborative trials.
All clinical researchers are invited to participate, especially researchers from resource poor countries.
Results: GONet has formalized its mission, charter and structure, and held a formal launch meeting. The Board
includes representation from Europe, North America, Australia and Asia. A members’ website has been developed (www.globalobstetricnetwork.org), including a database of ongoing/planned trials. A course on clinical trial
design has been organized. A meeting with representatives from international funding agencies was held; a
funding proposal is underway. Priorities for future trials will be decided at the second annual general meeting.
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Conclusion: Progress has been made towards global collaboration and more efficient use of resources in obstetric trials.
P19
Estimating Death Rates in Substance Use Disorder Clinical Trials
Robert Lindblad, Lian Hu, Marie Campanella, Radhika Kondapaka,
Carmen Rosa, Colleen Allen, Paul Van Veldhuisen
Rockville, MD, USA; Bethesda, MD, USA
Interpreting results of safety reporting in substance use disorder (SUD) clinical trials is difficult when the baseline rate of serious events like deaths in this population is not well described. Particularly for Data and Safety
Monitoring Board reviews, defining a threshold event rate could provide guidance to recognize increased risk
in a given clinical trial. Often, the reported number of deaths in any given trial is too small to characterize this
issue. National death rates by age and gender are publically available and provide a baseline. Since 1999, the
National Institute on Drug Abuse, National Drug Abuse Treatment Clinical Trial Network (CTN) has posted 21
SUD pharmacologic and/or psychosocial intervention clinical trials spanning various SUD populations to the CTN
public data share. Protocols and safety data from these completed trials were reviewed. A total of 61 deaths
(0.6%) were identified from adverse event reports across 9,396 enrolled participants (5,543 male, 3,844 female,
9 unknown). The overall death rate in the CTN SUD clinical trials was 14.4 deaths per 1,000 person years (PY),
and was numerically higher in females (17.1 per 1,000 PY) than males (12.1 per 1,000 PY). By age, the highest
death rate was observed in the 25-34 year olds (17.6 per 1,000 PY). These death rates are numerically higher
when compared with age- and gender- specific rates to the national death rate information and likely represent
underlying social issues surrounding SUD populations, particularly in women, and likely are not attributable to
clinical trial participation. Estimating death rates within types of substance use disorders may further contribute
to the understanding of underlying risks in SUD populations
P20
Statistical Considerations for Analysis of Progression-Free Survival Data
Imogene Grimes, Janet Wittes
Otsuka Pharmaceutical Development & Commericalization, Inc.; Rockville, MD, USA
Progression- free survival (PFS) is a composite endpoint incorporating the time to either death or progression,
with varying definitions of progression. Time to death is a continuous variable where death occurs at random
times, and the date of death is known specifically. Time to progression is, strictly speaking, an interval measure,
as the date of progression is unknown so the time to progression is not precisely known. When the assessment
of progression is made, a patient is classified as having progressed or not having progressed, but the time of
progression is unknown. In our experience in oncology, the most common statistical methods for PFS include a
graphical display of a Kaplan-Meier curve and analysis using a logrank test or a Wilcoxon test with some type
of accommodation for censoring (usually). When PFS in the particular dataset is composed mostly of time to
death (as a continuous measure) and time to progression (not measured continuously), these analysis methods
perform well. When, however, PFS is dominated by time to progression, and when the assessment times are
infrequent, the Kaplan-Meier graph resembles a step function, and these analysis methods may be far from
optimal. A life-table extension of the Mantel-Haenszel test may perform better, and Cutler-Ederer estimates for
interval data may describe the data more accurately. This paper presents a discussion of the appropriateness
of the analytical methods for PFS with examples of comparisons from PFS datasets.
P21
A Study of Autologous Valve Replacement - Cd133+ Stem Cell-Plus-Fibrin Composite
Based Sprayed Cell Seeding for Intra-Operative Heart Valve Tissue Engineering
Aenne Glass, Guenther Kundt
Institute for Biostatistics and Informatics in Medicine and Ageing Research IBIMA, University of Rostock (Germany)
Objective The development of biological valve prostheses with lifetime native-like performance and optimal host
engraftment is a goal of heart valve tissue-engineering. We describe a new concept for autologous graft coating
based on a CD133+-stem-cells-plus-fibrin-complex (SC+F) processed from bone marrow and peripheral blood
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of one and the same patient. Methods CD133+-SC (1x106cells/ml) from human bone marrow and autologous
fibrin (20mg/ml) were administered simultaneously via spray administration. During static cultivation, SC+F
performance was monitored about 20 days after delivery and compared to controls. For dynamic testing SC+Fcomposite was sprayed on a decellularized porcine pulmonary valve and transferred to a bioreactor under pulsatile flow conditions for 7 days. Quantitative analysis of the data is given for experimental group containing fibrin
and control group without fibrin, respectively. Because measurements were made several times within three
independent groups we applied the GLM Repeated Measures procedure for statistical analysis to test the null
hypotheses about the effects of both the between-subject factor (group) and the within-subject factor (time). For
the endothelial differentiation parameters during endothelial colony forming assay differences between day 0
and day 28 were investigated, using paired t test or Wilcoxon’s rank test, as appropriate. Test selection was
based on evaluation of differences for normal distribution using the Shapiro-Wilk test. Results Static cultivation of
SC+F-composite induced significant improvements in stem cell proliferation as compared to controls. For dynamic
testing, microscopic analyses on a smooth engineered heart valve surface detected homogenous distribution of
stem cells. Ultrasonic analysis executed native-like valve performance. Applied CD133+ stem cells differentiated
into endothelial-like cells positive for CD31 and VEGF Receptor 2 and engrafted the valve. However, occasional
delamination was observed. Conclusion SC+F serves as an excellent autologous matrix for intra-operative tissueengineering of valve protheses promising optimal in-vivo integration. However, stability remains an issue.
References: Kaminski et al. (2011)
P22
Confidence Intervals for Difference of Correlated
Proportions Based on Paired and Unpaired Data
Jiajun Liu, Yue Shentu, Yabing Mai;
Merck Research Laboratories, Rahway, NJ, USA
In clinical trials, paired binary data often arise from crossover study design or pre-test/post- test comparisons.
Missing data due to drop- outs and other reasons may lead to incomplete paired binary data for a subgroup of
subjects. Interval estimation for the proportion difference can be problematic in these situations. In this article
we propose an extension of the method of variance of estimates recovery (MOVER) to construct confidence intervals (CIs) for the correlated proportion difference based on paired and unpaired data. Two sets of CI estimators,
one based on paired data, the other based on pooled paired and unpaired data, are utilized in the double-MOVER
procedure to construct the asymptotic CI. Extensive simulations show that the double-MOVER estimator performs
well under various degrees of missingness and correlations, even with small to moderate sample sizes. Two real
examples of clinical studies are used to demonstrate the proposed method.
P23
Change Point Identification with Adaptive Partitioning
in Isotonic Regression for Event-Time Data
Yong Ma, Yinglei Lai and John M. Lachin
Isotonic regression is a useful tool to investigate the relationship between a continuous covariate and a time-toevent outcome. The resulting non-parametric model is a monotonic step function and the steps can be viewed as
change points. However, when there are too many steps, over-fitting can occur and further reduction is desirable.
Here we propose adaptive partitioning to allow combination of small steps which do not differ greatly. In this
approach, a second step, the reducing step, is integrated into the usual monotonic step building by appropriate
statistical testing of the adjacent steps. Adjacent steps not significantly different at a pre-specified alpha level
are combined. We achieve this through a modified dynamic programming algorithm. Two popular parametric survival distributions, exponential and its extension Weibull, are implemented first. Then we explored a more robust
piecewise exponential distribution, which is less stringent in model assumptions and the model can potentially
be used in interval censored survival data. We apply this methodology to the Diabetes Control and Complication
Trial (DCCT) data set to study the relationship between HbA1C and the time to a severe hypoglycemia event. All
three approaches are used and the results compared. The models are very similar to each other and all suggest
a negative non- linear association between HbA1C and time to severe hypoglycemia. When the alpha level is set
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at a modest level (for example, 0.05), HbA1C at 6.2, 7.3 and 9.6 are identified as the potential change points
in its association with severe hypoglycemia.
P24
SAS Enterprise Guide and Graphics in Clinical Trials
Levent Bayman, Jon Yankey, Chris Coffey, William Clarke
Clinical Trials Statistical and Data Management Center, Department of Biostatistics, University of Iowa
Sometimes one picture is worth one thousand words, especially in the scientific community. Coding and managing SAS Graphics is difficult even for experienced SAS programmers. It is common to use other software to visually represent data even though the analyses were performed using SAS. Enterprise Guide, a newer facility within
SAS, has emerged as a remedy to these problems and creates automated and/or semi-automated graphical
displays via a point and click user interface with minimal or no coding required on the user’s part. More importantly, the produced graphics are of high quality and SAS statements that produced the graphs are automatically
generated. This added flexibility allows the user to modify the code if needed or to incorporate it into existing SAS
programs. This presentation will first investigate traditional SAS coding used to generate graphics. Second, stepby-step instructions will be provided to obtain the same (and even better) graphics by using Enterprise Guide’s
built-in graph facility. Finally, use of the Enterprise Guide applications in the University of Iowa Clinical Trials
Statistical and Data Management Center to accelerate producing graphics will be discussed.
P25
Methods for Calculating Variability of the Incremental Cost
Effectiveness Ratio in Cost-Effectiveness Studies
Nicole Foster, Michele Melia for the Pediatric Eye Disease Investigator Group (PEDIG)
Cost-effectiveness is an important method for gauging the impact of one health care strategy over another. Costeffectiveness is defined by the incremental cost-effectiveness ratio (ICER), that is, the difference in cost of the
two strategies divided by the difference in the effect of interest. Because the ICER is a ratio of two random variables, its sampling distribution cannot be easily derived, and quantification of the uncertainty in ICER estimates
can be problematic. Recommended procedures for calculation of a confidence interval on the ICER can only be
applied in the case where there is a significant difference in both cost and effect. The bootstrap method of sampling with replacement is a relatively straightforward and popular approach for estimating uncertainty in the ICER,
but it has been criticized for giving overly narrow confidence regions and involving many unstated assumptions.
The purpose of this presentation is to explore methods for calculating and displaying the variability of the ICER
using data from a recently completed clinical trial conducted by the Pediatric Eye Disease Investigator Group
(PEDIG) to illustrate the methods.
P26
Use of Historical Controls in Assessing Long-Term Zoster Vaccine Efficacy
Gary R. Johnson1, Jane H. Zhang1, Xiaoming Li2, Ivan S.F. Chan2, Michael
N. Oxman3, Myron J. Levin4, Kenneth E. Schmader5, Robert F. Betts6,
Vicki A. Morrison7, Constance Pachucki8, Paula W. Annunziato2
1VA
Cooperative Studies Program Coordinating Center, VA Connecticut Healthcare System, West Haven, CT, USA;
Merck, Sharp, & Dohme Corp., Whitehouse Station, NJ, USA; 3VA San Diego Healthcare System and University
of California, San Diego, CA, USA; 4University of Colorado Denver Health Sciences Center, Aurora, CO, USA;
5Durham VA Medical Center Geriatric Research, Education and Clinical Center and Duke University Medical
Centers, Durham, NC, USA; 6University of Rochester Medical Center, Rochester, NY, USA; 7Minneapolis VA
Medical Center and University of Minnesota, Minneapolis, MN, USA; 8Hines VA Medical Center, Hines, IL, USA
2
Background: The primary efficacy study for a vaccine to prevent herpes zoster (HZ) and its complications followed subjects for a median of 3.1 years post-vaccination and analyses of vaccine durability showed that the
vaccine was effective for four-years post-vaccination. Of interest is the assessment of how long the zoster vaccine
remains effective against HZ. Extended follow-up of study subjects was carried out in one substudy (3.3 to 7.8
years post-vaccination), but once placebo subjects were vaccinated, there was no longer a concurrent control
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group for direct estimation of vaccine efficacy.
Objectives: A method for determining historical control rates for long-term follow-up study was needed in order
to provide estimates of long-term efficacy for the three study outcomes: burden of illness due to HZ associated
pain or discomfort; incidence of HZ; and incidence of postherpetic neuralgia (PHN).
Methods: The extended follow-up protocol initially planned to use historical controls adjusted for increasing age
of the study population. However, the final analysis of the primary efficacy study showed that the incidence of
HZ in placebo recipients increased over the study duration even after the adjustment for increasing age. Poisson
regression methodology was used to develop and select models to estimate the age and calendar time effects.
Age and calendar time adjusted controls were then calculated by multiplying the model-based estimates times
the number of person-years of follow-up observed for each age year in the long-term follow-up of vaccinated subjects (4.7 to 11.6 years post-vaccination).
Results: Models selected for calculating the historical controls for the incidence of HZ included effects for both
age and study (calendar) time, while models for outcomes related to severity of HZ only included age. Methods
for assessing age and calendar time effects, for model selection, for the calculation of controls and for calculating vaccine effectiveness will be presented.
P27
Sampling Considerations for Genetic Associations in the
Environmental Polymorphisms Registry (epr)
Lindsey A. Ho and Patrick W. Crockett
SRA International, Inc., Durham, NC, USA
The Environmental Polymorphisms Registry (EPR) of the National Institute of Environmental Health Sciences
(NIEHS) was established as a “recruit-by-genotype” resource which houses a databank of DNA linked to participants who may be recontacted for phenotype information. The EPR is designed to screen for functionally significant polymorphisms by identifying individuals with shared genotypes at candidate genes and then recontacting
them for phenotype information that can be used for genetic association testing. We show that sufficient power
is obtained by equally sampling few numbers of individuals per genotype group. For example, assuming a 25%
change in TNF-alpha release between each genotype group (and a standard deviation of 200 units), we calculated
89% power by including a total of 12 subjects (4 per genotype group). In contrast, if we randomly sampled subjects and measured both their continuous phenotypes and genotypes using the same distributional assumptions
and mode-of-inheritance, a rare susceptibility allele of 2% would require 166 subjects to achieve similar power, a
substantial increase in the number of subjects as compared to the EPR approach. This suggests that contrasting
equal numbers of homozygotes dramatically improves power for less common alleles as opposed to sampling
genotypes at random. We note that there is no need to include heterozygotes if investigators seek only to test
the presence of an effect, rather than including this group to distinguish among inheritance models.
P28
Repeat Participants in Clinical Research: an Overlooked Sub-Population?
Evidence From 20 Years of Inner City Asthma Consortium (icac) Studies
Miguel Villarreal, Agustin Calatroni, Jeremy Wildfire, Cindy Visness, Herman Mitchell
Rho, Inc., Chapel Hill, NC, USA
When inclusion/exclusion criteria are considered during protocol development for a clinical trial, previous study
experience is routinely considered exclusionary only if a previous drug or intervention is likely to have a direct
effect on the intervention under study. However, patients who have participated previously in a research study
may respond differently to an intervention compared to new participants, even when the interventions are not
similar. We examined data from the National Cooperative Inner-City Asthma Study (NCICAS) and the Inner-City
Anti-IgE Therapy for Asthma (ICATA) Study to assess the impact of previous research experience on the response
to the intervention.
The NCICAS Phase II study enrolled 1033 participants, 457 (44%) of whom were recruited from NCICAS Phase I,
a 12-month observational study designed to identify risk factors for asthma morbidity. The ICATA Study enrolled
419 participants, 39 (9%) of whom were previously enrolled in the Asthma Control Evaluation (ACE) Study, a trial
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that used measurement of exhaled nitric oxide as an adjunct to clinical care in the intervention group. In both
studies, the intervention was more effective in the study-naïve population compared to the study-experienced
population. In NCICAS II, there was a strong intervention effect for the study-naïve population and the experienceby-intervention interaction was statistically significant. The results of ICATA were consistent with NCICAS and
showed a significant decrease in asthma symptom days for the study-naïve participants in contrast to studyexperienced participants, but the interaction term was non-significant.
In both NCICAS and ICATA, study-naïve participants responded more favorably to the intervention than studyexperienced participants. These study-experienced participants began the second study with a lower level of
symptoms, which may reflect better asthma management learned during the previous study. Researchers should
consider the effect of prior study experience even when it is not directly related to the current intervention.
P29
Results of Remote Monitoring Techniques for MultiCenter Ophthalmic Imaging Trials
Dana AH Keane
Optos, Inc. Marborough, MA, USA
Background: Imaging in clinical trials has become more important than ever to help predict treatment outcomes,
monitor disease progress and document treatment effectiveness. With the ever-present need for shorter, more
cost effective trials quality assurance in imaging is an essential component of ensuring trial success. It is generally recognized that the implementation of digital imaging systems and cloud computing may be improve remote
imaging methods, but data is limited.
Purpose: To report on remote monitoring techniques use to ensure protocol adherence and high image quality in
a study where quantification of small peripheral retinal changes was the key endpoint.
Methods: This trial is an ancillary imaging study to a large multi-center randomized interventional trial for Agerelated Macular Degeneration. Images were obtained using a widefield imaging system in which peripheral
changes were to be observed and quantified. The primary aim of monitoring was to ensure each site was obtaining full field images taken in the appropriate sequence for evaluation. Images were submitted remotely to the
reading center for evaluation and mirrored to the sponsor for monitoring purposes. Images were reviewed by the
sponsor on a weekly basis and feedback to the site occurred immediately. If issues arose with image quality a
monitor was dispatched to the site for a traditional site visit.
Results: Trial is ongoing however the average amount of retakes requested has been reduced by 30% with a
reduction in site visits by 50%. Prior trials relied on on-site monitoring visits in 8 week intervals. Monitors would
review study image databases and request reimaging as well as re-train imagers if necessary. This often led to
delays in assessing quality issues and required more recall visits for reimaging. Monitoring in this trial allowed
for more swift feedback to be given to sites thus reducing reimaging requests and technical failures.
P30
The Use of Adult Learning Theory in Critical Care Clinical Trials
Site Initiation Meetings Improves Confidence in New Research
Skills and Techniques and May Enhance Study Conduct.
Elizabeth A. Sweetman, Philippa T. Heighes, Gordon S. Doig
Royal North Shore Hospital, Intensive Care Unit, Sydney, NSW 2065, Australia
Introduction: Excessive protocol violations (PVs), defined as preventable mistakes in study conduct, may result
in patient harm and may dilute statistical power.
PVs are more likely to occur early during trial conduct, while research staff are still ‘learning’ the trial protocol.
Incorporation of interactive workshops into start-up meetings addresses the needs of research staff as adult
learners and may lead to improved study conduct.
Purpose: To evaluate the attendees responses towards interactive workshops as part of clinical trial start-up
meetings.
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Methods: In 2010 we commenced two novel multi- centre clinical trials (Study A and Study B) at 29 sites across
Australia and New Zealand. We held five sequential start-up meetings over seven months, each attended by
research staff from three to five study sites.
Didactic lectures were followed by interactive group workshops to reinforce new skills and study processes. Both
Study A and Study B introduced new study processes however only Study B taught a ‘new skill’, which involved a
specific technique for measuring QT intervals. At the final start-up meeting for each study, attendees evaluated
the interactive workshops.
Results: Study A and Study B: New Study Processes When asked whether the interactive workshops were useful
for reinforcing the learning of new study processes, 16/16 (100%) participants responded YES.
Study B: New Skills When asked whether the interactive workshops improved confidence with new skills, 8/8
(100%) participants responded YES. When asked whether the interactive workshops should be held in future
meetings if new skills were being taught, 10/10 (100%) participants responded YES.
Conclusions: Interactive workshops provide a protected learning environment for research staff learn new trial
protocols prior to enrolling their first patient. Attendees reported improved confidence in the mastery of new
skills, which may translate to improved study conduct. Additional research is required in this field.
P31
Demographic and Health Factors Associated With Enrollment in PostTrial Studies: the Women’s Health Initiative Hormone Therapy Trials
Sarah A. Gaussoin, Mark A. Espeland, Mary Pettinger, Karen L. Falkner,
Sally A. Shumaker, Marian Limacher, Fridtjof Thomas, Kathryn E. Weaver,
Marcia L. Stefanick, Cynthia McQuellon, Julie R. Hunt, Karen C. Johnson
Wake Forest School of Medicine, Winston-Salem, NC, USA
After clinical trials end, continued follow-up of the assembled cohort is often pursued for additional research.
Factors influencing participants’ decisions to consent to additional follow-up and how these shape post-trial
cohorts have not been broadly studied. The WHI Hormone Therapy (WHI HT) clinical trials were designed to
assess the impact of two regimens of postmenopausal hormone therapies compared to placebo. Postmenopausal
women, 50-79 years of age at initial screening, were eligible for participation. We examine how two re- enrollment campaigns, occurring in 2004-2005 and 2009-2010, and the passage of time altered broad features of
the post-trial cohorts compared with the original WHI cohort, which was recruited in 1993-1998. Associations
that markers of socio- demography, health, lifestyle and on-trial experiences had with re-enrollment were examined and the characteristics of successive post-trial cohorts were contrasted with those of the original enrollees.
The post-trial enrollment campaigns re- enrolled 81.1% and 82.5% of available women, respectively. Women
who re- enrolled tended to have better health characteristics than those not re-enrolled. Compared to women
of comparable age in the original cohort, women retained for the second post-trial follow-up were less likely to
have a history of cardiovascular disease [odds ratio=0.36: 95% confidence interval: 0.32,0.41], hypertension
[0.57: 0.54,0.61], diabetes [0.59: 0.54,0.61], or measured cognitive deficit [0.40: 0.26,0.64]. These women
were more likely to have graduated from high school [1.72: 1.54,1.92] and to have participated in other WHI
trials [1.76: 1.66,1.87]. Although we have examined a single study and cannot clearly generalize how our findings might apply to other cohorts and protocols, these methods may be used to estimate re- enrollment in other
studies. Post-trial enrollment can be successful, however the characteristics of the resulting cohort may differ
substantially from the originally assembled cohort and it may be important to collect predictors of differential
re-enrollment during the original trial to facilitate re-enrollment.
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P32
Impacting a Clinical Trial’s Success by Integrating Regulations,
Standards and Guidelines Into Organizational Culture
Jan Hickey, Mike Sather, Stanley Johnson, Julia Vertrees, Kathy Boardman
Department of Veterans Affairs Cooperative Studies Program Clinical Research
Pharmacy Coordinating Center, Albuquerque, NM, USA
The Department of Veterans Affairs Cooperative Studies Program (CSP) Clinical Research Pharmacy Coordinating
Center (Center) is responsible for clinical supplies used in multicenter clinical trials conducted by the CSP.
Clinical supplies lay at the core of drug and device trials. They must meet stringent quality standards to ensure
patient safety. The integrity of the clinical supplies and the controls on their processing must provide a guarantee
that the results of the trial, whether positive or negative, cannot be questioned.
The Center integrates quality regulations, standards and guidelines into all their processes to ensure the integrity
of not only the clinical supplies, but all their processes. These regulations, standards and guidelines include:
•current Good Manufacturing Practice Regulation 21 CFR 210 and 211 for drugs, •Quality System Regulation,
21CFR Part 820 for medical devices, •Quality Management System Standard, ISO 9001:2008, •Primary
Packaging Materials for Medicinal Products Standard, ISO 15378:2007, • Organizational Quality processes,
Malcolm Baldrige Criteria, and •ICH guidelines for Stability testing and other processes.
This poster demonstrates how quality standards and guidelines apply to all processes associated with the clinical supply chain including the typical cGMP regulated product development, manufacturing, laboratory testing,
packaging, labeling, distribution, corrective and preventative actions, training and document controls.
But equally important, in addition to using regulations, standards, and guidelines to control the supply chain processes, they also support administrative processes including management responsibilities, planning and design,
pharmaceutical project management, budget and finance, treatment assignment, continuous improvement, document control, and study closeout.
The organizational model for the Center’s quality management system melds industry standards, quality models
and federal regulations into an effective infrastructure, resulting in a high-performing organization that designs
and controls all processes to assure the successful conduct of large and small scale clinical trials from design
to closeout.
P33
Abstract Withdrawn
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P34
Resolving the Conflict: Sponsor-Investigators and the
Ethical Concern Behind the Consent Process
Melissa Brown, Johanna Sanchez, Dalah Mason, Elizabeth Asztalos
Sunnybrook Health Sciences Centre is the sponsoring institution and lead site for several multi-centred clinical trials. As such, investigator-initiated trials are conducted by clinical research teams generally comprised of
the Sponsor-Investigator, Site Principal Investigator (PI), and Research Coordinator. As a policy at Sunnybrook,
the initial approach for participation in a trial must be made through a member of a patient’s circle of care.
Because of their access to the patients, their knowledge of the question and commitment to the study, SponsorInvestigators that are clinicians are most suitable for the approach phase of the recruitment process. However,
due to ethical standards, their exclusion from the consent process during recruitment is imperative.
The requirements for autonomy and informed consent in research are competence, information, understanding
and voluntariness. Due to factors of trust and dependency in a physician-patient relationship, the imposition of
undue influence is commonly an area of ethical concern. To avoid this, the inclusion of a Site PI and Research
Coordinator to the research team has become vital.
As a task delegated by the Sponsor- Investigator, the Site PI assumes responsibility for the oversight of the
consent process, which establishes a chain of command that results in the Coordinator reporting consent to the
Site PI instead of the Sponsor-Investigator. This order alters the physician-patient relationship and eliminates
any obligation the Coordinator may have to the Sponsor-Investigator, allowing an unbiased approach to potential
participants.
The implementation of these precautionary measures assists in building trust between the Coordinator and each
participant, which leads to increased study compliance and decreased rates of attrition. Furthermore, they allow
the Sponsor-Investigator to continuously drive the study with enthusiasm and commitment without ethical compromise during the consent process.
P35
The Quality of Medical Record Abstraction in a MultiCenter Study: the Importance of Training
Nancy Payte, Brenda Brewer, Kathy Clingan, Jennifer Rosenbaum
Westat, Rockville, MD, USA
The National Lung Screening Trial (NLST) is a randomized controlled trial, funded by the National Cancer Institute,
to determine whether screening with low-dose helical computed tomography reduces lung cancer mortality relative to screening with conventional chest x- ray in persons at elevated risk of lung cancer. It was comprised of
the Lung Screening Study (LSS) and the American College of Radiology Imaging Network (ACRIN). Lung cancer
diagnosis, a critical study outcome, relied on data abstracted from medical records. The Coordinating Center (CC)
for the LSS was responsible for training and monitoring abstraction at 10 sites.
A medical record abstractor (MRA) training program was developed and implemented by the CC to include centralized initial training, refresher training at annual meetings, quarterly conference calls and individual training
as needed. Training sessions focused on comprehension of specifications and proper completion of MRA forms,
and emphasized the responsibility of the abstractor in collecting quality data. Effectiveness of training was
assessed during the on-going QA process: central re-abstraction of all primary lung cancer cases and a random
sample of positive screens without a lung cancer diagnosis. Over 2000 sets of medical records were reviewed.
MRA QA reports monitoring 13 key data elements were compiled quarterly, depicting the number and type of
errors. Findings from the QA reports changed during the study. Overall adherence to abstraction specifications
and reporting of diagnostic procedures improved over time.
In studies requiring medical record abstraction, it is vital to develop thorough standardized training approaches
and to engage in continual abstraction training and monitoring. The use of quarterly QA reports enabled us to
focus training efforts on problem areas and to identify individual MRAs and/or sites requiring additional training.
We will demonstrate how our on-going training program was an integral part of the MRA process.
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P36
Outcomes Adjudication - the Preparation Process
Ainy Zahid, Trinh Hoac, Johanna Sanchez, Elizabeth Asztalos Claire Hahnhaussen, Joanne
Kirton, Sue Ross, Peter von Dadelszen, and Laura A. Magee for the CHIPS Study Group
Sunnybrook Research Institute, Toronto, Ontario, Canada
The CHIPS Trial (Control of Hypertension in Pregnancy Study) is an international multi-centre randomised controlled trial recruiting 1028 women from 100 centres internationally. CHIPS aims to determine whether ‘less
tight’ or ‘tight’ control of non-proteinuric hypertension will decrease the likelihood of pregnancy loss or ‘high level’
neonatal care, without increasing serious complications for the mother. A committee of clinicians (representing
obstetrics, medicine, and neonatology), masked to treatment, convenes quarterly to review perinatal and maternal outcomes and adjudicate whether or not the outcomes have occurred. As the Trial expects approximately
30% of babies and 2% of mothers to have a serious complications, an efficient adjudication preparation process
is required.
To accurately adjudicate the outcomes, it is necessary to review all reported cases with fetal, neonatal, and/or
maternal complications to ensure that case report forms (CRF) have been accurately completed, and the hospital
documents received. These cases are assessed in a preliminary review to confirm they meet the relevant trial outcome definition. The following are resolved prior to adjudication: CRF inaccuracies, missing hospital documents,
discrepancies between the CRFs and hospital records, and translation of international hospital documents. At the
adjudication meeting, all data forms for each case are reviewed along with the corresponding hospital records.
Due to the high volume of outcomes and various steps required for preparation, a Microsoft Access tracking
system was developed. Cases requiring adjudication are added to the tracking system, and issues requiring clarifications are recorded. Lists are generated to identify outstanding issues, which are resolved by corresponding
with the centre, and subsequently tracked to monitor case progess. Once all issues have been resolved, case
identifiers are blocked, an identifying code is assigned, and cases are mailed to the adjudication committee
members. The tracking system allows for systematic collection of information resulting in an efficient adjudication preparation process.
P37
Transitioning an Adolescent Cohort From a Randomized Clinical
Trial (today) to a Post-Intervention Follow-Up Study (today2)
Marisa Payan1, Trang Pham1, Brian Burke1, Nancy Chang2, Kristin
Porter3, Jill Schanuel4, Aimee Wauters5, TODAY Study Group
1The
George Washington University, Rockville, MD, USA; 2Childrens Hospital of Los Angeles, Los Angeles, CA,
USA; 3Children’s Hospital of Pittsburgh, Pittsburgh, PA, USA; 4Oklahoma University Health Sciences Center,
Oklahoma City, OK, USA; 5University of Texas Health Sciences Center - San Antonio, San Antonio, TX, USA
Treatment Options for type 2 Diabetes in Adolescents and Youth (TODAY) was a multi- site randomized clinical
trial comparing three treatment arms on time to treatment failure, funded by the National Institute of Diabetes
and Digestive and Kidney Disease (NIDDK) of the National Institutes of Health. Participants were randomized
between the ages of 10-17 and diagnosed with type 2 diabetes (T2D) less than 2 years at baseline. As the first
large national study of this vulnerable population of youth diagnosed with T2D, it was considered important to
continue to follow this unique, well-characterized, ethnically diverse cohort in order to understand the persistence
of effects of the treatment regimens used in TODAY and the development of vascular complications. The youth
are now participating in a post- intervention, prospective follow-up study called TODAY2.
While other studies have undergone the transition from a clinical trial of blinded experimental intervention regimens to a post- intervention follow-up study, TODAY provides insights into procedures and strategies specific to
this cohort. We will describe our experience and impart ‘lessons learned’, which have resulted in several important study-wide changes intended to increase compliance during the follow-up period. We encountered challenges
due to major life changes occurring in participants shifting from adolescence to young adulthood. Further, we
were providing standard practice patient care and management in TODAY2, which meant a switch from blinded
pill packets to open-label bottled pills and from an over-encapsulated pill size (described as a ‘horse pill’) to a
smaller tablet. These changes had ramifications for encouraging and tracking study drug adherence at the start
of TODAY2. We make recommendations and suggestions for other study groups facing a similar situation.
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P38
Adverse Event Reporting for Hematopoietic Stem Cell Transplant Studies
Mary Crann BSN, Adam M. Mendizabal MS, Iris Gersten MS, Shelly L. Carter ScD
The Blood and Marrow Transplant Clinical Trials Network (BMT CTN), sponsored by the NHLBI and NCI, was established in 2001 to conduct multi-institutional clinical trials in hematopoietic stem cell transplantation (HSCT).
The Data and Coordinating Center (DCC) is responsible for data collection, review, monitoring, and reporting of
adverse events (AE). Significant regimen-related adverse events are anticipated in this patient population that
warrants a systematic approach to reporting adverse events.
The BMT CTN utilizes the AdvantageEDCSM electronic data management system to capture unexpected grades
3-5 AEs in six case report forms (CRFs): AE1-Initial Report, AE2-Summary, AE3-Therapy/Concomitant Medications,
AE4-Laboratory/Diagnostics, AE5- PI Review, and AE6-Medical Monitor Review. AEs are graded according to the
National Cancer Institute’s Common Terminology Criteria for Adverse Events (CTCAE). Grades 3-5 AEs not listed
in the protocol, informed consent, or drug label are determined to be “Unexpected” and are reported expeditiously regardless of attribution. Expected adverse events including protocol- specific toxicities are captured on
calendar and event driven CRFs. Examples of expected data collected on these CRFs include infectious complications, graft-versus-host disease, relapse, readmission, graft failure and other protocol-specific events.
AdvantageEDCSM generates an automated e- mail notification when an unexpected grade 3- 5 AE has been
entered. The AE coordinator notifies the DCC Medical Monitor who makes a determination of the expectedness
and grade. The AE coordinator is responsible for managing the process including queries to the transplant center
and filing reports to the NHLBI Project Officer and the FDA in compliance with reporting timeframes.
The BMT CTN AE process was developed to manage unexpected grades 3-5 AEs without burdening the system
with expected events that are common among HSCT clinical trials. The AE process is coordinated by the DCC
and requires constant vigilance to ensure events are reported, processed, and reviewed expeditiously with the
objective of protecting the safety of study participants.
P39
Neuronext: Developing Infrastructure for Phase 2
Clinical Trials in Neurological Disorders
Dixie Ecklund, Marianne Kearney, Chris Coffey, Merit Cudkowicz,
Elizabeth McNeil, Petra Kaufmann, Walter Koroshetz
University of Iowa, Massachusetts General Hospital, National Institute of Neurological Disorders and Stroke
The need to independently develop infrastructure for each trial is one of the impediments to efficiently implementing phase 2 trials. To improve efficiencies, the National Institute of Neurological Disorders and Stroke (NINDS)
recently initiated the Network for Excellence in Neuroscience Clinical Trials (NeuroNEXT). The goals of NeuroNEXT
are to lower barriers for individuals to bring good ideas forward in adult and pediatric neurological disorders,
and to provide a flexible and accessible infrastructure to facilitate the development and deployment of phase
2 clinical trials and biomarker studies. To accomplish this goal, a Data Coordinating Center (DCC) is funded at
the University of Iowa and a Clinical Coordinating Center (CCC) at Massachusetts General Hospital (MGH) and
25 clinical sites are funded throughout the United States. The first year of the project is aimed at establishing
Standard Operating Procedures between the DCC and the CCC, Master Trial Agreements with each site to facilitate contractual requirements, and Reliance Agreements between the Central Institutional Review Board (IRB) at
MGH and the IRBs at each site to facilitate IRB review. In addition, there are Protocol Working Groups (PWGs)
that provide CCC and DCC assistance to academic, industry and advocacy partners in order to design and finalize
robust protocols and grant applications. Data entry systems are being developed using the NINDS Common Data
Elements to harmonize data sets at the end of each trial. The NeuroNEXT will develop and implement at least 7
clinical trials over the next 7 years, with at least one trial expected to start within the first year. Metrics on site
performance, protocol development, and success of implementation are being collected to examine efficiencies
and identify barriers. This innovative approach to improving efficiencies in phase 2 clinical trials may lead to more
rapid development of therapies for adults and children with neurological disorders.
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P40
Serious Unexpected Events in an Obstetric Clinical Trial – Definitional Challenges
Laura A. Magee1, Jennifer M Menzies1, Sue Ross3, Johanna Sanchez2,
Elizabeth Asztalos2, Joanne Kirton1, Trinh Hoac2, Ainy Zahid2, Claire
Hahnhaussen1, and Peter von Dadelszen1 for the CHIPS Study Group
1The
University of British Columbia, Vancouver, British Columbia, Canada; 2Sunnybrook
Health Sciences Centre, The Centre for Mother, Infant, and Child Research, Toronto,
Ontario, Canada; 3University of Calgary, Calgary, Alberta, Canada
The concept of serious unexpected events (SUEs) is rooted in drug research in which unintended effects of medication (e.g., skin rash) must be identified. Although routine reporting of SUEs is an essential part of conducting
a clinical trial, how to define a SUE in a pragmatic trial of high risk women is problematic.
The CHIPS Trial (Control of Hypertension In Pregnancy Study) is a multicentre randomised controlled trial recruiting 1028 women in 100 centres internationally (2008-14). CHIPS aims to determine whether ‘less tight’ control
[target diastolic blood pressure (dBP) 100mmHg] or ‘tight’ control [target dBP 85mmHg] of non-proteinuric hypertension in pregnancy is better for the baby (primary outcome: pregnancy loss or high level neonatal care for >
48hr) without increasing risk to the mother.
Women eligible for CHIPS are high risk from perinatal and maternal perspectives, such as serious neonatal
complications (16%), admission to high level neonatal care (30%), pre-eclampsia (35%), or serious maternal
complications (2-3%). We needed to further develop our method of SUE review to prevent anticipated outcomes
from being sent to our Data Safety Monitoring Board (DSMB) for review as SUEs.
In CHIPS, reported SUEs are reviewed by the Working Group (WG) to determine both the urgency of further review
and what supporting documents are required. The Outcomes Adjudication Committee (OAC) reviews each SUE
to determine whether the event is a pre- specified trial outcome or a ‘true’ SUE. This decision is reviewed by
the Steering Committee (SC). A summary report is submitted to the DSMB at the interim and final analyses or
immediately, as decided by the WG, OAC, and/or SC.
To date in CHIPS, three SUEs have been reported, all of which were determined to be pre-specified outcomes
and will be reviewed by the DSMB at the time of the first interim analysis.
P41
Planning for the End: the Type 1 Diabetes Genetics Consortium (t1dgc)
Letitia H. Perdue1, June J. Pierce1, William M. Brown1, Hoa Teuschler1, Beena Akolkar2
1Division
of Public Health Sciences, Wake Forest School of Medicine, WinstonSalem, NC, USA; 2Division of Diabetes, Endocrinology and Metabolic Diseases, National
Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA
The T1DGC was an international effort to identify genes that determine risk of type 1 diabetes. The Consortium
created a resource of 2,836 affected sibling pair families as well as 493 trios, 830 cases and 968 controls
worldwide. Data and sample collection was conducted in four networks (Asia-Pacific, European, North American
and United Kingdom) from January 2004 - January 2010, with support from a Coordinating Center for various
activities. While implementing standardized data collection for this international study presented many challenges, study closure proved to be as formidable. Disassembling this complex infrastructure (composed of 214
clinics in 34 countries, four Network Centers and 17 laboratories) while preparing all data and samples for
transfer to the NIDDK Central Repository proved as difficult and required as much effort as initiating the study.
At the time that we started study closure activities, there were no established guidelines or experience to direct
our actions or identify potential difficulties. Study close out was staggered, beginning in October 2006 and concluding in December 2011. We developed a clinic close-out data entry form, delineating key elements required
for closure. Additionally, comprehensive checklists of closure tasks for laboratories and Network Centers were
developed and utilized. Finally, the Coordinating Center held a meeting with the NIDDK Central Repository to
outline the data, samples and study documentation to be deposited. By clearly defining close-out tasks, providing timelines, and performing close-out site visits and/or conference calls, staff at each facility can understand
their responsibilities and ensure that all items are completed in this lengthy and complex process. Implementing
these steps permits an orderly and efficient study closure and should be undertaken as soon as data collection
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has been initiated. We will present our procedures and solutions to problems encountered to assist other studies in the close-out process.
P42
Risk Management of Non-CTIMP Trials: Focus on Complex Intervention Trials
Liz Graham, Shamaila Anwar, Maria Bryant, Suzanne Hartley
Clinical Trials of Investigational Medicinal Products (CTIMPs) are regulated in the UK via the Medicines for
Human Use (Clinical Trials) Regulations. This is implemented via a) Research Ethics Committee (REC) review, b)
Research Management & Governance review by the NIHR Clinical Research Networks followed by c) local Trust
R&D department review, and d) Competent Authority (CA) review.
Non-CTIMPs are approved via the same routes (excluding CA review). However, these studies are not governed
by the Clinical Trial Regulations; instead they are conducted in line with the UK Department of Health’s Research
Governance Framework, and in accordance with the Medical Research Council’s Good Clinical Practice guidelines. Robust processes to ensure ethical and governance compliance are implemented but we have observed
that low-risk non-CTIMP trials are subject to high levels of scrutiny by RECs and R&D departments, which is not
necessarily commensurate with the risk to participants. This can detract from addressing key logistical issues
associated with trial implementation (e.g. clinician training, optimising complex data collection processes from
many sources), and can considerably extend the set-up phase of such trials, delay the start of recruitment, and
even discourage site and patient participation. It is apparent that the measurement of risk in non-CTIMP trials
needs to include the risk to the participant per se, but also the complexity of trial conduct (which impacts on
participant risk if processes for implementing the trial are not thoroughly planned).
We will discuss the risk to the participant and the complexity of trial conduct identified in 3 complex intervention
trials co-ordinated by the CTRU, and present the impact this had on the set-up and implementation of each trial.
We will present a risk-based approach for review and implementation of complex intervention trials, based on the
type of intervention, participant, patient pathways and outcome measures to be used.
P43
Strategies to Maximise Response Rates to Postal Questionnaires in
Pragmatic Trials Involving Elderly Stroke Patients and Their Caregivers
Shamaila Anwar, Amanda Farrin, Ivana Holloway
Response rates of patient reported outcome measures administered postally influence robustness of trial results.
We aim to present ways in which postal response rates can be maximised in pragmatic trials using experience
gained in the implementation of postal follow-up process for two large multi- centre randomised controlled trials
within stroke - Training Caregivers after Stroke (TRACS) and Longer Term Stroke Care (LoTS care) co-ordinated by
the University of Leeds’ Clinical Trials Research Unit.
Both trials obtain their primary outcome measures via patient self-completed measures administered postally.
Follow-up procedures include a mixture of postal and telephone reminders, typically undertaken at two weekly
intervals. Response rates are carefully monitored and, where necessary, amendments to the process are made
and accounted for in later trials. For example in TRACS, following initial monitoring of data to enhance completeness, the team instigated the collection of the primary endpoint via a telephone interview for patients who did not
return questionnaires despite earlier standard postal and telephone reminders. This process was adopted much
earlier in the subsequent LoTS care trial. In addition, after the publication of a systematic review on methods to
increase response rates, trial pens were enclosed with questionnaire packs. Lessons from LoTS care and TRACS
led to implementation of strategies to enhance compliance in subsequent trials (e.g. sending questionnaires to
participants in advance of a face-to-face interview in participants’ homes)
Response rates during specific postal and telephone reminder stages will be reported as well as the characteristics (such as age, gender, level of anxiety and depression) of participants responding at the different stages.
Many aspects need consideration when developing follow-up response strategies. Above all, strategies need to
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be easily adaptable, closely monitored from the outset and any lessons learnt disseminated.
P44
Pregnant Women’s Views About Participation in Trials – a Qualitative Study.
Katrien Oude Rengerink1, Sabine Logtenberg2, Ben Willem Mol1
1
Academic Medical Center, Department of Obstetrics and Gynaecology, Amsterdam, the Netherlands;
2Onze Lieve Vrouwen Gasthuis, Obstetrics and Gynaecology, Amsterdam, the Netherlands
OBJECTIVE Patient recruitment in trials often takes longer than expected. This is costly and if the sample size
remains insufficient it might lead to indecisive conclusions for practice. The field of obstetrics is unique in the
way that there are two patients: the mother and her baby. We aimed to identify reasons why women participated
or declined participation in an RCT during or shortly after pregnancy.
DESIGN We performed a qualitative study with semi-structured interviews in women who were asked to participate in a RCT in obstetrics. We randomly selected both women who consented and those who did not for one of
a set of 7 different RCT’s. Transcripts of the interviews were analyzed anonymously using a constant-comparative
approach. Two researchers independently identified barriers and facilitators for participation. Interviews were
continued until saturation was reached.
RESULTS Of 22 women approached, 20 (90%) consented to be interviewed. Respondents varied by educational
level, ethnicity, geographical area, age and parity. The main motivation for trial participation was either to contribute to research, as the women were convinced of it’s importance (50%) and/or preference for a treatment arm
not available outside the trial (60%). Key barriers for participation in non-consenters were a negative association
with the intervention (100%) and/or with randomization (45%). Fear and uncertainty, probably due to unfamiliarity
with research and the feeling of being inappropriate because of unique personal characteristics, also played a
role. Stress and doubt about the decision were present in both groups.
CONCLUSION Trial participation is a tough decision for most women. The final choice about participation is made
intuitively, but will be influenced positively if women are well informed about the importance of research in general
and the specific trial in particular. A personal, complete, well-timed dialogue may facilitate to make a balanced
decision and improve trial participation.
P45
Good Clinical Practice Compliance in a Surgical
Trial - Results of Monitoring and Audit
Inga Rossion, Thorsten Löffler, Markus K. Diener, Anna-Lena Gamer,
Hans-Heinrich Otter, Oana Brosteanu, Jürgen Weitz
Study Center of the German Surgical Society Dept. of General, Visceral and
Transplantation Surgery, University of Heidelberg, Heidelberg, Germany
Good clinical practice (GCP) compliance is required for state of the art quality in clinical trials (CT). For HASTA
trial (Hand suture vs stapling for closure of loop ileostomy) most participating centers are non-university institutions with little experience in CT. Therefore, we established a quality assurance system with on site monitoring
visits and audits in all 27 centers. Based on monitoring reports, GCP violations are analyzed and their impact on
patient safety and data quality is assessed.
Preparation for HASTA included a 2-day investigator meeting with surgical training and individual on site initiation
visits. During recruitment 48 regular on site monitoring visits were conducted. Close out visits and independent
audits are currently carried out and will be finished in February 2012.
Most GCP violations concerned patient informed consent (IC), although no IC was missing. 16 findings were
rated major, 42 minor. Safety: 27 events were identified requiring serious adverse event reporting according to
protocol. Primary endpoint needed to be corrected in 6 cases following monitoring findings. Violation of eligibility criteria were reported 4 times only. Further violations were regarding performance of trial intervention (wrong
treatment group, procedure not performed according to protocol) and time window for follow-up visits.
Quantitative and qualitative results of monitoring findings will be presented and compared to findings discovered
120
by on site audits. As on site monitoring is not routinely established for investigator initiated surgical trials, relevance of monitoring and auditing for conduct of HASTA trial and validity of trial data will be discussed.
Like most clinical research studies, minority enrollment rates are low in the EPR, particularly for African American
males. In addition, African Americans have higher attrition rates compared with Caucasians. Therefore, in the
EPR, we have employed special methods for recruiting and retaining minority subjects with varying levels of
success. In this report, we will describe these methods, the lessons learned, and strategies used to improve
minority recruitment and retention. These include: relationship-building with key stakeholders; capitalizing on
personal and professional contacts; utilizing community “champions” and leaders; and targeting health-related
and faith-based organizations/events. Success rates for the various strategies are presented by sex, age, race,
and ethnicity.
P46
Parental Perception of a Contract Improves Adherence in Longitudinal
Randomized Controlled Trials of Disease Prevention in Early Life
Helen Fisher1,2, Dr Annette Boaz1, Dr Christopher McKevitt1, Professor Gideon Lack2
1
Health and Social Care Research, Kings College London, London, UK;
Asthma Allergy and Lung Biology, Kings College London, London, UK.
2
Objectives: During participation in a Randomized Controlled Trial (RCT) adherence to the intervention and to other
protocol requirements (e.g. visit attendance and completion of questionnaires) is essential for the production
scientifically robust and clinically meaningful outcomes. Yet little is known about the issues that affect adherence
during trial participation. This study aimed to explore the factors that influenced adherence to research procedures by parents who were invited to enrol their infants in longitudinal RCTs aimed at allergic disease prevention.
Methods: Two RCTs of an intervention to prevent food allergy in infants were used as case studies for this
research. Data were collected using ethnographic methods: participant observation (130 hours) was carried out
on the clinical trials unit; staff (n=26) who worked on the RCT and parents (n=55) who considered participation
or had participated in the RCT took part in semi-structured interviews; and documents were gathered. Data were
analysed thematically.
Results: Parents appeared to commit to a contract in their participation in the studies. The potential to gain
direct benefit from participation improved adherence to the protocol. However even when no personal benefit was
obtained, parents put considerable effort into adhering. This reflected their beliefs in the worth of the RCT and
the importance they placed on fulfilling the perceived contract. Staff took proactive and reactive approaches to
improving adherence. This involved ‘negotiating’ adherence with colleagues and parents to balance manageable
participation with achieving scientifically robust outcomes.
Conclusion: Many factors are important in achieving optimal adherence to the intervention and other protocol
requirements. Parental and staff willingness to invest considerable time and resources is essential to achieving
optimal adherence. The results suggest that staff and parents considered that research participation represented
a ‘contract.’ Maintaining an open dialogue regarding the nature of this contract helps to promote adherence in
longitudinal RCTs.
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P47
Factors That Influence Recruitment to Longitudinal Randomized
Controlled Trials of Disease Prevention in Early Life
Helen Fisher1,2, Annette Boaz1, Christopher McKevitt1, Gideon Lack2
1Health
and Social Care Research, Kings College London, London, UK;
Allergy and Lung Biology, Kings College London, London, UK
2Asthma,
Objectives: Successful recruitment to clinical trials is essential for scientifically and clinically robust findings.
Additionally problems with accrual results in increased trial costs and the inefficient use of resources. Yet little
is known about effective recruitment to pediatric studies. This study aimed to explore the factors that influenced
recruitment to non-therapeutic, pediatric longitudinal randomized controlled trials (RCTs). Methods: Two RCTs
of an intervention to prevent food allergy in infants were used as case studies for this research. Data were collected using ethnographic methods: participant observation (130 hours) was carried out on the clinical trials unit;
staff (n=26) who worked on the RCTs and parents (n=55) who considered participation or had participated in
the RCT took part in semi-structured interviews; and documents were gathered. Data were analyzed thematically.
Results: The potential value of participation had a substantial influence on recruitment. Parents considered possible benefits for their child and the scientific worth and integrity of the RCT before agreeing to participate. The
possibility that participation would be mutually beneficial was relevant to parents and staff. The ability to manage
the demands of participation was also important; parents delayed making a decision until they considered they
could cope. The potential for participation to cause harm had a substantial influence; fathers were often more
concerned about harm and placed less importance on the scientific worth of the study than mothers. Conclusion:
Recruitment to non-therapeutic longitudinal RCTs in early childhood is influenced by complex inter-related factors.
Holding detailed discussions with parents regarding the scientific value of the studies and the support that can
be offered to improve the manageability of participation may help to promote recruitment. Mothers and fathers
often appear to have different opinions about the potential for harm and benefit; holding discussions with both
parents (where appropriate) may also increase recruitment.
P48
Recruiting and Retaining Minority Subjects for Genetic
Research: Challenges and Successes
Andrea Zombeck1, Bekki Elmore1, Kara Sanya1, Beverly A. Warden1,
Robyn Davis Stephens1, Patricia C. Chulada2
1SRA
International, Inc., Research Triangle Park, NC, USA; 2Clinical Research Program,
National Institute of Environmental Health Sciences, National Institutes of Health,
Department of Health and Human Services, Research Triangle Park, NC, USA
The Environmental Polymorphisms Registry (EPR) is a unique resource of subjects and their DNA samples that
was created to facilitate genotype-driven translational research of complex disease. EPR goals are to recruit
20,000 individuals from North Carolina, collect their blood for DNA isolation, and make these DNA samples
available to scientists to screen for genetic variants in environmental response genes. Once individuals with the
“genotypes-of-interest” are identified, they are invited to participate in various types of follow-up studies ranging
from basic laboratory ex vivo cell phenotyping investigations to observational studies and clinical trials.
Since 2005, over 15,000 subjects of diverse sex, age, race, and ethnicity have been enrolled in the EPR from
clinics at local hospitals, community-based events (health fairs, health conferences, community meetings,
churches, etc.) and the internet. To minimize attrition and ensure high response rates for follow-up studies, these
subjects are contacted annually (through multiple mailings and phone calls) and asked to update their contact
information and other basic data. Nonresponders are traced using LexisNexis® and other public databases.
Using these methods, our overall attrition rate is <20%.
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P49
Data Collection for an Aging Cohort in Long-Term Clinical Trials
Pam Mangat, Nicole Butler, Hanna Sherif, Ella Temprosa, Sharon Edelstein
A major benefit of long-term clinical trials is the ability to collect large amounts of prospective data on individual
participants. With such large amounts of data, it is critical to ensure the integrity of the data and the methods
with which it is collected. Long-term clinical trials may span much of a participant’s lifetime. To accommodate
for this aging transition, minor adjustments may need to be considered during the course of the trial in order
to collect valid data while ensuring systematic collection. With an aging cohort, it is important to consider your
methods of data collection to ensure the best quality of the data. Such methods include specialized staff trainings to deal with age-related sensory, functional, and physiologic decline and cognitive impairment. To increase
functional capability, modified equipment such as sitting scales, wider examination tables and assistive devices
may be necessary. Altering phlebotomy techniques such as utilizing smaller needles and tubes may help alleviate poor venous access caused by physiologic decline. Cognitive impairment can affect the accuracy of the data
collected and a proxy may need to be consulted for verification. Prolonged illness and decreased mobility of aging
participants create barriers to clinic access for data collection. In such cases, performing collection at convenient
locations for participants including their home or nursing home may combat possible retention issues. Specific
equipment such as a portable centrifuge or scale may be needed for non-clinic study visits, so long as consistent methods of data collection and types of equipment between the home and clinic setting are maintained.
Prioritizing data collection for non-clinic visits will help staff capture the essential outcomes while reducing burden
on participants. This presentation will discuss data collection and retention issues and the important considerations necessary to retain data quality for an aging cohort in a long-term clinical trial.
P50
Participant Perception of Treatment Assignment Is Related to
Symptom Severity in a Clinical Trial of Phytotherapy
Jeannette Lee, Michael Barry, John Kusek for the CAMUS Study Group
University of Arkansas for Medical Sciences, Little Rock, AR, USA
Benign prostatic hyperplasia (BPH), a common condition among older men, is characterized by lower urinary
tract symptoms (LUTS). Symptom severity is measured by the American Urological Association Symptom Index
(AUA-SI) with higher scores reflecting greater symptom burden. The Complementary and Alternative Medicines for
Urological Symptoms (CAMUS) trial, a randomized, double-blinded trial, found that saw palmetto, a phytotherapy,
did not differ from placebo with respect to symptom relief over a 72-week period. Saw palmetto participants
received a single daily 320 mg gelcap for the first 24 weeks, two gelcaps from weeks 25-48, and three gelcaps
from weeks 49-72. Placebo participants received the same number of matching gelcaps for each period. At the
end of each 24-week period, participants were asked to guess their treatment assignment and the AUA-SI was
administered. Across assessments, no significant difference was found between treatment groups with respect
to the participants’ guesses of their treatment assignments (P=0.638) (Table 1). Regardless of actual treatment assignment, participants who thought they were on saw palmetto had significantly greater decreases in
AUA-SI than those who thought they were on placebo (Table 2). Using a general estimating equations analysis
that adjusted for intrapatient variation, the effects of actual treatment assignment, time and AUA- SI change on
participant guess were evaluated. Only change in AUA-SI was significantly associated with participant guess of
treatment assignment (P<0.001). Men with greater improvement in LUTS were more likely to believe they were
assigned to saw palmetto than placebo. It is unclear whether the perception of treatment assignment had an
effect on AUA- SI or AUA-SI change influenced perception of treatment assignment.
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P51
Dollars and Sense: Effective Fiscal Management of the Carotid
Revascularization Endarterectomy Versus Stenting Trial (CREST)
Alice J. Sheffet1, Linda Flaxman1, MeeLee Tom1, Susan Hughes1, Mary Longbottom2,
Jenifer Voeks3, John Marler4, Thomas Brott5 for the CREST Investigators
1UMDNJ-New
Jersey Medical School, Newark, NJ, USA; 2Mayo Clinic Jacksonville,
Jacksonville, FL, USA; 3University of Alabama at Birmingham, Birmingham, AL, USA;
4Rockville, MD, USA; 5Mayo Clinic Jacksonville, Jacksonville, FL, USA
BACKGROUND: CREST received five-years’ funding ($21,268,366) from NIH/NINDS to compare stenting to surgery for stroke prevention in 2500 randomized participants at 40 sites. Reimbursement denial by Medicare and
device malfunction delayed start-up. Strategies to conserve funding when the trial was halted and recruitment
lagged are described and may benefit other trials.
METHODS: Immediately, site-payment was changed from line-items for physicians’, coordinators’ and technicians’
salaries, mailings, and indirect costs, to a flat fee-for- service reimbursement for trial visit data. Reimbursement
was highest for enrollment visits and increased ($1500-$2500 per participant) when recruitment lagged. Corecenters were combined and reduced (eight to three); payments were converted to fee-for- service for consultants
and readings of angiogram and ultrasound studies. Nonessential visits were eliminated. Credentialing study
follow-up was decreased from four-years to one-year. With additional funding from Abbott Vascular, CREST
assumed the Investigational Device sponsorship, centralizing regulatory and site management by adding previously- unbudgeted research associates, a regulatory expert, paralegal, site monitoring organization and services
of Abbott field personnel.
RESULTS: NINDS funding was extended by no-cost extension from five to eight years. During these three years,
credentialing-study sites increased from 52 to 98, and 773 (50%) additional patients were enrolled. Randomizing
sites tripled (34 to 109), and 9,528 follow-up visits occurred. Of the 2500 sample size, 138 (5.5%) were randomized during the first five years and 1387 (55.5%) during the no-cost extensions, contributing to completion
of enrollment (2008) and publication of results (2010).
CONCLUSIONS: Performance-based budgets for data submitted are cost-effective, conserve funding during slow
recruitment, promote visit and data compliance, and allow for additional sites at little additional cost. Partnering
with industry for unbudgeted resources enhances productivity. Costs of large-scale clinical trials can thus be
reduced through effective management without compromising scientific integrity.
P52
Adjudication of Safety Outcomes in a Web-Based Clinical Trial Management System
Aaron Perlmutter, Holly Battenhouse, Cassidy Conner, Catherine
Dillon, Jordan Elm, Keith Pauls, Wenle Zhao
Department of Medicine, Division of Biostatistics and Epidemiology, Data Coordination Unit, Charleston, SC, USA
The central adjudication of primary safety and efficacy outcomes has been frequently used in multicenter clinical
trials in order to ensure the accuracy and consistency of outcome assessments.[1] A recent review indicated
roughly one third of randomized controlled trials used central adjudication. [2] In addition, a task-dedicated, webbased outcome adjudication system has been used in clinical trial practice.[3] The NIH NINDS-funded PlateletOriented Inhibition in New TIA and Minor Ischemic Stroke (POINT) Trial plans to enroll 4150 subjects from up
to 150 clinical sites. The trial requires a complex adjudication procedure for primary safety outcomes, involving
up to seven review steps. This adjudication procedure has been implemented into a web-based Clinical Trial
Management System (CTMS), using its generic form review function, which allows a form record to be reviewed by
a designated user based on the contents of the record and the results of previous review steps. To accomplish
this in the CTMS, the adjudication procedure was broken down into seven steps with clear definitions of triggering conditions and review questions. A transition logic matrix was used to avoid dead loops and broken chains.
Scheduled and action driven email notifications and main menu alerts were designed to notify users of action
items. The preliminary experience of using this web-based adjudication function demonstrates that the average
time from a site’s first submission of the safety event case report form to final adjudication was trimmed about
50 percent compared to manual coordination, in addition to benefits in automatic documentation of the review
process. While the advantages of web-based trial operation management are easy to show, the complexity level
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of the adjudication procedure must be justified based upon cost- benefit considerations. Also, the close monitoring of the adjudication process by a designated project manager is needed in order to address unforeseeable
situations.
P53
Study Design Issues in a Randomized Trial Comparing the Cost-Effectiveness
of Immediate Treatment Vs. Observation/deferred Treatment Approaches
Danielle Chandler, Michele Melia
Some medical conditions may resolve with a period of observation and/or conservative treatment but may
require a more aggressive treatment if symptoms persist. In such conditions it is often of interest to design
studies to compare clinical and economic outcomes of immediate treatment versus deferred treatment strategies. Evaluating cost-effectiveness can be particularly important when the timing of treatment affects how much
the treatment costs.
One example is treatment of nasolacrimal duct obstruction (blocked tear ducts) in infants. This common condition often resolves without surgery, either spontaneously or with non-surgical treatment, and is sometimes
treated with a surgical probing of the nasolacrimal duct. In infants younger than one year, the surgical probing
can be performed with the infant awake in the office setting. In infants older than one year, the surgical probing
must usually be performed under general anesthesia in a more costly surgical facility setting. We designed a
randomized trial to address the question ‘is it more cost- effective to perform the less expensive surgery on all
patients or to perform the more expensive procedure on the subset of patients whose condition doesn’t resolve
with observation and non-surgical treatment?’
Using our randomized trial as an example, we explore the impact of the rate of resolution in the observation/
deferred treatment group on cost-effectiveness and illustrate study design issues related to defining outcomes,
choosing an outcome timepoint, deciding on a subject-level or eye-level analysis, estimating sample size, and
the impact of loss to follow up. We also discuss the advantages and disadvantages to the approach we have
taken to handling these issues.
P54
Starting a Genetic Repository
Alice K. Henning
Genetic Repositories are increasingly common components of clinical trials since identifying genetic risk factors for disease is an area of great interest to the research community. In the process of setting up a Genetic
Repository for the Age-Related Eye Disease Study 2 (AREDS2), a large multi-center study sponsored by the
National Eye Institute, we found a number of areas needed to be considered both in the design of the sample
collection and the selection process of the laboratory to serve as the Repository. Maximizing research goals given
budgetary considerations will determine what type of samples will be collected (blood and/or saliva) and which
materials (DNA, RNA, serum, and/or plasma) will be isolated and stored in the Repository. Participants may be
offered a choice in the consent document whether their samples are to be used for research for any disease or
a specific disease. However, if this choice is provided, this means that data from the different consent groups
will need to be provided in separate data tables when sent to the Database of Genotype and Phenotype (dbGaP).
While assigning a different number to the material than the one on the blood/saliva sample helps protect participant confidentiality, this should be weighed against the potential for labeling error at this step. Quality control
procedures should be put into place to identify labeling errors. One possibility is DNA fingerprinting the materials
obtained from multiple samples from the same participant. In evaluating the laboratory that will serve as the
Repository, it is important to assess how sample history is documented and to evaluate the procedures for adjudication and documentation of mishandled/mislabeled samples. In addition, the experience of the laboratory in
handling a similar volume of samples and whether staff will be dedicated to processing samples for the study
should be considered.
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P55
Interim Analysis With Sample Size Re-Estimation for Binary Outcome in a Trial of
Intravitreal Ranibizumab Versus Saline Injection for Prevention of Vitrectomy
in Eyes With Proliferative Diabetic Retinopathy and Vitreous Hemorrhage
Michele Melia, Allison Edwards, and Craig Kollman for the
Diabetic Retinopathy Clinical Research Network
This trial was designed to determine whether intravitreal injections of ranibizumab would facilitate clearing of vitreous hemorrhage and avoidance of vitrectomy (surgical removal of the vitreous) in eyes with proliferative diabetic
retinopathy and vitreous hemorrhage. Vitrectomy by 16 weeks was the primary outcome. Due to uncertainty in the
outcome proportions used for the sample size calculation, an interim sample size re- estimation was proposed, in
addition to monitoring for efficacy and futility. This presentation will describe the interim monitoring and sample
size re-estimation plan, focusing on the concepts and implementation rather than statistical details, and discuss
points to be considered and pitfalls to be avoided. The plan used the method proposed by Li et al [Biostatistics,
2002], and consisted of a single interim analysis when outcome data was available for approximately ½ of the
initial sample size. If this analysis showed a strong benefit of treatment meeting a predefined criterion, the plan
recommended early stopping for treatment benefit. Otherwise, the sample size needed to give 90% conditional
power to detect the treatment effect of interest (2:1 ratio of events control:treated) was calculated based on the
observed outcome proportion, pooling both treatment groups, at the time of interim analysis. If the new sample
size was the same or less than the original sample size, the plan recommended continuing with the original
sample size. If the new sample size was greater than the original sample size but less than a pre- specified maximum, the plan recommended continuing using the new sample size. If the new sample size was greater than the
pre-specified maximum sample size, the conditional power at the pre-specified maximum was computed. If this
conditional power was less than a pre-specified minimum acceptable power, the plan recommended stopping for
futility. Otherwise, the plan recommended continuing to the maximum sample size.
P56
Abstract Withdrawn
P57
Alcoholism Treatment Studies: a Design Proposal to Improve Relevance
Robert Lew, Jasmine Escalera, John Hermos
Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Cooperative
Studies Program Coordinating Center, VA Boston Healthcare System, Boston, MA, USA
Randomized trials designed to determine effective treatments for alcoholism have produced, at best, minimally
positive, short- term findings. To obtain more clinically relevant results, studies need to address: the heterogeneity and diverse treatment goals of the population with alcohol problems, narrow eligibility criteria that limit
generalizability; subjects’ reluctance to enter and remain in studies; and short-term interventions that, even if
successful, have little impact on long- term courses and recoveries. We propose an adaptive study design which
would be potentially feasible within the large cohort of veterans seen at Department of Veterans Affairs (VA) medical facilities. The VA electronic data capture (EDC) system collects nearly all data from clinical visits, pharmacy,
procedures, radiology, and follow-up visits. Utilization of this system would allow for the potential to passively
follow a cohort of perhaps 50,000 veterans for a decade. Some randomization is needed to detect and minimize
confounding by indication; this process would entail attention to eligibility and informed consent. Physicians must
comply with rules about regular follow-up evaluations. With these provisos, the range of problems, goals, and
treatments could be evaluated as in a phase II design with statistical adjustment for missing data and dropout.
Adaptively, new patients can receive more of the promising treatments and weaker treatments can be dropped
as if seeking an optimal dose, with the ongoing cohort providing long-term results for the promising treatments.
If a particularly promising treatment emerges and some past randomization has occurred, then a formal phase
III randomized trial can begin making use of the past accrued data and following the analysis plan in Berry’s
seamless designs.
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P58
Randomised Controlled Trials With the Purpose to Gain Reimbursement
for Medical Devices in Germany - Responsible Institutions and Trial Design
Requirements for the Implementation of Study Results in the DecisionMaking Processes Using the Example of Negative Pressure Wound Therapy
Doerthe Seidel1, Marcus Redaelli2, Tim Mathes1, M. Affuepper-Fink1, Stefanie
de Lange1, Tilman Treptau1, Rolf Lefering1, Edmund A.M. Neugebauer1
1Institute
for Research in Operative Medicine Private University of Witten / Herdecke gGmbH Cologne, NordrheinWestfalen, Germany; 2Interdisciplinary Center for Health Services Research Institute of General Medicine and
Family Medicine Private University of Witten / Herdecke gGmbH Witten, Nordrhein-Westfalen, Germany
A decision of the Federal Joint Committee Germany states that negative pressure wound therapy is not accepted
as a standard therapy with full reimbursement by the health insurance companies in Germany. This decision
is based on the rapid report and the final report of the Institute for Quality and Efficiency in Health Care, which
demonstrated through systematic reviews and meta-analysis of previous studies projects that an insufficient
state of evidence regarding the use of negative pressure wound therapy (NPWT) for treatment of acute and
chronic wounds exists. The Institute for Research in Operative Medicine (IFOM) as part of the University of Witten
/ Herdecke gGmbH is an independent scientific institute that is responsible for the planning, implementation,
analysis and publication of trial projects regarding the efficacy and effectiveness of negative pressure wound
therapy for acute and chronic wounds in both medical sectors (in- and outpatient care) in Germany. The study
projects are designed and conducted with the aim to provide solid evidence regarding the efficacy of NPWT. The
trials evaluate the treatment outcome of the application of a technical medical device which is based on the principle of negative pressure wound therapy (Intervention Group) in comparison to standard wound therapy (Control
group) in the treatment of chronic foot wounds and acute subcutaneous abdominal wounds after surgery. All used
treatment systems bear the CE mark and will be used within normal conditions of clinical routine and according to
manufacturer’s instructions. The aim of the trial projects is to compare the clinical, safety and economic results
of both treatment arms. Study results will be provided until the end of 2014 to contribute to the final decision of
the Federal Joint Committee Germany regarding the general admission of negative pressure wound therapy as a
standard of performance within both medical sectors.
P59
Multicentre Trial Electronic Data Capture Platform (MCT eDC)
OHRI-CEP, Methods Centre-Data Management Services
Dong Vo
Methods Centre-DMS manager, OHRI-CEP
The management of multicentre trials is a tremendous undertaking from an administrative perspective. Too often,
multicentre trials operate as silos and there may be a lack of standardization in how administrative aspects of
the trials are organized. Presently, it is extremely inefficient for the development, implementation and management of a multicentre trial using a paper-based data capture system. The bigger the multicentre trial, the bigger
the challenges for the management of a paper-based, non-standardized system.
The OHRI Methods Centre Electronic Data Capture System Platform is an integrated, electronic multicentre trial
management software package (thin-client /web-based) that is comprehensive in scope, yet general enough
that it can be adapted for use in multicentre trials of various designs and in different clinical areas. It has many
advanced features and fully compatible with all the popular internet browsers.
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P60
Aging in Numbers – National Health Care Trends and the
National Institute on Aging Funded Clinical Trials
Tibor Szentendrei, Patti Shugarts, Ben Piper, Selma Kunitz
KAI Research, Inc. an Altarum Company, Rockville, MD, USA
The Human Intervention Studies Database (HISD), developed by KAI Research, Inc. for the National Institute on
Aging (NIA), National Institutes of Health, helps NIA program officials to manage their scientific portfolio. The
database tracks all NIA funded clinical trials and provides detailed information and customized reports. We have
used the NIA HISD data to analyze the frequency of health conditions, diseases and interventions the NIA targets
in its mission to improve the health and quality of life of older adults. We compare these data to aging statistics
and key indicators of wellbeing available from the National Center for Health Statistics and to the strategic
initiatives of the NIA. Indicators of chronic health conditions, mortality, age-related diseases and disabilities and
various health care indicators are used for the comparison. The HISD frequency data are well aligned with the
strategic goals of the NIA and the national health statistics. We will provide case studies of uses of the data
and illustrate how an administrative tracking tool can yield valuable information for describing current initiatives
and planning future directions. Since the database tracks only interventional studies, these data show an important part but not all of the clinical research and strategic initiatives sponsored by the NIA in support of an aging
society.
P61
Factor Analysis of the Correlates and Characteristics
of Stressful Life Events in the Today Cohort
Laura Pyle, Natalie Walders Abramson, Jennifer Berry, Laure El ghormli
George Washington University Biostatistics Center, Rockville, MD, USA;
University of Colorado Denver, Denver, CO, USA
Relationships between deterioration in health status and exposure to stressful life events have been well-documented among patients with various chronic illnesses; however, little is known about the impact of life stressors
on the course and management of type 2 diabetes (T2D) in youth. The TODAY clinical trial provided an opportunity
to examine associations between stressful life events and physiologic markers, specifically, elevations in HbA1c
and BMI among youth with T2D. TODAY (Treatment Options for type 2 Diabetes in Adolescents and Youth) was a
multi-center NIH-funded clinical trial to test treatment regimens for youth-onset T2D. Participants were age 10-17
inclusive and diagnosed with T2D < 2 years at baseline. They were treated and followed for 2-6 years. During the
trial, the study teams had to address multiple challenges to retention and participation in the study due to the
psychosocial environment of the participant and the youth’s family. In the final year of the trial, participants completed a self-report life stressor form adapted from the Yeaworth Adolescent Life Change Event Scale(1980) and
inclusive of selected items from the Holmes and Rahe (1967) Social Readjustment Rating Scale. The 33-item
measure assessed frequency and self-rated level of distress associated with stressful life events over the past
year. Data are available from 517 overweight youths from predominantly minority backgrounds (41.1% Hispanic;
31.5% Non-Hispanic Black; 19.6% Non- Hispanic White).
After presenting descriptive statistics and correlations to describe the associations between stressful life events
and select physiological markers, we report the methods and results of factor analysis to identify any relevant
subgroups of stressor types. Findings will increase our understanding of the psychosocial challenges faced by
youth with T2D which will help shape and optimize clinical practice, as well as inform the development of intervention programs to maximize self-care and functional status among this vulnerable population.
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P62
Strategies Implemented for Successful Data Retrieval
and Accuracy in a Long Term Follow-Up Study
Mariam Saleem, Johanna Sanchez, Elizabeth Asztalos
The Centre for Mother, Infant, and Child Research Sunnybrook Research Institute Toronto, Ontario, Canada
The Multiple Courses of Antenatal Corticosteroids for Preterm Birth Study: A 5-year Follow-up (MACS-5), is an
international multi-centre trial assessing 1200 children from the original MACS study at 5 years of age. The
MACS-5 study aims to determine the long-term effects of antenatal corticosteroids with emphasis on cognitive,
behavioral and motor development. It was important to implement specific data retrieval strategies in the early
phases of the study, since challenges with long term follow-up were anticipated.
Throughout the study, regular communication via email was maintained with all sites. Monthly reminder reports
listing all overdue data were mailed to collaborators, and reminders to send in all data were also included in a
bi-monthly newsletter. Efforts to ensure data accuracy were maintained by generating quarterly query reports for
each site and conducting annual frequency reviews for all MACS-5 data.
In the final year of follow-up, efforts to retrieve data and resolve queries were intensified and specific strategies
were implemented to collect the remaining data. A site status report was created to regularly monitor outstanding
data and queries for each site. Focus on retrieving query replies was increased by sending monthly query reports
to sites, followed by telephone calls if no reply was received within a three week period. For sites who still had
not returned their data, the Principal Investigator contacted the sites by email and telephone. Continued delays
of receiving data led to the implementation of a pre-arranged courier to have data picked up from the sites. Site
visits were undertaken as a last resort where communication remained unsuccessful.
The approaches implemented in the MACS-5 study were successful in surpassing the original target follow-up
goal of 1200 children. As of December 1, 2011, 1539 children had completed MACS-5 follow-up assessments.
In addition, 98.6% of these follow-up cases had no outstanding queries.
P63
An Approach to Study Drug Management in Randomised Controlled Trials
Sunny Chan, Michael Shi, Elizabeth Asztalos
In randomised controlled trials (RCTs) involving study drug, supply management is a challenge that is often faced
by the site and trial coordinating centre. The drug supplier and drug distributor may work independently, and as a
result, a combined effort is essential to maintain a consistent flow of study drug for the duration of the trial. The
Centre for Mother, Infant, and Child Research (CMICR), is the data and clinical coordinating centre for several
multi-centre RCTs. Several of the RCTs evaluate study drug intervention. The approach to study drug management
was to design and develop a software program to facilitate the process of ordering treatment kits containing
study drug, tracking shipment, and maintaining precise details of all assigned treatment kits.
In the study drug management program, treatment kits are uniquely numbered and a corresponding document
is generated as a reference for the drug distributor. As new sites join the trial, treatment kits are ordered and
shipped to prepare for patient recruitment. Additional kits are ordered for participating sites on an as-needed
basis. The process is completed using automated electronic communication with instant update of the site inventory that is available for patient randomisation. For the trial coordinator, the program gives them the control over
the amount of treatment kits to store at a particular site and better manage the overall supply parameters. The
program is also able to facilitate drug reconciliation, drug recall, and set triggers for low inventory and drug expiry.
The study drug management program greatly reduces the administrative effort needed by the trial coordinator
while improving the efficiency of the drug supply management process.
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P64
Using iPods© as an Intervention Delivery Method and Fidelity Monitoring Device
Tamara Olinger, Elizabeth Avery, Giselle Mosnaim
Rush University Medical Center Department of Preventive Medicine, Chicago, IL, USA
Fidelity and adherence with respect to an intervention can be tracked using readily available software and devices
without burdening study participants. The Coping Peer Intervention for Adherence Trial (ADEPT) is a behavioral
trial aiming to improve medication adherence in underserved minority youth with asthma. The study’s primary
intervention involves listening to medication adherence messages on an iPod © that is provided to each participant and pre-loaded with songs. Participants in the intervention arm meet as a group weekly to record messages
to each other that encourages his/her peers to take their medication as prescribed. These messages are overlaid on a song of the participant’s choice. While mirroring in content, the control arm’s messages are recorded
by a physician and don’t incorporate music. Participant’s iPods© are updated weekly with five new songs of
his/her choice as well as new adherence messages. During these weekly visits the iPod© statistics, including
song name, artist, length of song, number of times played, and number of times skipped, is extracted from the
iPods©. Usage statistics are reset between individuals to ensure clean data. These data are stored in iTunes©
and can be exported and stored in Microsoft Excel sheets by participant and time period, and can be exported
to any database of choice. This data allows investigators to monitor intervention fidelity by comparing listening
habits, particularly to medication adherence messages. In ADEPT, the iPod© serves as not only the intervention
delivery method, but also the means to remotely monitor intervention fidelity and dosage.
P65
Establishing a Remote Data Entry System in a Rural Trial Community
Dixie J. Ecklund, David Drake, Kathy Phipps
University of Iowa, Iowa City, IA, USA
American Indian and Alaska Native (AI/AN) populations within the United States are underserved in their access
to health care as well as clinical trials. Our goal was to establish a clinical site in a rural Tribal community for
an observational trial and train staff at the clinical site in remote data entry. In order to conduct a clinical trial
with members of a tribe, approval must first be obtained from the Tribal Research Review Board and the Tribal
Institutional Review Board of record. To facilitate interactions with the Tribe, the Principal Investigator contracted
with a researcher who has an established professional history of working in and among AI/AN populations to
serve as a liaison. A clinical site coordinator was hired who did additional hirings of staff for recruitment, clinical
assessments and data entry. A data entry system was developed with up to 15 electronic case report forms collected at each of 8 visits. Because of the likelihood of missing data or missing visits, none of the forms or fields
were developed as required or mandatory data entry. When the data entry system was completed and validated,
we traveled to the clinical site on the reservation and conducted data entry training with the staff, all of whom
were Tribal members. The clinical site staff quickly learned the requirements of data entry and have entered data
on almost 250 subjects into the data entry system. The tribal liaison has traveled to the site on several occasions to review data entry and perform quality control. Follow-up is expected to be completed by May 2014 and
the data will be ready to be analyzed by statisticians at the University of Iowa.
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P66
Clinical Data Management of HIV/AIDS-Related Illnesses
in Hiv Clinical Trials: Challenges and Solutions
Maija Anderson, Jenny Tseng, San-San Ou, Lei Wang
Statistical Center for HIV/AIDS Research and Prevention, Fred
Hutchinson Cancer Research Center, Seattle, WA, USA
Objectives: HIV/AIDS-related illnesses are key endpoints in multi-site HIV prevention trials. Accurate reporting
of these endpoints requires systematic procedures for collecting, reviewing, and cleaning the clinical data. The
U.S. Center of Disease Control (CDC) and World Health Organization (WHO) provide guidelines that define HIV/
AIDS-related illnesses; yet clinical data management and operational challenges are rarely discussed.
Methods: The Statistical Center for HIV/AIDS Prevention and Research (SCHARP) was responsible for collection
and analysis of clinical data from the National Institute of Allergy and Infectious Diseases (NIAID)-sponsored
HIV Prevention Trials Network protocol 052 (HPTN 052). In HPTN 052 primary clinical endpoints were reviewed
by blinded protocol team physicians for acceptance. Clinical data reconciliation challenges included reporting of
multiple symptoms instead of one known diagnosis, inaccurate onset and outcome date, inconsistent reporting
on worsening of illness, and over reporting of events. Discrepancies in reporting any of the above key data elements ultimately affect the medical review and data analysis.
Results: SCHARP clinicians and statisticians routinely partnered with protocol team physicians to assess and
reconcile discrepancies in HIV/AIDS-related illnesses using multiple data sources. The SCHARP clinicians then
worked with study sites to resolve identified issues. SCHARP designed a web-based tool to facilitate and track
the clinical medical review. A consistent work flow was developed and utilized for the clinical data management
and operational process for review of HIV/AIDS-related illnesses.
Conclusion: Close collaboration between the SCHARP statistical and clinical groups and the protocol team physicians ensured accuracy and completeness in HIV/AIDS-related illnesses for endpoint analysis. The web-based
tool, though in its nascence, proved useful to streamline the review process and reduce potential data errors.
The utilization of this web-based tool, providing blinded clinical cases for protocol team member review, can serve
as a useful model for other clinical trials.
P67
Coding Open-Ended Responses: Identifying Problems and Solutions
Jennifer Talton, Ralph D’Agostino Jr., Joseph Grzywacz, Thomas
Arcury, Maria Mirabelli, Grisel Trejo, Sara Quandt
Open-ended responses are common in many questionnaires, and coding of responses is challenging. La Familia
Sana Promotora Program was a demonstration project conducted to evaluate the translation of an intervention
designed to improve farmworker family pesticide-related knowledge and practices. The Promotora Program used
open- ended responses to measure changes in behavior and knowledge from pre- to post- test. This paper identifies complexities and solutions in the process of ensuring reliability in coding of responses in order to create
discrete categories for evaluation of results.
The evaluation included 20 questions used to address 18 learning objectives. Seven questions relied completely
on participants’ narrative responses and were coded as “correct”, “incorrect”, or “partially correct”. Thirteen
questions had “other” as a response field, and the text was then coded as “correct” or “incorrect”.
Primary and secondary coders were trained to code the open-ended responses. The primary coder coded all participant responses; the secondary coder coded a 10% random sample. Kappa statistics were used to gauge the
inter-coder reliability. The seven questions based solely on narrative responses were highly discordant (range:
21% to 60%). The “partially correct” and “correct” codes were combined into a single “correct” code, and the
discordance decreased (range: 8% to 27%). Despite this improvement, the investigators decided that an expert
should code these problematic questions. For the thirteen partial narrative responses, the kappa statistics
showed favorable reliability between coders and did not require expert coding (range: 0% to 2% discordant). This
study illustrates the need for content experts to code responses to completely open-ended questions; training
staff is not sufficient to ensure quality data is coded.
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P68
Database Structure for Multiple Protocols Within a Project
Danielle Smith
Data structure can be straightforward for a single protocol in a project. However, when sub-studies need customization, there can be many obstacles when variation is required for each protocol. The Autism Treatment
Network (ATN) began a data registry to collect retrospective and prospective data on children with autism spectrum disorders (ASD) between the ages of 3-18 with a primary focus on nutrition and sleep issues. With a grant
from the Health Resources and Services Administration (HRSA), the ATN conducted two sub- studies: The Diet
and Nutrition in Children with ASD (Nutrition) and Sleep Education Program for Parents of Children with Autism
(Sleep).
Both studies had assessments that overlapped with the Registry as well as assessments that were exclusive to
each protocol. Data from the Registry was used for the sub-study if collected within a specific window. For example, the Child Behavior Checklist was completed for the Registry and required for both the Nutrition and Sleep
protocols but did not need to be repeated as long as the data were collected within 60 and 90 days, respectively.
Initially, only assessments exclusive to the Nutrition and Sleep protocols were required in the database for each
participant at the time of enrollment. Assessments that overlapped with the Registry were already developed
and as the assessment was only repeated for a portion of the participants, any repeated assessments were
entered under the Registry protocol. This allowed the data to be pulled from one database for all three protocols
using the form date to determine most recent data. However, when the Registry protocol was amended and the
database was restructured, the Nutrition and Sleep databases also required restructuring. This presentation will
also highlight other obstacles related to the management of sub-studies.
P69
Optimizing Optical Character Recognition Software for High Quality Data
Jennifer Andringa, Rachel Akers, C. Ralph Buncher, Todd Jenkins,
Yanhong Liu, Rosemary Miller, Carolyn Powers
Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
Accurate, high quality data are essential to any research study, making it critical to proactively identify and
eliminate errors before they enter the database. A major challenge to using optical character recognition (OCR)
software for data entry is identifying errors produced by stray marks, respondent corrections, or improperly completed fields. While many errors can be caught by carefully defining fields through built-in field property settings,
we have found that the error reducing capacity of OCR software is greatly expanded by use of customizable
scripts. Common checks scripted into data collection forms typically verify skip pattern logic, logical comparisons
between fields, and restrict numeric entries to discrete values. If data read by the OCR fails these checks, they
are flagged for review. Customizable scripting allows developers to add additional checks and flag data during
processing. In instances where noise or an unintended mark was interpreted as data, or valid data was not
detected by the OCR, use of customizable scripts enables the data manager now to prevent such errors from
migrating to the database. Furthermore, if the data reported were captured accurately but fails a check, the data
manager can query the reporting site and rectify the issue. We selected an OCR software system (TeleForm®) as
our primary tool for data collection and management in a multi-center study investigating the safety and efficacy
of bariatric surgery in adolescents. We conducted an in-depth evaluation of the database, encompassing more
than 250,000 data fields, and found very few errors (0.065%). Among critical data elements, the error rate was
0.048%. By optimizing TeleForm® through robust error checking scripts, we produced accurate, high quality data
in a timely fashion for a multi-site clinical study.
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P70
Challenges to Transitioning From Paper-Based Data
Collection to Electronic Data Capture
1
Trinh Hoac , Ainy Zahid1, Dalah Mason1, Johanna Sanchez1, Elizabeth
Asztalos1, Claire Hahnhaussen2, Joanne Kirton2, Sue Ross3, Peter von
Dadelszen2, and Laura A. Magee2 for the CHIPS Study Group
1The
Centre for Mother, Infant, and Child Research, Sunnybrook Research Institute,
Toronto, Ontario, Canada; 2The University of British Columbia, Vancouver, British
Columbia, Canada; 3University of Calgary, Calgary, Alberta, Canada
The Centre for Mother, Infant, and Child Research (CMICR) is a central coordinating centre for several large
national and international multi-centre randomized controlled trials to improve the health of women and their children. The unit has conducted research trials since 1988, and has evolved in clinical research practices alongside
technological advancements. The data collection process has transitioned with each new trial, from paper-based
data collection to online PDF data forms to electronic data capture. With every transition, it is important to maintain the integrity of data quality and ensure that the process is in compliance with International Conference of
Harmonisation (ICH)/ Good Clinical Practice (GCP) standards.
The challenges and considerations in transitioning the data collection process include programming to set up
the database and training for both the CMICR data coordinator and site coordinators. The transition requires
changes in programming for how the data are captured in the database and updating various reporting systems
such as data form tracking, queries, funding and compliance reports. Furthermore, it is necessary to consider
training each site coordinator in the new process of reporting data, and how to interpret the associated reports.
This presentation will illustrate the approaches used in the technological transition of the data collection process.
P71
Utilizing a Web-Based Telephone Call Tracking System
in the Collection of Cognitive Data
Darrin Harris, Patricia Hogan, Sarah Guassoin, Claudine Legault,
Michelle Naughton, Julia Robertson, Debbie Pleasants
The Women’s Health Initiative Memory Study (WHIMS) is an ancillary study to the Women’s Health Initiative (WHI),
designed to determine the short and long-term effects of hormone therapy on the development and progression
of dementia symptoms in postmenopausal women. The Women’s Health Initiative Memory Study - Epidemiology
of Cognitive Health Outcomes (WHIMS-ECHO) provides annual cognitive assessments of women who were aged
65 or older at the time of randomization to WHI, and The Women’s Health Initiative Memory Study of Younger
Women (WHIMS-Y) assesses the long-term impact of random assignment to postmenopausal hormone therapy
among women who were aged 50-54 at the time of randomization into the WHI hormone trials.
To increase efficiency, lower participant burden, and reduce costs, cognitive data on consenting women from
WHIMS-ECHO and WHIMS-Y are obtained annually through centralized cognitive telephone interviews conducted
by trained and certified staff at the WHIMS Coordinating Center. To assist in this process, a web-based telephone
call tracking system has been implemented, identifying administrative tasks and the order in which participants
should be called based on study rules and priorities that have been established. Additionally, it is flexible enough
to allow interviewers to schedule calls in accordance with participant needs. When a participant is selected,
the interviewer is provided the contact information, pertinent study data and call history. After a call has been
made the interviewer inputs the date, start time, end time, and outcome of the call allowing the system to track
each attempt. Real-time reports monitoring study calls are used to detect any issues that may have a significant impact on data collection, personnel needs, or costs. The poster will describe the Telephone Call Tracking
System in detail discussing the benefits and challenges.
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P72
Improving the Reliability of Web-Based Randomization Using Encrypted
Allocation Information Embedded Into Data Elements
Gordon S. Doig and Fiona Simpson
Royal North Shore Hospital, Intensive Care Unit, Sydney, NSW 2065, Australia.
Background: The use of web sites to conduct patient allocation is increasing in popularity. Embedding encrypted
information into a data element that is fed- back to the user after a patient is allocated is an inexpensive and
effective way to provide an off-site back-up to protect machine rooms from catastrophic failures.
Methods: Assume a multi-centre trial generates an allocation sequence using variable sized permuted blocks,
stratified by site and one patient factor. Each site requires a unique allocation sequence matrix (Table 1).
Table 1. Allocation sequence, Site 1
StrataA 0_A1 0_A2 1_A3 1_A4 0_A5 … treatment_AX
StrataB 1_B1 1_B2 1_B3 0_B4 0_B5 …
treatment_BY
To allocate patients, the web server must track two counters at each site: the number of patients previously
assigned to StrataA (AX) and StrataB (BY). Using a hash function based on a block cipher, or a trapdoor function,
the study server can generate a variable representing these counters (Site1_AXBY) and pass the variable back
to the participating site as an encrypted ‘transaction code’ (enc- Site1_AXBY). This transaction code is recorded
on paper and stored locally at the participating site.
Results: To randomise a patient during a catastrophic server failure, the site research coordinator telephones the
study coordinating centre (SCC) and provides the ‘transaction code’ (enc-Site1_AXBY) for the patient randomised
immediately prior to the server failure. The transaction code is decrypted and matched against the site- specific
allocation sequence matrix which enables the SCC to make the appropriate treatment allocation for the next
patient to be enrolled.
Conclusion: This approach to backing-up trial status is inexpensive, robust and enables a study to recover from
catastrophic server failures with zero down time with no reliance on archived electronic information. It can be
extended to work with any type of allocation sequence (Ex. blocked or adaptive, such as minimization).
P73
A Tailored Communication Platform for a Virtual Intervention Team
Elizabeth F. Avery, Tamara Olinger, Steven K. Rothschild, Erin E. Emery
Department of Preventive Medicine, Rush University Medical Center, Chicago, IL, USA
Optimal healthcare is often accomplished by enlisting a team of interventionists. However, an intervention team
does not have to meet in person to achieve effective communication. The intervention arm of the BRIGHTEN Heart
behavioral trial employs an interdisciplinary virtual team strategy to enable experts to jointly develop and implement treatment plans for older adult trial participants with depression. The virtual team consists of BRIGHTEN
Heart interventionists and the participant’s primary care physician (PCP). The PCP’s access is limited to their
patients using built in security. In order to facilitate secured remote communications between team members,
the Data Core of the Rush Center for Urban Health Equity has developed a Microsoft SharePoint web server to
host an intervention communication platform that is HIPAA compliant. All data and written communications are
held in a series of connected “lists” that appear on the webpage in a set of interactive, easily readable forms.
Data from the initial research assistant interview is combined with a report from an evaluation by a social worker
to create a patient description. Initial communications about the participant are handled in a separate linked
list. The platform allows each virtual team member to have an individual entry line to record their recommendations for each participant. This communication platform is used to keep the intervention team informed of each
participant’s progress in the study by the Data Core and treatment personnel, offers the means to make new
recommendations, and allows effective communication among team members. The lists also enable the Data
Core to track specific intervention fidelity measures (e.g. level of engagement and quality of care for each virtual
team member). By utilizing standard components of SharePoint we have created a tailored communication platform that is easy to use, efficient, cost effective, tracks intervention fidelity and protects participant information.
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P74
The Use of a Multifaceted Clinical Trial Implementation and
Education Strategy to Minimise Major Protocol Violations
Fiona Simpson, Gordon Doig, Elizabeth Sweetman
Northern Clinical School, Intensive Care Research Unit, University of Sydney, Australia
and Royal North Shore Hospital, Intensive Care Unit, Sydney, NSW 2065
Introduction: Evidence demonstrates the effectiveness of clinical trial interventions may not become apparent
until major protocol violations are minimised. Certain change management strategies are proven to promote
adherence to clinical protocols and guidelines and can successfully narrow gaps between knowledge and practice. These strategies may also be useful in minimising major protocol violations in a clinical trial.
Study Objectives: To design a clinical trial implementation and education strategy using change management
strategies and evaluate its impact on major protocol violations.
Methods: The change management and clinical trials literature was reviewed. The resultant implementation and
education strategy included: formal training for local recruitment coordinators; educational outreach visits with
one-on-one education (academic detailing); a formal run-in phase and; staggered site start-up meetings. This
strategy was used to initiate a multi-centre clinical trial. Major protocol violation rates are reported and compared
to published figures.
Results: At the time of analysis, 409 patients had been enrolled from 32 sites, with 9 (2.2%) major protocol
violations: four recruitment errors; three study process errors and; two technical website errors (2/9). This is
significantly lower than published Phase III FDA licensing trial figures (PROWESS 351/1690 vs 9/409, p <0.001).
Conclusions: An implementation and education strategy based on change management strategies can reduce
major protocol violations significantly lower than published rates. We believe that formally trained local trial
recruitment coordinators, who retain primary responsibility for patient identification, recruitment and protocol
implementation, are the most effective component of our strategy.
P75
The Novel Use of Site Selection Surveys to Improve Sub-Optimal Recruitment
Fiona Simpson and Gordon Doig
Royal North Shore Hospital, Intensive Care Unit, Sydney, NSW 2065, Australia
Background Recruitment fatigue is known to occur in numerous trials. Many strategies have been utilised in the
past in order to improve and/or maintain steady recruitment, such as use of patient screening logs. Screening
logs have been shown to be effective in increasing trial recruitment but require dedicated persons to screen,
which may not always be feasible.
Methods In preparation for a 26-hospital randomised controlled trial, potentially eligible sites interested in participating in the trial were required to complete a detailed site selection survey. Interested sites recorded trial
eligibility criteria information on 15 consecutive patients in a de-identified manner. Realistic minimum and maximum expected recruitment rates were then calculated for each site.
Results After study onset, certain sites were found to be recruiting sub-optimally. Although many sites kept
accurate screening logs, others were incomplete, as research coordinators worked part-time. Where no complete
screening logs were available, site selection surveys were used to facilitate open communication between the
site and the lead investigators. We found that site investigators, who had not previously seen the completed
site selection surveys, were very responsive to the results of the survey and were motivated to work actively to
improve recruitment. Minimum recruitment rates estimated by the site selection survey were then set as their
future recruitment rate targets.
Conclusion When accurate screening logs are not available, detailed site selection surveys can be used to
improve sub-optimal recruitment and combat trial fatigue.
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P76
Consort-Like Flowcharts in Dsmb Reports
Patricia Feeney, Neil Wohlford
Statistics Collaborative, Inc.
Data Safety Monitoring Boards (DSMBs) perform an important role in overseeing participant safety during randomized clinical trials. DSMBs generally review unblinded data and report back to the sponsor or Steering Committee.
Interim reports to the DMSB typically include data by study arm that encompass enrollment, treatment, patient
disposition, data collection, laboratory values, adverse events, and/or efficacy.
While DSMB reports generally include tables and listings, figures can be particularly effective in communicating
overall trends. A CONSORT like (Consolidated Standards of Reporting Trials) flowchart can provide an effective
way for DSMB members to easily review the time course of participant status with respect to randomization, time
on- study, treatment, and other events.
Like the CONSORT diagram used in publications of final study data, a CONSORT- like figure in a DSMB report
would typically include the number of participants enrolled, randomized, treated, and discontinued by study arm
relative to their time on-study. For a DSMB review, this type of figure provides an interim “snapshot” of relevant
study data illustrating the study flow and can incorporate important reference events such as achieving study
goals, completion of milestone visits, deaths, or withdrawal of consent. The report could also contain separate
figures with the same layout to display events of interest particular to the study or the DSMB, such as data lag,
secondary outcomes, elements of a composite outcome, or adverse events on a timescale.
We will present several examples of CONSORT-like flowcharts that can be used to enhance interim reports to
DSMBs to help them monitor the ongoing safety, conduct, and efficacy of a trial in a succinct and clear manner. We will also provide an outline highlighting select SAS version 9.2 statistical graphing procedures that can
be used to automate the generation of the flowcharts, saving time and reducing the possibility of transcription
errors.
P77
Ethical Issues in Secondary Research With Human Specimens
Liza Dawson
NIH/NIAID Division of AIDS Research Ethics Team, Bethesda, MD, USA
Specimens collected in clinical trials are an important resource for biomedical investigation. Frequently secondary
analyses are conducted on specimens, or they may be banked in repositories for future access by researchers.
Researchers and oversight bodies often struggle with the question of consent for secondary uses of specimens.
Frequent questions include 1) whether it is acceptable to anonymize specimens which were collected for a specific purpose and use them for research outside the original scope of the project; 2) whether general consent for
future unspecified use is ethically acceptable; 3) whether genetics research requires a separate specific consent;
4) when re-consent may be needed when research aims change. As recent developments in the Advance Notice
of Proposed Rule-Making (ANPRM) on 45 CFR 46 have demonstrated, this area of research oversight is hotly
debated. This presentation will describe three models for addressing consent for research with specimens: 1)
the risk based model, where oversight is tied solely to identifiability of the materials; 2) the contribution model,
where oversight is based on donors’ interests in controlled future use of materials, regardless of identifiability
and 3) the public health model, where consent is presumed when research serves public health goals and when
risks of information breaches are appropriated reduced through secure data management and in some cases,
anonymization. The ethical and practical implications of these three models will be discussed.
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P78
Abstract Withdrawn
P79
Compensation for Bodily Damage to Participants
in Un-Notified Clinical Trials in Japan
Toshinori Murayama1, Manabu Minami1, Hiromi Nishimura2, Masayuki Yokode1
1Clinical
Innovative Medicine, Kyoto University Hospital, Kyoto, Japan;
of Biomedical Research and Innovation, Kobe, Japan
2Institute
CIOMS International Ethical Guidelines for Biomedical Research Involving Human Subjects (2002) states that
investigators should ensure that research subjects who suffer injury as a result of their participation are entitled
to free medical treatment for such injury and to such financial or other assistance as would compensate them
equitably for any resultant impairment, disability or handicap. While Helsinki Declaration of World Medical
Association (2008) describes that the protocol should include information regarding provisions for treating and/
or compensating subjects who are harmed as a consequence of participation in the research study. This (nofault) compensation is different notion from legal liability/indemnity/reparation due to malpractice or negligence
in clinical trials.
Un-notified clinical trials to the authorities are still allowed in Japan, other than IND/IDE trials. The Ethical
Guidelines for Clinical Studies, the only regulation for those, were fundamentally revised and enacted in April
2009, which obligate researchers to take measures on compensation such as insurance in clinical trials to
assess pharmaceuticals or medical devices.
Since casualty insurance companies have not accumulated know-how to estimate the risk of un-notified trials
besides IND/IDE trials, compensation insurance remains inadequate in quality; 1) Medical expense or medical
allowance cannot be paid. 2) There are considerable exceptions for such clinical trials as employ anticancer
agents, immunosuppressants, and implantable devices in this insurance.
In order to overcome the situation, we have set a working group of ‘Risk-based protection of trial participants
in un-notified clinical trials’ among academic clinical institutes and casualty company. The working group has
investigated legal restriction for insurance, medical expense reduction system in the academic hospital, and an
academic guideline for compensation in researcher-initiated un-notified clinical trials.
P80
Increasing Institutional Oversight for Multicenter Protocols: an
Institutional Office at Memorial Sloan-Kettering Cancer Center (mskcc)
Supriya Parikh, Ann Jenckes, Stephanie Skoler- Karpoff,
Ann Rodavitch, Collette Houston, Roger Wilson
As of September 2011, there were 79 active MSKCC-coordinated multicenter protocols (MCPs) spanning six
clinical departments and involving 104 unique active sites in 29 states and 5 countries. Until recently, regulatory
oversight of MCPs was investigator dependent and staff efforts were duplicated around the Center. In December
2009, the MSKCC Office of Clinical Research established the Multicenter Protocols Group (MCPG) to provide
institutional support for MSKCC- coordinated MCPs. The goals of the MCPG are to institute policies and procedures, as well as provide tools and training to ensure participant safety, protocol and regulatory compliance, and
data integrity for all MSKCC- led MCPs.
The MCPG participates in protocol development, tracks regulatory documentation for all participating sites in
MSKCC’s Protocol Information Management Database, trains MSKCC research staff, manages an intranet page
housing information and tools for MCP management, conducts MSKCC-based MCP regulatory audits, and advises
on and reviews all participating sites audits.
137
Since the establishment of the MCPG, there has been an increase in the number of new participating sites
opened to accrual as well as the number of inactive participating sites closed; a decrease in the average time
for sites to obtain amendment approvals, from 82 to 67 days. Thirty sites were suspended for regulatory noncompliance; 93% were re- opened following corrective action. The MCPG conducted the first two regulatory audits
of MSKCC-coordinated MCPs; and the study teams conducted fifteen audits of participating sites on eight protocols across four clinical departments.
Staff report that MCPG oversight has improved overall regulatory management and streamlined MCP development and oversight. The MCPG will continue tool development, quality assurance, and work closely with Clinical
Research Informatics towards web- based data entry by participating sites. This poster will compare trends in
regulatory compliance on MSKCC led MCPs since the inception of the MCPG and discuss MCP best practices
and challenges.
P81
Use of Barnard’s Test as a More Powerful Alternative to Fisher’s Exact Test
Peter Calhoun
Although Barnard’s exact test is not as commonly known or used as Fisher’s exact test, it typically offers more
statistical power for analyzing 2x2 tables. The difference between the two tests is how they handle the nuisance
parameter of the common success probability under the null hypothesis. Fisher’s test avoids estimating this
parameter by conditioning on the margins thereby considering fewer tables and restricting the number of distinct
values of the test statistic. Barnard’s test considers all possible values of the nuisance parameter and chooses
the one that maximizes the p-value. This typically provides greater power because the discreteness is less pronounced.
A previous barrier to the widespread use of Barnard’s test was likely the computational burden of considering
all possible values of the nuisance parameter. However, with the continuing improvements in computing speed
and the implementation of Barnard’s test now accessible in StatXact, Matlab, and R, the computational burden
is no longer a barrier.
The advantages of using Barnard’s test were shown when comparing the two tests by running 10,000 simulations with different sample sizes and proportions. Both tests give type 1 error rates at or below the nominal alpha
level, but Fisher’s test was often more conservative. This resulted in less power under the alternative hypothesis.
For example, when Fisher’s test required a sample size of 50 to achieve 90% power, Barnard’s test required a
sample size of 44 to attain the same power (Figure).
The limitation with using Barnard’s test is that it only applies to 2x2 tables and often requires more computation
time. However, implementing Barnard’s test using R with an Intel® vPro™ processor took around 0.1, 1, and 20
seconds for sample sizes of 30, 100, and 500 respectively. Using Barnard’s test can require fewer observations
to achieve the same level of statistical power.
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P82
Interpretation and Results Comparing Frequentist and Bayesian
Interim Monitoring: Survival and Continuous Outcomes
Alice Pressman1, Marnie Bertolet2, Alice Jacobson1
1Kaiser
Permanente Division of Research, Oakland, CA USA; 2University of Pittsburgh,
Graduate School of Public Health, Department of Epidemiology, Pittsburgh, PA, USA
Background: Frequentist group-sequential and Bayesian interim analysis techniques are increasingly promoted
for improved efficiency and ethical conduct of clinical trials. However, use of these methods is seldom reported
outside of data and safety monitoring boards. In addition, there are few published reviews of the different techniques. This project is a comparative effectiveness study which compares and contrasts Bayesian analyses with
frequentist group-sequential analyses using examples of data from two published clinical trials. We offer interpretation and evaluation of these two types of sequential analyses. Methods: For each trial, we use a commonly
utilized frequentist method (O’Brien-Fleming) and implement Bayesian sequential analyses with non-informative
prior. Because current practice dictates the preservation of an experiment-wise false positive rate (Type I error),
we approximate these error rates for our Bayesian analyses with the posterior probability of detecting an effect
in a simulated null sample. In order to consider stopping for futility, we use a frequentist group sequential inner
wedge and conditional power, a concept that translates easily to the Bayesian realm. Thus for these trials, we are
able to compare the relative performance of these techniques and evaluate both the Bayesian and frequentist
methods. Results: In the two trials we present, Bayesian and frequentist methods lead to the same decisions
about treatment efficacy or futility, however the interpretations differ. The frequentist method, more commonly
reported, uses observed data to refute the hypothesis of no effect, while the Bayesian method uses the data to
build a probability distribution from which to determine likelihood of effectiveness of the treatment. Conclusions:
Bayesian methods provide an easily interpretable outcome distribution, however there is little emphasis on decision making. Frequentist methods provide an easy decision-making tool, but tend to be more difficult to explain.
Code is provided for all analyses.
P83
Implementation and Diagnostics for Frequentist and Bayesian Interim
Monitoring: Sequential Bounds and Chain Convergence in SAS
Marnie Bertolet1, Alice Pressman2, Alice Jacobson2
1University
of Pittsburgh, School of Public Health, Pittsburgh, PA, USA;
Permanente Division of Research, Oakland, CA, USA
2Kaiser
Background: Interim analyses provided to data and safety monitoring boards in clinical trials address ethical,
cost and efficacy issues. Both frequentist group-sequential and Bayesian interim monitoring approaches address
these issues; however their implementation and verification involve very different steps.
Methods: SAS 9.2 has recently developed procedures to facilitate both frequentist and Bayesian interim monitoring. For frequentists, PROC SEQDESIGN and PROC SEQTEST will develop and identify interim monitoring
bounds and account for sequential testing of interim results. The effects of various parameters, and the interplay
between the two procedures is explained and demonstrated on a real data set. Tips and troubleshooting for
these procedures are discussed. For Bayesians, a BAYES option has been introduced into PROC GENMOD, PROC
PHREG and PROC LIFEREG. This option executes a Monte Carlo Markov Chain (MCMC) technique to obtain draws
from the posterior distribution. Tools needed to monitor convergence and techniques for improving convergence
are presented and discussed.
Results: Bayesian and frequentist methods of interim monitoring will often, though not always, agree. Frequentist
methods have the advantage of familiarity among trialists. Bayesian methods have the advantage of a more
natural interpretation and the ability to take interim looks at any time during the analysis. They have different
diagnostics and options that must be understood before implementing either method.
Conclusions: Beginning with the dissemination of SAS9.2, group sequential and Bayesian methods are accessible without high-level programming expertise. SAS9.2 provides a relatively easy-to-use set of procedures that
allows flexible analysis plans for clinical trials analysis. Understanding how to implement both sequential method
approaches should help trialists adopt a flexible approach to choosing among available options.
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P84
Analysis of Safety Data Using Sas
Thomas Bruckner, Justine Rochon, Stefan Englert
Institute of Medical Biometry and Informatics, University Heidelberg, Heidelberg Germany
Data and safety monitoring committees (DMC) become more common to evaluate the safety of new therapies,
especially in clinical trials with long duration, or life-threatening diseases requiring more or less dangerous
therapies. The task of the DMC is to monitor independently the course of the study and recommend whether an
intervention is too dangerous for patients to continue the trial or it is not ethical to continue due to efficacy of the
new therapy. While efficacy analysis is mainly focused on one primary endpoint looking for differences, analysis
of safety has to consider several adverse events which may occur during the course of a trial and therefore the
focus lies more on rates and confidence intervals. We developed SAS-macros to calculate measures for safety
analyses such as crude rates, exposure adjusted incidence rates and poisson rate ratios. Graphical methods to
illustrate the course of adverse events over time include Kaplan-Meier time to event plot and mean cumulative
function (1). The application of the SAS macros will be given by an example comparing two different surgical
interventions within a randomized clinical trial (2). The proposed SAS-macros provide measures to evaluate the
safety of an intervention with standardized tables and plots, which can be applied several times over the course
of a trial. We hope this is a contribution to the wish to a DMC “helping them to do their job well” (3).
1. Siddiqui O: Statistical Methods to Analyse Adverse Events Data of Randomized Clinical Trials. J Biopharm Stat;
19: 889-899, 2009. 2. Diener MK, et al: Efficacy of stapler versus hand-sewn closure after distal pancreatectomy
(DISPACT): a randomised, controlled multicentre trial. Lancet; 377:1514-22, 2011. 3. Damocles study group:
A proposed charter for clinical trial data monitoring committees: helping them to do their job well. Lancet: 365:
711-22, 2005.
P85
Multiple Hypotheses Testing and Simultaneous Confidence
Intervals for Multiple Adverse Event Assessment
Zhibao Mi, Joseph Collins
VA Cooperative Studies Program, Perry Point, MD, USA
Adverse effect assessment often involves many clinical symptoms, and each individual may experience multiple
adverse events (AE) in a clinical trial. The common practice for AE analysis compares the proportions between
the treatment arms by forming confidence intervals of the proportional differences or ratios for each individual
AE type. However, this analysis is often not adequate, and sometimes, it may not be methodologically appropriate. We propose to analyze multiple AE data by comparing the multiple AE incidence densities and constructing
simultaneous confidence intervals of both the relative risks (RR) and the hazard ratios (HR) derived from Cox
proportional hazard models. This approach usually involves multiple testing procedures that control for inflation
of type I error, such as using family-wise error rate (FWER) across all AE types. Commonly used procedures
include the Bonferroni-based corrections. These methods are straightforward and easy to implement, but they
are conservative and reduce sensitivity. A less conservative method that considers dependencies among the
various tests is employed to control for type I error by using false discovery rate (FDR). Multiple AE data from a
VA/NIDA double-blinded randomized multi-center clinical trial was used to test the proposed method’s clinical
relevance. From the analysis, among thirty AEs, three of them were significant between two treatment arms using
an unadjusted confidence interval level or significance level; when adjusted for multiple hypotheses testing, no AE
was significant by controlling either FDR or FWER. Among the procedures used, the Benjamini- Hochberg-Yekutieli
procedure (BHY), which controls for FDR, was more powerful when assuming a positive dependency among the
multiple tests than both the Bonferroni-Holm step-down method and the simple Bonferrni procedure by controlling
for FWER. However, the BHY procedure was more conservative when assuming a negative dependency among
the multiple tests.
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P86
Enrollment Propensity Weighting to Assess the
Generalizability of a Randomized Clinical Trial
Marie Gantz, Darryl Creel, Wade Rich, Rosemary Higgins and Abhik Das for the SUPPORT Trial
Subcommittee of the Eunice Kennedy Shriver NICHD Neonatal Research Network (NRN)
RTI International, Statistics and Epidemiology Unit, Research Triangle Park, NC, USA
Randomized trials typically enroll a convenience sample of eligible patients without regard to formal probability
sampling. However, trial results often substantively change clinical practice for the population at large, without
systematic evaluation of the generalizability of results.
The Surfactant Positive Airway Pressure and Pulse Oximetry Trial (SUPPORT) used a 2X2 factorial design to test
different ventilation and oxygenation strategies for respiratory management of extremely premature babies. This
influential and largest of its kind trial demonstrated that a less invasive ventilator strategy may be safe to use
and indicated increased mortality at lower oxygen saturation.
Because intervention started upon delivery, antenatal consent was required, restricting the ability to enroll some
eligible infants, including those who were born precipitously following the mother’s admission. Enrolled babies
had significantly higher socioeconomic status and greater exposure to antenatal steroids compared to the nonenrolled, which raised questions about the generalizability of the trial results. We conducted a sensitivity analysis
by incorporating enrollment propensity weights so the analysis would better reflect the eligible population.
We used Classification and Regression Trees to model enrollment based on maternal and infant characteristics at delivery. Using the groups created by the trees, we constructed enrollment propensity weights. Then we
analyzed the weighted data using models that reduced the variance based on a finite population correction. The
results were largely similar to the original unweighted analysis.
Although weighting to reflect the characteristics of the larger population is common in survey statistics, to our
knowledge the approach has not been used to explore the generalizability of results from randomized trials conducted on convenience samples of eligible patients. When adequate data on the eligible population are available
and enrolled individuals are known to differ from those not enrolled, these methods provide a means to assess
the sensitivity of trial results to such differences.
P87
Sample Size Considerations in Cluster Randomised Trials With Unequal
Clusters – Experience From Two Uk Stroke Rehabilitation Trials
Ivana Holloway, Amanda Farrin
Clinical Trials Research Unit (CTRU), University of Leeds, Leeds, UK
The aim of RCTs is to obtain unbiased estimates of treatment effects to answer the question of interest. In a
cluster randomised trial (CRT), maximum statistical efficiency is obtained with equally sized clusters. In practice,
the ability to achieve such balance is an exception rather than the norm. Two CRTs run by the Leeds CTRU;
TRACS (Training Caregivers After Stroke) and LoTS Care (Longer Term Stroke Care) demonstrate potential solutions to this issue.
Unequal cluster sizes decreases the statistical power in CRTs and leads to underestimated sample size.
In the TRACS trial, all centres were randomised simultaneously and unequal cluster size was not anticipated.
However, the recruitment attrition rates differed by centre and the attrition rate was higher than expected.
Including more clusters, each recruiting the same number of patients, would be an optimal solution. Due to time,
logistics and budget constraints, the number of centres was fixed, so overall more participants were recruited
and the maximum cluster size was capped. In the LoTS Care trial, imbalances were expected; centres were randomised in two phases but the recruitment period was fixed.
In both trials, we re-assessed the sample size calculations and studied the effect of conservative, typical and
extreme cluster size scenarios on the statistical power. Various values of the drop-out rate, design effect and
coefficient of variation were considered and the impact on statistical power was calculated. Using the most
conservative estimates, the overall power dropped by 2-3% when compared to the power based on equal cluster
size. For both trials, statistical power based on equal cluster size was estimated to be 90% - despite unequal
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cluster size, power above 80% was maintained.
Using TRACS and LoTS Care trials as examples, we have demonstrated the importance of incorporating unequal
cluster sizes into calculations of robust sample size for CRTs.
P88
Monitoring Rare Events in a Single Arm Non-Inferiority Trial (111; Cruk/09/011)
Roger A’Hern, Michael Cullen, Sally Stenning, Emma Hall
The Institute of Cancer Research, Clinical Trials and Statistics Unit, Sutton, UK; University Hospitals
Birmingham NHS Foundation Trust, Cancer Centre, Birmingham, UK; MRC Clinical Trials Unit,
London, UK; The Institute of Cancer Research, Clinical Trials and Statistics Unit, Sutton, UK
Background: Futility analysis is common when seeking to demonstrate non-inferiority. When the expected event is
rare careful monitoring is required. 111 is a single group trial in a very good prognosis group of patients, evaluating one cycle of adjuvant chemotherapy (BEPx1) in high risk, stage 1 non-seminomatous germ cell tumours
of the testis. BEPx2 (standard treatment) is associated with a 2% 2-year recurrence rate (Cullen et al. Journal
Clinical Oncology 1996).
Methods: 111 was designed to exclude a 2- year recurrence rate of >=5% and requires 236 patients (based on
exact binomial probabilities). If >=230/236 patients (>=97.5%) are recurrence-free at 2 years then the trial will
conclude that the event rate is <5% (power=80%, alpha=5%). A trivial futility boundary is therefore defined: if >=7
recurrences were observed the trial would be terminated, but more flexibility and guidance for interim monitoring
was sought.
In calculating the recurrence rate, total follow up for each patient is taken into account. As recurrences are
more likely to occur in the early months following treatment, follow up is weighted according to recurrence rates
observed in previous studies. To derive appropriate beta values for each analysis we simulated several design
parameters. A repeated confidence interval approach was adopted. The beta spending function was selected so
that: 1) overall alpha=0.05, beta=0.20 and 2) probability of stopping after 1 recurrence is very low.
Results: The chosen rule was that at each recurrence the estimated rate and its exact confidence interval (CI)
would be calculated. If the lower limit of this CI exceeded 2% then the trial would stop recruiting.
Conclusions: A sequential interim monitoring plan has been developed. This methodology could be adopted in
other studies to ensure that a rare event rate does not exceed a pre- specified threshold.
P89
The VACS Index Score as an Alternative Endpoint in HIV/AIDS Studies
Tassos Kyriakides1, Sheldon T. Brown2, Amy C. Justice3, Janet Tate3
1VA
Cooperative Studies Program Coordinating Center, VA CT Healthcare System,
West Haven, CT, USA; 2James J. Peters VAMC, Infectious Disease Section, Bronx,
NY, USA; 3VA Connecticut Healthcare System, West Haven, CT, USA
Background: Reliable intermediate outcome measures are needed to assess clinical interventions in the current
era of HIV treatment. We evaluated the performance of the Veterans Aging Cohort Study (VACS) Index that uses
routine clinical biomarkers to predict mortality as a surrogate outcome for randomized clinical trials.
Methods: VACS Index scores were determined from data collected in the Options In Management with
Antiretrovirals (OPTIMA) multi-national study of treatment strategies in patients with advanced HIV (Holodniy,
2011). OPTIMA data were used to validate the use of the VACS Index in a cohort of late-stage HIV patients.
Proportional hazards regression and survival analysis using baseline VACS Index scores and changes in score
during treatment were used to assess the utility of the index as an outcome for future clinical trials.
Results: VACS Index scores at baseline correlated highly with mortality and with time to death in the advanced
HIV patients enrolled in OPTIMA (Kirkwood, 2011; c = 0.749). Baseline score and change in score over 48 weeks
of treatment were equally associated with all-cause mortality (c = 0.783).
Conclusions: The VACS Index accurately predicted mortality and responded to changes in treatment. Measuring
changes in VACS Index scores over relatively short time periods may offer an efficient alternative endpoint for
the design of randomized clinical interventions among patients with HIV.
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References: Holodniy M, Brown ST, Cameron DW, et al. Results of antiretroviral treatment interruption and intensification in advanced multi-drug resistant HIV infection from the OPTIMA trial. PLoS One 2011; 6(3):e14764.
Katherine A. Kirkwood, Tassos Kyriakides, Sheldon T. Brown, Amy C. Justice, Mark Holodniy, Janet Tate, Joseph
Goulet. The VACS Risk Index Responds to Treatment Interventions and is Highly Correlated with and Predictive
of Mortality Events in the OPTIMA study. 2011 Joint Statistical Meetings, Miami, FL, July 30-August 4, 2011.
Session #423.
P90
Responsive Recruitment Strategies to Maximise Recruitment:
Experience From National Uk Stroke Trials
Shamaila Anwar, Suzanne Hartley, Lorna Barnard, Sharon Ruddock, Amanda Farrin
University of Leeds, Leeds, UK
Recruiting to target sample size is key to the success of all research yet continues to pose a significant problem.
Potential barriers are often unknown at the time of securing funding and trials must have processes in place to
identify and respond to these barriers. We present our experience from three UK publically funded multicentre
RCTs of stroke patients and discuss ways in which recruitment strategies were adapted and refined to help
achieve target recruitment.
The main approaches we used focused on the site feasibility and the collection of screening data.
Site feasibility and selection is used to understand the implementation and delivery of trials within existing services and provides recruitment estimates. This process revealed potential capacity and resource constraints which
were subsequently used to facilitate discussion with service providers and allow appropriate allocation of funds.
The recruitment estimates are used to engage in discussion with site during the recruitment phase to identify
further barriers to target. Systematic collection of screening data from time of recruitment is reviewed monthly
and is used to identify trends in the reasons for non-recruitment. This process led to changes in the recruitment
and consent procedures to simplify the patient information and to allow obtaining consent on the same day as
the provision of information. Eligibility criteria are reviewed and amended where clinically and scientifically valid.
Amendments included increasing the time window of recruitment and allowing co-enrolment into other trials.
Barriers to trials achieving target recruitment are multifaceted and trial teams need to be responsive to adapt
trial processes accordingly. We have shown that the systematic identification of barriers from the time of site
selection and during recruitment is essential and allows the trial to adapt to meet target sample size. Data on
the impact of the changes on recruitment will be presented.
P91
Challenges of Recruiting Women to a Clinical Trial of
Treatment for Mucopurulent Cervicitis
Jeannette Lee, Shelly Lensing, Stephanie Taylor
University of Arkansas for Medical Sciences, Little Rock, AR, USA
Mucopurulent cervicitis (MPC), a condition characterized by cervical discharge and inflammation, can be caused
by sexually transmitted infections (STIs). For the 50- 80% of cases where the cause of MPC is unknown, it is
unclear whether empiric antibiotic treatment is effective. Concerns that unnecessary antibiotic use may contribute to antibiotic resistance motivated a noninferiority clinical trial to compare the efficacy of empiric treatment
with two antibiotics, azithromycin and cefixime, with placebo for MPC not attributed to STIs. The plan was to
screen 3,357 women to enroll 772 participants with MPC, based on an estimated MPC prevalence of 23%. In one
year, 577 women were screened at one family planning (FP) and 3 sexually transmitted diseases (STD) clinics,
and 131 (23%) met the definition of clinical MPC: presence of cervical discharge and/or easily induced cervical
bleeding on pelvic exam. Eighty-seven (66%) women enrolled on the trial, 31 (24%) were excluded due to the
presence of an STI, 10 (8%) met another exclusion criterion, and 3 (2%) chose not to participate. The number
of women screened per enrolled participant was 4.6 and 7.0 from FP and STD clinics, respectively. Some entry
laboratory test results were not available until after enrollment. They identified 32 participants who were ineligible
for the study: 24 had positive results for STIs and 8 did not have > 30 WBCs per high power field on the cervical
gram stain, a measure of inflammation. Fifty-five women met all eligibility criteria. The study was terminated due
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to low accrual. Among women with MPC, 42% had one or more STIs, mainly among those enrolled at STD clinics.
Future studies of MPC with unknown etiology should consider recruiting from FP clinics or factor in the high rate
of exclusions due to STIs among women recruited through STD clinics.
P92
Transformation of Regulatory Requirements Into a Training
Curriculum for Investigational Site Teams of Clinical Trials With
Medical Devices in Germany* * Granted by the German Federal Ministry
of Research and Education, Germany, Bmbf Grant 01kn1106
Heike Moenkemann, Andreas Stoehr, Henrike Kolbe, Ursula Paulus
University of Cologne, Clinical Trials Center Cologne, Cologne, Germany, BMBF Grant 01KN1106
In Europe requirements for conducting clinical trials with medical devices were changed fundamentally by the
council directive 2007/47/EC (2007). Meanwhile the international standard ISO 14155:2011 and the German
Medical Device Act have been amended accordingly. All these regulations demand appropriately qualified investigational site teams. A certified training curriculum was established in order to develop the required operational
competence. It was not only harmonized within the German Clinical Trials Center (CTC)-network, but also reconciled with ethics committees as they examine the qualification of investigators. The curriculum was designed as a
two-stage process. It was based on an already well established 2-day training course for investigators focusing on
ICH-GCP E6 and German regulations for clinical trials with medicinal products. This course was supplemented by
an advanced half-day course for medical devices. This half-day course concentrates on the characteristic requirements of the federal authority and ethics committees, the newly set up electronic application procedure, and the
electronic SAE- reporting obligation of sponsor and investigators. In the next step we established a standalone
training course qualifying investigators for trials with medical devices without previous knowledge of conducting
clinical trials. The curriculum covers all regulatory specifications, good clinical practice, uses incorporated didactic quizzes to upgrade learning effects, and considers the characteristics of Investigator Initiated Trials (IITs).
With their know-how and academy CTCs are important components in the field of qualifying for conducting clinical trials with medical devices even beyond the scope of IITs. Our report will show the challenges of developing
these certified training courses for investigational site teams. And it presents the experiences of the CCT Cologne
conducting these courses and the evaluation by attending investigators.
P93
Methodology Matters: Spotlight on the Network of Hubs
for Trials Methodology Research (htmr) in the Uk
Emily Crowe
on behalf of the Network of Hubs for Trials Methodology Research
The Network of Hubs for Trials Methodology Research (HTMR Network) was established by the Medical Research
Council to create a UK- wide regionally distributed research resource to improve the design, conduct, analysis,
interpretation, and reporting of clinical trials. Consisting of eight Hubs, the HTMR Network possesses methodological expertise and fosters links with clinical trials units and other methodological groups in universities, the
National Health Service, industry and relevant professional bodies.
The HTMR Network aims to (1) promote and fund high quality collaborative methodological research, both
between Hubs and with other groups, UK-wide and internationally; (2) provide methodological advice to the clinical trials community; (3) encourage the implementation of the most effective and appropriate methodological
practice, for example by providing education and training; and (4) work with stakeholders, in particular to agree
on shared priorities for research and guidance and to advocate for improvements in the conduct of clinical trials.
The HTMR Network has funded several successful projects involving the Hubs and other groups, including
COMET (Core Outcome Measures in Effectiveness Trials), DIRUM (Database of Instruments for Resource Use
Measurement) and workshops on topics such as randomised trials in surgery and on recruiting children to trials. We are working on methodological issues raised by stakeholders through consultation and provide the
Methodology Advisory Service for Trials (MAST), a “second-line” advisory service for clinical trials units and
Research Design Services in the UK.
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P94
Evaluation of a New Institutional Clinical Research Monitoring
Program for Investigator Initiated Studies
Jami Jackson, Bonnie Edelman, Collette Houston, Jane Myers,
Joseph Lengfellner, Roy Cambria, Elsa Hwang, Marie-Antoinette Cesar,
Debbie Marcellus-Duval, Michelle Thomas, Saray Simo, Jennifer Tom
In February 2010, the Office of Clinical Research (OCR), at Memorial Sloan-Kettering Cancer Center (MSKCC),
established an institutional clinical research monitoring program for MSKCC-sponsored studies.
Although MSKCC has an extensive Data and Safety Monitoring plan which includes institutional and clinical
department auditing, the focus on protocol compliance auditing only comprises a small percentage of the institutional portfolio in a given year (<15%). The new clinical research monitoring program focuses on in-house,
investigator-initiated, MSKCC-sponsored studies, for which no outside organization provides monitoring or oversight. The goal of the monitoring program is to provide “real time” oversight of approximately 40% of MSKCC
investigator initiated studies.
In order to achieve this goal we developed the following: a set of criteria to evaluate protocols in our institutional
portfolio for monitoring priority; documents to conduct protocol compliance, data verification, and regulatory documentation review; and guidelines for selection of participants to be monitored per visit. In addition, we identified
department monitors and established written procedures for them to follow in the program.
To determine the outcome of the monitoring visits, we created a rating system. Consistently high quality monitoring visits for a particular protocol would allow transition of that protocol off the monitored list and allow for us
to initiate review of another protocol. Guidelines for serious and unresolved issues were also established which
included suspension of new accruals for continuous unacceptable ratings. To keep a record of the monitoring
visits, an access database to collect the summary letters of each visit and enter relevant data was created.
In this poster presentation we will review our evaluation of the program and determine whether we are achieving
our goal of “real time” oversight of 40% of our investigator initiated studies. We will also outline the challenges
we encountered and methods we are developing to improve the program.
P95
Lessons Learned: Effective Training Strategies for Electronic Data Capturing
Siobhan Tobin, Asma Qureshi, Johanna Sanchez, Dalah Mason, Denice Feig, Elizabeth Asztalos
Metformin in Women with Type 2 Diabetes in Pregnancy Trial (MiTy) is a multi-center, double masked, randomized
placebo-controlled trial for pregnant women with type 2 diabetes. With 500 recruits expected from 25 participating centers across Canada, MiTy seeks to determine the effect of the addition of Metformin to a standard regimen of insulin on perinatal morbidity and mortality. Study sites are required to record specific outcomes for each
study participant in prenatal visit forms every four weeks, based on gestational age at randomization. In order to
accurately capture the complex nature of this large amount of data, it was decided that electronic data capture
(EDC) would be more effective than paper data collection.
Since EDC is a recent system, a strategy for disseminating user training was required. Collaborators participated
in a three hour training session in which they were guided through a simulation that involved entering patient data
into an EDC program. Due to differences in technical skills, abilities and learning styles, it was evident that the
majority of the participants did not gain a comprehensive knowledge of how to use the EDC program. Following
this, three separate strategies were implemented to provide more effective training.
First, an EDC test website was created in which collaborators could enter simulated data to become proficient
with the system. This allowed collaborators to familiarize themselves with the program according to their own skill
level and pace. Next, a section in the Study Manual was created with step-by-step instructions and troubleshooting for further clarification. Lastly, email and phone support was offered to remedy problems that could not be
resolved by the Study Manual.
These strategies proved both cost-effective and successful in providing collaborators with comprehensive EDC training.
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P96
Factors Influencing Recruitment in Clinical Trials
Katrien Oude Rengerink1, Lotty Hooft2, Patrick Bossuyt3, Ben Willem Mol1
1Academic
Medical Center, Obstetrics and Gynaecology, Amsterdam, the Netherlands; 2Dutch
Cochrane Centre, Academic Medical Center, Amsterdam, the Netherlands; 3Academic Medical
Center, Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam, the Netherlands
INTRODUCTION Patient recruitment in clinical trials often takes longer than expected. Trials with slow recruitment are more costly and an insufficient sample size leads to indecisive conclusions. We identified factors
influencing recruitment in clinical trials. DESIGN We sent a questionnaire to principle investigators of all 1130
trials prospectively registered in the Netherlands Trial Register with an expected date of completing recruitment
between 2005 and 2010. We used logistic regression analysis to assess whether characteristics of the trial
or the principle investigator were associated with successful recruitment, i.e. 80% of the targeted number of
patients was recruited within the planned time. RESULTS Of 392 trials questionnaires were completed. For these
trials 232,707 persons were to be recruited. In half of the trials recruitment was unsuccessful. Although 42%
of the trials were extended for ?6 months, when closing recruitment 46% still had recruited fewer patients than
originally intended. Of the investigators 67% stated recruitment was more difficult than expected. Factors univariably associated with unsuccessful recruitment were: clear responsibilities for recruitment, investigator not PhD,
multicenter trial, presentation at start for recruiters, newsletter for recruiters, pocket cards, email at start of the
trial and a low expected number of randomizations per month. In multivariable analysis, adjusted for potential
confounders, associated with recruitment were having a PhD (OR 0.37; 95% CI 0,17-0,83) and giving a presentation at start of the trial for recruiters (OR 0.24; 95% CI 0.09-0.64) - the latter might be indicative for complexity
of a trial. CONCLUSION Investigators frequently overestimate recruitment success when starting a trial. Although
we identified factors associated with recruitment, we are unable to make general recommendations for improving
recruitment. A possible limitation of this study is the risk for selective responses and unmeasured confounders.
Investigators should be aware of potential recruitment difficulties when starting a new trial.
P97
Role of Glucocorticoid Receptor SNPs in Receptor Function and Metabolic Disease
Lisa Murphy2, Christine Jewell1, Stavros Garantziotis1, John Cidlowski1
1National
Institute of Environmental Health Sciences, NIH, DHHS, Research
Triangle Park, NC, USA; 2SRA International Inc., Durham NC, USA
The role of glucocorticoid receptor single nucleotide polymorphisms (SNPs) in receptor function and metabolic
disease is being studied at the National Institute of Environmental Health Sciences (NIEHS). This in vivo and
in vitro observational gene association study investigates functional relevance of SNPs in the NR3C1 gene.
Individuals with and without functionally relevant SNPs are identified and recruited from the Environmental
Polymorphism Registry (EPR). The EPR is a DNA biorepository of over 15,000 participants developed at NIEHS to
help researchers better understand relationships between environmental exposures, genetic susceptibility and
disease. The primary objective is to investigate in vivo the role of hGR SNPs (hGR9b A3669G, hGR N363S) in steroid responsiveness using dexamethasone and comparing serum cortisol levels by genotype. Initial comparisons
indicate some hGR9b A3669G carriers are resistant to dexamethasone. The secondary objective is to investigate
the role of hGR SNPs (hGR9b A3669G, hGR N363S) in human steroid responsiveness by comparing gene expression profiles of macrophages exposed ex vivo to corticosteroids. A pilot microarray study on macrophages without
hGR SNPs revealed that although there is great variability in gene regulation between individuals, treatment with
dexamethasone significantly altered gene regulation. These initial study results suggest functional relevance of
hGR SNPs in the NR3C1 gene. The study is also the first EPR study conducted at the NIEHS Clinical Research
Unit (CRU) and will help define and enhance operations of future EPR studies, including recruitment strategies.
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P98
Ensuring Successful Adherence to Study Requirements in a Multi-Centre Study
Asma Qureshi, Siobhan Tobin, Johanna Sanchez, Dalah Mason, Denice Feig, Elizabeth Asztalos
Metformin in Women with Type 2 Diabetes in Pregnancy Trial (MiTy) is a multi-centre, double-masked, randomized
placebo-controlled trial for pregnant women with type 2 diabetes. With 500 recruits expected from 25 participating centres across Canada, MiTy seeks to determine whether the addition of Metformin to their usual insulin regimen, will decrease the incidence of adverse perinatal outcomes. Study sites are required to schedule prenatal
visits for study participants every four weeks, based on gestational age at randomization.
At MiTy prenatal visits, collaborators are required to supply study drug, distribute glucose strips, take specific
blood tests, measure serum creatinine, download glucometer readings, and count pills to verify patient compliance, in addition to routine standard care. Prenatal visit information is then entered on the prenatal visit form
following each patient appointment. Specific strategies were needed to help collaborators keep track of prenatal
visit schedules; identify which tasks were required to be completed at each visit; and to indicate when to complete the prenatal forms. Therefore, several tools were developed to ensure successful adherence to the study
requirements.
A study manual was created to explain the specifics on how to manage the trial. This included a timeline with
descriptions of tasks to be completed at particular stages during the patient’s pregnancy, as well as checklists
of tasks to be completed at each appointment. Prenatal visit appointment schedules were programmed upon
randomization, notifying study coordinators of the exact week to schedule prenatal visits according to gestational
age. Appointment reminders were emailed one week prior to the appointment, along with consistent email and
telephone communication. Furthermore, centres receive tips and reminders through the monthly MiTy newsletter,
group teleconferences, and regional meetings.
This presentation will share successful approaches used to ensure adherence to study requirements.
P99
Who Can Recist?: the Evolution of Solid Tumor Response Criteria
Bingyan Wu1, Daniel J. Quinn2, Donna E. Levy1
1Rho
Inc., Chapel Hill, NC, USA; 2Partners Healthcare, Boston, MA, USA
Assessment of the change in tumor size in response to treatment is critical in the evaluation of anti-cancer
agents. The purpose of this presentation is to review the status of standardized solid tumor response criteria
published since the early 1980s including WHO criteria, RECIST 1.0, RECIST 1.1 and PERCIST 1.0. The existing
criteria (WHO, RECIST 1.0, RECIST 1.1) will be compared in terms of number of target lesion requirement at
baseline, lymph node usage in the calculation of tumor size, the requirement of confirmatory responses as well
as other specific criteria used in the existing guidelines. Similarities and differences between the tumor assessment criteria will be illustrated using specific examples. Consideration of unidimensional and bidimensional measurements as well as the possibility of three-dimensional analyses will be discussed. New imaging techniques
such as FDG-PET and MRI in tumor assessment as well as treatment classification, specifically cytostatic, will
be examined. Non-measurable disease at baseline will also be considered with respect to each criterion. Other
discussions will include “modified RECIST” and why it should be avoided. The limitations of standardization and
possible future development will also be discussed.
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P100
Partners in Research: Effective Collaboration Between a National Clinical
Trial (today Study) and Oklahoma-Based Multi-Tribal Health Boards
Jennifer Chadwick, Marisa Payan, Mary Daniel, Julie Erb-Alvarez, Beverly Felton,
Sohail Khan, Bobby Saunkeah, David Wharton, Kenneth Copeland
University of Oklahoma Health Science Center, Oklahoma City, OK, USA; George Washington University, Rockville,
MD, USA; OKC Area Indian Health Service, Oklahoma City, OK, USA; Absentee Shawnee Tribe, Little Axe, OK, USA;
Cherokee Nation of Oklahoma, Tahlequah, OK (USA); the Chickasaw Nation, Tishomingo, OK, USA; Choctaw Nation
of Oklahoma, Durant, OK, USA; and University of Oklahoma Health Science Center, Oklahoma City, OK, USA
Background: Historically, there have been significant barriers to conducting research in tribal communities,
including a lack of understanding of American Indian (AI) culture and research. Methods: Spring of 2002,
University of Oklahoma Health Science Center (OUHSC) and four AI Tribe/Nations with Institutional Review
Boards (IRB) (Absentee Shawnee Tribe, Cherokee Nation, the Chickasaw Nation, Choctaw Nation) and OKC Area
Indian Health Service (IHS) IRB (collectively AI Partner(s)) proposed to participate in one of the largest pediatric
diabetes research trials supported by the National Institutes of Health (NIH). This venture required an agreement between AI Nations and academic university addressing essential elements: trust, collaboration, and successful outcome. Results: The four AI Tribe/Nations executed a Memorandum of Agreement (MOA). The MOA
stipulated: 1) AI Coordinator hired to foster relationships, assist with recruitment, and facilitate pre- review by AI
Partners of publications containing AI descriptive data. Sixty-one (61) AI patients were screened and forty (40) of
those patients randomized into the TODAY Study. 2) Establish a committee comprised of AI Partner representatives to review publications. The committee meets for monthly publication updates with regular communication
between meetings. The committee has met approximately 20 times and has reviewed approximately 50 items.
Presentation will describe the efforts in retaining tribal partnerships including barriers that arose and resolutions.
Conclusions: After 9 years, 4 AI IRBs and OKC IHS IRB have created and maintained a successful collaboration
with an academic university in a large clinical trial. This multi-tribal research partnership is an excellent model of
how community and multi-ethnic collaborative research can be effective.
P101
Minority Cancer Survivors’ Attitudes and Experiences
Related to Participation in Cancer Clinical Trials
1
Margaret M. Byrne , Jamie L Studts, Susan L. Schmitz1, Andrea Vinard1, Martha Gonzalez1, Heraldo
D’Almeida1, Colleen Bauza1, Nicole Whitehead1, Sue Stableford2, Angie Fagerlin3, Sarah Hawley3
1University
2University
of Miami, Miami, FL, USA; Studts: University of Kentucky, Lexington, KY, USA;
of New England, Portland, ME, USA; 3University of Michigan, Ann Arbor, MI, USA
Purpose: To ascertain the experiences and perceptions of participation in cancer clinical trials by Hispanic and
Black cancer survivors.
Methods: As part of a larger study to develop a decision aid for participation in cancer clinical trials, we conducted semi-structured interviews with English-speaking Hispanic (15), Spanish- speaking Hispanic (15), and Black
(15) cancer survivors. We employed quantitative content analysis to code responses to 16 specific questions
based on transcripts from the interviews.
Results: The average age of participants was 56.0 (SD 10.6) years; 93.3% were female, with most having had
breast cancer (66.7%). Years since diagnosis ranged from 1-16, with an average of 3.3 (SD 3.0). Only 4 had
been asked to participate in a clinical trial, and of these, 3 had joined a trial. Although only 4 had talked with a
provider about participating, 23 (54.8%) wished that such a conversation had happened. In addition, 32 (71.1%)
said that they would be willing to participate in a trial, and another 8 (17.8%) said that they may be willing.
Almost all, 97.8%, said that it would be helpful to hear other cancer patients’ experiences with clinical trials.
However, most (81.8%) stated that it would not make any difference if the people relaying the experiences were
of the participant’s own race/ethnicity. Rather, information from someone with their own type of cancer was
viewed as very important by 36%.
Conclusions: Although few participants had even talked about clinical trials with their health care providers, most
cancer survivors expressed willingness to participate. These findings highlight the need for discussions about
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clinical trials between physicians and patients. Increasing cancer patients’ knowledge and self-efficacy to discuss
clinical trials with healthcare providers, for example through a decision aid, may lead to a much needed increase
in participation rates.
P102
Development of a Decision Aid to Improve Minority Cancer
Patients’ Decisions About Participating in Clinical Trials
Margaret M. Byrne1, Jamie L. Studts2, Susan L Schmitz1, Andrea Vinard1, Martha Gonzalez1, Heraldo
D’Almeida1, Colleen Bauza1, Nicole Whitehead1, Sue Stableford3, Angie Fagerlin4, Sarah Hawley4
University of Miami, Miami, FL, USA; 2University of Kentucky, Lexington, KY, USA; 3University
of New England, Portland, ME, USA; 4University of Michigan, Ann Arbor, MI, USA
Purpose: Participation in cancer clinical trials is very low, particularly for minority cancer patients. The goal of this
research was to develop a web-based decision aid to improve minority cancer patients’ decision making about
whether to participate in a clinical trial.
Methods: Steps in developing the decision aid were: a) collecting information on barriers and promoters of participation; b) developing a theoretical framework to conceptualize the decision aid components; c) using cognitive
interviewing to pilot test the decision aid; and d) testing the decision aid to determine its effects on attitudes
and knowledge about cancer clinical trials. Information was collected using 3 complementary approaches: a) data
from a telephone survey of 1100 cancer survivors; b) a literature review; and most importantly, c) semi-structured
interviews with cancer survivors. All participants were either Hispanic or Black.
Results: For the semi-structured interviews, 45 participants were recruited. The information from the 3 sources
was used to develop the KEV (Knowledge, Empowerment, and Values) framework for the decision aid. The website was developed, and successfully pilot tested with 8 participants. Currently, we are assessing the effectiveness of the decision aid to improve patients’ knowledge about clinical trials, empower them to talk with their
health care provider about trials, and clarify their values and preferences related to trials participation in 100
participants. Assessment of the effect of the decision aid is done by comparing knowledge, attitudes, and decisional conflict about clinical trials before and after viewing the decision aid.
Conclusions: While quantitative data on the effectiveness and acceptability of the decision aid is not yet available, feedback from the participants has been extremely positive. Participants knowledge increases, and many
state that they wish they had had such an instrument when they were first diagnosed. Our ultimate goal is to
make this decision aid widely available.
P103
Developing and Maintaining Standard Operating Procedures
for a Multi-Trial Data Coordinating Centre
Cerisé Robinson, Johanna Sanchez, Dalah Mason, Elizabeth Asztalos
Centre for Mother, Infant, and Child Research, Sunnybrook Research Institute, Toronto, Ontario, Canada
The Centre for Mother, Infant, and Child Research (CMICR) was established to improve the health of women and
their children through clinical research and education. As the data coordinating centre for several international
randomized controlled trials (RCTs), it is imperative that all trial operations are completed in a consistent manner to ensure maintenance of a quality management system. Thus, in adherence to Good Clinical Practice (GCP)
guidelines, CMICR uses written standard operating procedures (SOPs) in its daily operations. In a team setting, it
is especially important to have a standard set of detailed SOPs, along with clear, well-established rules to follow.
This allows for the management of various aspects of the organization to be structured and easily maintained.
In previous years, each trial team created and maintained their individual SOPs. This resulted in varying procedures between each study and a lack of detail, which was addressed in the new format. Various methods were
employed to identify the most effective way to achieve uniformity of all SOPs. A staff member was designated the
specific role of standardizing all trial SOPs to ensure consistency. The existing SOP system was reviewed over a
three month period to assist in developing an improved structure. This new structure includes a revised coding
system, as well as improved methods for archiving and updating task-specific SOPs. A template was also created
to ensure a simple, easy-to-read layout of all newly established SOPs. In addition, to assist in the implementation
149
of the new SOP system, specific guidelines were established on how to create an SOP document. All SOPs are
submitted to the designated staff member for review, and are made accessible to all staff. These revisions to
the SOP system have addressed inconsistencies, and created cohesion throughout the organization.
P104
Developing an Effective Site Feasibility Questionnaire
for the Site Selection Process
Johanna Sanchez, Dalah Mason, Elizabeth Asztalos
The Centre for Mother, Infant, and Child Research, Sunnybrook Research Institute Toronto, Ontario, Canada
The Centre for Mother, Infant, and Child Research (CMICR) is the data coordinating centre and administrative
site for several large, multi-centre, international randomized controlled trials that aim to improve clinical practice
and the health outcomes of women and their children. CMICR has established an international collaborative
group of research sites that may simultaneously participate in several CMICR-coordinated trials. It has become
evident that successful recruitment and protocol adherence of a site in one CMICR-coordinated trial does not
guarantee its success in another, and in trials with limited budgets and timelines, identifying suitable sites is
vital. To assist in the site evaluation and selection process, CMICR developed an improved trial-specific Site
Feasibility Questionnaire (SFQ).
The revised SFQ developed by CMICR includes four main sections. The first, “Study Background”, includes the
research summary, inclusion/exclusion criteria, and outlines the study requirements. In the second section,
“Site Information”, sites are asked to provide information about their experience and performance in other
research trials, resource information (i.e. research staff, facilities, equipment), and the total number of patients
that meet the study inclusion/exclusion criteria annually. The third section, “Study Protocol Requirements”, is
important in determining whether the site will be able to adhere to the study protocol. Sites are asked about their
local standard of care and whether they will be able to follow the schedule of events and carry out all the required
tasks. The final section covers recruitment topics and sites are asked to explain any anticipated difficulties with
the trial. Once the centre has reviewed the protocol and considered all survey responses, the final requirement
is to provide their expected annual recruitment goal.
The presentation will share how to write an effective Site Feasibility Questionnaire that will help in site evaluation
and selection process.
P105
Recruitment and Retention of Trial Subjects in the 21st
Century: Insights From Experience Fom Conducting Several
Recent Large International Trials in Cardiology
Susan Chrolavicius
McMaster University Hamilton, Ontario, Canada
Ensuring timely recruitment of appropriate subjects into clinical trials is not only a measure of study discipline,
it provides economic efficiencies and also ensures that study results will be relevant since they are reflective of
current practice. We have developed processes to ensure the timely recruitment of appropriate subjects and will
provide suggestions and examples from several large international trials involving over 500 hospitals in more
than 40 countries. Not only is timely recruitment essential to success of the trial, adherence to the trial intervention and complete follow-up on all patients is critical. We have developed tools to encourage compliance and
prevent “potential lost to follow-up” . We will also present examples of specific impediments to follow-up. Among
these examples is recent privacy legislation enacted in some countries which has fostered an environment of
uncertainty and caution at many investigating sites. There is a perception that individual rights can take precedence over the completeness and accuracy of the clinical trial results. Site personnel have refused to follow any
patient who has “withdrawn his/her consent”. We will demonstrate how we have been able to overcome this
obstacle in most countries by clearing up misconceptions and by re- educating the investigating site personnel.
150
P106
Monitoring Blood Sample Collection and Shipment in a Publicly Funded
Post Thrombotic Syndrome (PTS) Randomized Controlled Trial (RCT)
Adrielle H. Houweling, Vicky Springmann, Stan Shapiro, Susan R. Kahn
McGill University, Montreal, Quebec, Canada
Successful blood sample collection in multi-center trials could be achieved through the implementation of a trialspecific Quality Assurance Monitoring System (QAMS) that ensures the high-quality sample retrieval needed for
optimal biomarker measurement. In the SOX Trial, a Canadian Institutes of Health Research and Heart & Stroke
Foundation funded multi-center RCT of active vs. placebo stockings to prevent PTS in 803 patients with acute
proximal deep vein thrombosis (DVT), blood specimen samples were collected within the first 6-mths of diagnosis to evaluate whether biomarkers reflective of inflammation, coagulation activation and genetic thrombophilia
influence PTS development. At baseline, 1 and 6-mth visits, blood samples drawn from consenting patients were
processed, aliquoted into microcentrifuge tubes, frozen at -80°C and batched from 24 study sites to the Trial
Coordinating Centre (TCC) for central storage according to study Standard Operating Procedure (SOP) instructions.
Specimens were then assessed for quality based on these standards: sample recovery (SR), correct sample type
(CST), adequate sample volume (ASV) and correct tube labeling (CTL). For buffy-coat collection, all 4 criteria were
met for 79% of samples: 99.2%, 79.9%, 99.8% and 100% for SR, CST, ASV and CTL standards, respectively.
For platelet-poor plasma collection, all 4 criteria were met for 94.3% of samples: 97.7%, 98.2%, 99% and 100%
for SR, CST, ASV and CTL, respectively. In general, we noted that sites with lower overall quality were those with
a lower patient retention rate, frequent coordinator turnovers, and sample processing left to study personnel.
Development of site-directed SOPs followed by routine TCC quality checks for sample integrity are two economical ways to implement a successful QAMS in budget-limited government-funded studies; these mechanisms help
safeguard sample quality, reduce missing data and enhance credibility of study results. Additional site-specific
monitoring may also be warranted for study sites with poor performance and limited resources.
P107
Challenges and Strategies in the Start-Up Phase of Large,
International Clinical Trials in Cardiac Surgery
Jessica Vincent
Population Health Research Institute, Hamilton Health Sciences/ McMaster University, Hamilton, Ontario, Canada
There are unique challenges faced in the conduct of clinical trials in the relatively new research field of cardiac
surgery. Several strategies have been implemented in the start-up phase of a large, international, publicallyfunded clinical trial in cardiac surgery (the Steroids in Cardiac Surgery (SIRS) trial) to address these challenges.
Currently, the largest published clinical trial in cardiac surgery is the ROOBY trial which recruited 2203 patients
from 18 centers. SIRS will recruit 7500 patients from approximately 85 centers in 18 countries, making it the
largest clinical trial conducted in cardiac surgery to date (recruitment as of Nov. 30, 2011 was 1919). From the
experience of starting-up SIRS, many challenges were identified and strategies have been used which can be
translated to other research fields, particularly to trials being conducted in new disease research areas.
The most common challenges faced during the start-up phase of a large, international clinical trial are: adhering
to project timelines; dealing with various country-specific regulatory issues; identifying appropriate clinical sites;
and ensuring proper study conduct for the duration of the trial. In SIRS, there were the added unique challenges
of being a study in a fairly new clinical research field with many novice investigators and without an established
global cardiac surgery research network, as well as having limited funding. These challenges and the implemented strategies used to address these obstacles have been outlined in Table 1.
Conducting global clinical research is complex and involves many hurdles, especially in a relatively new area such
as cardiac surgery. SIRS will hopefully pave the way for future large clinical trials in cardiac surgery by building a
global network of investigators, and by developing tools to meet the challenges (particularly in the start-up phase)
which are crucial to the successful and efficient coordination of a large clinical trial.
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P108
Transitioning Paper to Electronic Case Report Forms Mid-Study
From One Clinical Research Organization to Another
Denise King, Traci Clemons, Diane Brandt
EMMES Corporation, Rockville, MD, USA
Under the Best Pharmaceutical for Children Act (BPCA), the protocol “Use of Lorazepam for the Treatment of
Pediatric Status Epilepticus: A Randomized, Double- Blinded Trial of Lorazepam and Diazepam,” changed from
one Clinical Research Organization (CRO) to another CRO mid- study. The transition included moving from paper
to electronic case report forms (CRFs).
The transition involved four steps: 1) transferring the datasets from the previous CRO’s data format to the new
data format, 2) creating a user-friendly electronic data capture system that included all required fields and any
new fields desired by the sponsor, 3) accurately mapping and uploading the data from the previous CRO to the
new system and 4) transitioning the sites to the new system. To streamline these processes, collaboration with
the previous CRO, the study sponsor, and the coordinators performing the data entry was essential. Building the
electronic data system required identifying all required fields, determining the format of data fields, changing free
text fields to drop-down fields, adding new fields requested by the sponsor, obtaining any data quality checks
implemented by the previous CRO, and assuring sponsor approval for all changes made to the data collection
procedures. All uploaded data required extensive quality control to assure the accuracy of the mapped data.
Site transition involved creating a plan for the collection of ongoing data while the electronic system was in
process, including reporting of serious adverse events and protocol deviations, and training the sites on the
new system. Soliciting input from the site coordinators on the data collection process was valuable in improving
efficiency of and satisfaction with the new data collection system.
P109
NIAID Auditing Services Program (NASP): Providing Worldwide
Quality Assurance Audits of DAIDS Monitoring Functions
Jan S. Peterson1, Suheila Abdul-Karrim2, Michael Fillius1, E. Michelle Bush1
1The
EMMES Corporation, Rockville, MD, USA; 2Johannesburg, South Africa
Background: The National Institute of Allergy and Infectious Diseases (NIAID) invests heavily in the conduct of
clinical trials benefiting public health. For the Division of AIDS (DAIDS), trial quality is managed in part through
a risk-based monitoring program performed by contract monitors. Prior to 2010, these monitoring functions
were not subject to independent review. In 2010, DAIDS began sponsoring an independent auditing program to
assess the quality and effectiveness of the contract monitoring. We report on the development and progress of
these quality assurance (QA) audits during the first 2 years of the auditing contract, where ~90 QA audits were
conducted, and on their preliminary impact on the DAIDS monitoring program.
Methods: Using an independent contractor for the NIAID Auditing Services Program (NASP), QA auditors sampled
monitoring reports and performed on-site audits at selected clinical research sites (CRSs). About 12 CRSs were
chosen quarterly based on several qualifying criteria, including monitoring report content and risk level of protocols. Routine NASP audits are characterized primarily as performance audits rather than Good Clinical Practice
(GCP) audits, since DAIDS procedures for the monitoring contractor are very focused due to the risk-based monitoring program design. Teams of NASP auditors based in the United States, South Africa, and Brazil were trained
on DAIDS-specific procedures and the same instructions provided to monitors. Auditors reviewed a sample of
the same materials that were previously monitored, and reported directly to the DAIDS sponsor on any findings.
Results: From over 740 CRSs in nearly 50 countries, over 1170 on-site monitoring visits were performed at about
233 CRSs in 21 countries over the past 2 years. Sampling those visits, ~90 NASP audits were completed in 14
countries, with no critical and few major findings observed. Several findings led directly to significant improvements in DAIDS monitoring policies and procedures.
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P110
Provision of Coverage Analysis in Multi-Site Clinical Trials Aids All
Sites and Particularly Smaller, Community-Based Practices
Kelly Willenberg, Laurence Baker
Chesnee, SC, USA; University of Michigan, MI, USA
Over the past decade, the administrative burden of clinical trials has become an issue of national concern. One
significant component of the bureaucracy is ensuring compliant billing practices.
Where a coverage analysis at a single site may take as many as eight hours to complete, the inefficiency of this
being repeated by every site in a multi-institution clinical trial highlights an unnecessary burden.
One cooperative group, SWOG, piloted providing a coverage analysis to its sites and found the utility of doing so
most benefited lower-accruing sites, who reported the most time spent completing analyses for trials they participated in and with the least resources to do so. The pilot also revealed that some sites had not yet adopted
a practice of completing a coverage analyses, pointing to the increased risk of clinical billing fraud. With the
future of cancer research diverging from standard of care and into innovative new directions such as biomarker
discovery, the current federal funding system for cancer research requires processes to ensure compliant billing.
In multi-institutional clinical trials, having the sponsor providing a coverage analysis using national guidelines
and standards adds efficiency to an administratively over- burdened clinical trial management process. Further,
the provision of a sponsor-provided coverage analysis particularly benefits the lower-accruing sites in reducing
the risk of fraudulent billing. Cancer research sponsors can easily support success and continued participation
by community practices by providing coverage analyses.
Project supported by NIH funded grants CA032102 and CA037429
P111
Implementation of Likelihood-Based Continual Reassessment
Method Designs in Dose Finding Trials
Emily Van Meter, Stacey Slone, Heidi Weiss, Jeri Reynolds, Jay Hayslip
University of Kentucky, Markey Cancer Center, Lexington, KY, USA
Many dose finding designs including the continual reassessment method (CRM) have been shown as statistically
advantageous over traditional up down methods such as the ‘3+3’. However, these designs have been slow to
gain popularity as they can be computationally intensive, often need specialized software, and require additional
input during protocol development. We present a practical application that utilizes the likelihood-based CRM to
monitor an ongoing investigator initiated ‘3+3’ phase I trial for lymphoma patients at the University of Kentucky
Markey Cancer Center. During this trial, dose-limiting toxicities were redefined and there were concerns about the
flexibility of the ‘3+3’ to accommodate these changes mid-cohort. Since the CRM accommodates various cohort
sizes and makes use of all accrued patient toxicity information to estimate the dose closest to the maximum
tolerated dose at any point in the trial, we monitored the ongoing trial to confirm dose escalation rules according
to the ‘3+3’ were appropriate. Additionally, we compared operating characteristics of various CRM designs that
accommodate ordinal or binary toxicity grades. We describe what information was needed to construct the initial
design as well as how current accrued toxicity data was included in the model to estimate the next dose needed,
using the R package ordcrm. Interestingly, this monitoring exercise gave clinical investigators, biostatisticians,
and other research team members the opportunity to learn more about the likelihood-based CRM and gain information regarding the logistical issues and advantages of applying this design in practice. Not only did this verify
that the CRM is feasible to implement and incorporates more toxicity information throughout the trial, but it has
educated clinical research team members on this alternative dose finding design and has sparked interest in
using the likelihood-based CRM as the design in future trials.
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P112
Application of Different Randomized Phase II Trial Designs in a Breast Cancer Trial
Heidi L. Weiss, Emily Van Meter, Bin Huang, Li Li, Suleiman A. Massarweh
Markey Cancer Center, University of Kentucky, Lexington, KY, USA
The utilization of randomization in phase II trials is increasingly being recommended in the evaluation of anticancer therapies prior to pursuing larger phase III trials. Randomized comparisons offer protection against selection
bias and are needed when historical control data are not available for designing a new trial. Several candidate
randomized designs can be considered depending on trial design and objectives. A phase II randomized trial
in breast cancer of two candidate targeted therapies is planned in patients with locally advanced or metastatic
breast cancer. The study endpoints are tumor response rate and progression-free survival (PFS). We consider
different study designs to determine patient number requirements and assess feasibility and performance of the
trial design under different scenarios. Specifically, we utilize i) selection design (design A); ii) two-stage selection
design (design B); iii) screening design (design C); and iv) two-stage randomized phase II trial design (design D).
Given the null and alternative hypotheses assumptions for response and PFS endpoints of this particular breast
cancer trial, patient number requirements are reasonable across all potential trial designs. Designs C and D offer
more conclusive results given the hypothesis-testing strategy of these designs. For the particular regimens and
clinical problem being addressed in this phase II breast cancer trial, we favor the use of designs C or D which,
although requiring slightly bigger patient numbers, affords more definitive conclusions on whether to proceed
to a larger phase III trial. It is important to carefully assess a particular clinical trial scenario to decide not only
whether to proceed with a single arm, historical control design but also the most appropriate randomized design
if the latter is of interest.
P113
Ranking and Selection Design of a Phase IIa HIV Vaccine Clinical Trial in
China With Three Active Arms and Multiple Endpoints of Interest
Steve Self, Yiming Shao
Fred Hutchinson Cancer Research Center, Seattle, WA, USA;
Chinese Center for Disease Control and Prevention, Beijing, China
The Chinese Center for Disease Control and Prevention has successfully completed phase Ia and Ib clinical trials of one of their leading HIV vaccine candidates in 2010. While China is committed to launch its first HIV vaccine efficacy trial, it is important to appropriately choose the most promising vaccine regimen to advance from
Phase IIa safety and immunogenicity testing to later phase efficacy testing. The candidate vaccine regimen is
comprised of 3 DNA prime immunizations followed by one replicating Tiantan Vaccinia (rTV) virus vector boost.
Since the timing of the vector boost will have great impact on the potency and longevity of the vaccine-induced
immune responses, the Phase IIa trial is designed to evaluate 3 different boosting schedules and to select the
best to advance to efficacy testing. For Phase IIa testing, since multiple immunogenicity and safety endpoints
with an ordering of preference are of interest for assessment with respect to clinical and biological relevance and
importance, we propose a ranking and selection design that accounts for multiple endpoints of different types
and allows for equal ranking when vaccine arms are indistinguishable within certain pre-specified margin from
the best arm. Bootstrap-based evaluation of the precision of ranking is performed for each endpoint. In addition,
to prevent advancing any vaccine arms from trials with uniformly week candidates, we require that a vaccine
regimen to be selected must exceed an absolute minimum response probability and/or magnitude threshold.
Sample size calculations are performed to evaluate how many vaccinees per arm are needed to achieve high
probability of correctly selecting the arm with the best combination of 4 endpoints. Preliminary simulation results
show that such selection design performs well. As the distinction between the best arm(s) and inferior arm(s)
becomes larger, the selection accuracy increases. Overall the probabilities of incorrect selection are low.
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P114
US-China Collaborations on the Design of China’s
First Phase IIb HIV Vaccine Efficacy Trial
Steve Self1, Peter Gilbert1, Lena Yao1, Yiming Shao2
1Fred
2Chinese
Hutchinson Cancer Research Center, Seattle, WA, USA;
Center for Disease Control and Prevention, Beijing, China
Chinese Center for Disease Control and Prevention plans to launch the country’s first Phase IIb HIV vaccine efficacy trial in 2014. The candidate vaccine regimen is comprised of 3 DNA prime immunizations followed by one
replicating Tiantan Vaccinia (rTV) virus vector boost. Supported by a supplementary fund to the HIV Vaccine Trials
Network (HVTN) by NIAID, the HVTN statistical team is currently working closely with Chinese researchers on the
design and planning of this trial. The proposed trial design is considered to be reviewed by the Chinese State
FDA in early 2012. We intend to apply a contingency two-stage evaluation of vaccine efficacy (VE), where durability of VE over a range of 0-3 years will be evaluated in Stage 2 if and only if positive VE proximal (e.g. over the
first 18-24 months) to the immunization series is detected in Stage 1. Such a strategy is under consideration for
the design of future HVTN trials in South Africa which may launch after the start of this China trial. To foster the
most synergetic collaboration, we expect to work with a collaborative trial design team including representatives
from trial sponsors, regulators, vaccine developers, manufactures, the Institutional Review Board of China CDC
and key HIV vaccine researchers from both US and China. We acknowledge that the design phase will be highly
iterative in order to finalize various context-driven trial design parameters, including study population, trial endpoint, type I and type II error rate level, trial outcome monitoring type and monitoring plan. Because the primary
HIV vaccine trial sponsors are, for the first time, outside of US and the design expertise is primarily from the US,
experience gained and lessons learned during such a process will be a treasure to share with the international
clinical trial community.
P115
Design of a Neonatal Intervention Based on Joint
Evaluation of Efficacy and Toxicity
Kristi Watterberg, Rosemary Higgins, Abhik Das for the Hydrocortisone and
Extubation Trial Subcommittee of the Eunice Kennedy Shriver National Institute
of Child Health and Human Development Neonatal Research Network
University of New Mexico, Albuquerque NM, USA; Eunice Kennedy Shriver National Institute of Child
Health and Human Development, Bethesda, MD, USA; Research Triangle Institute, Rockville, MD, USA
While many Phase III clinical trials have efficacy and safety endpoints, sample size calculations are generally
based on efficacy, with safety addressed separately as a secondary endpoint. However, the overall clinical effect
often involves efficacy and adverse safety or side effect trade-offs. While joint efficacy and safety endpoints have
often been used for Phase II dose finding studies, such approaches have found limited application in Phase
III trials. Bronchopulmonary dysplasia (BPD) is a leading morbidity in extremely preterm infants, and prolonged
mechanical ventilation increases BPD risk. Dexamethasone can facilitate extubation and decrease BPD incidence, but risk of neurodevelopment impairment (NDI) has led to decreased use. Because preliminary evidence
suggests a better long-term safety profile for hydrocortisone than for dexamethasone, we designed a Phase III
trial to sequentially evaluate the composite hypothesis that hydrocortisone (a) reduces the risk of death or BDP
at 36 weeks; and (b) has an acceptable safety profile for death or NDI at 18 to 22 months. For the two- stage
evaluation using robust Poisson models, we will first estimate relative risk and test the hypothesis that hydrocortisone lowers risk of death or BPD. If this test shows benefit, we will evaluate safety descriptively with safety
considered achieved if either (1) the point estimate of risk of death/NDI is lower for hydrocortisone, or (2) death/
NDI risk for hydrocortisone is increased, but the lower limit of a one-sided 95% confidence interval for the ratio
of death/BPD benefit to death/NDI risk is greater than 4. We describe procedures used for power and sample
size calculations for this two- stage testing approach, present results from those calculations, and compare
operating characteristics of this approach to one previously reported that involves joint testing of the bivariate
death/BPD and death/NDI outcomes using extensions of methods described by Tournoux, et al (Contemporary
Clinical Trials; 28:514).
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P116
A Two Stage Phase II Design Incorporating the Possibility That the Treatment
Effect May Be Restricted to a Biomarker Defined Subgroup : Investigation of
a PARP Inhibitor (Olaparib) in Castration Resistant Prostate Cancer (CRPC)
Roger A’Hern1, Johann DeBono2, Shahneen Sandhu2,
Eleftheria Kalaitzaki1, Martine Usdin1, Emma Hall1
1Clinical
2Department
Trials and Statistics Unit, Institute of Cancer Research, Sutton, Surrey, UK;
of Experimental Cancer Medicine, Institute of Cancer Research, Sutton, Surrey, UK
The objective was to undertake a phase II trial (TO-PARP) to identify the best CRPC patient group(s) to be studied
for sensitivity to olaparib in a phase III trial.
A multistage phase II design has been adopted which has a non-randomised component with response as the
primary endpoint followed by a randomised component with overall survival as the primary endpoint.
Non-randomised component : This allows early progression to a randomised comparison if there is evidence of
a high response rate (50% or more) in unselected patients. Biomarker defined groups are investigated for treatment sensitivity if the response rate is weaker than this.
The first stage involves entry of 30 patients. If 50% or more respond then no more patients will be entered and
the randomised component will be undertaken in unselected patients. If 2 (7%) or less respond then olaparib
will be rejected. If between 3-14 (10%-47%) patients respond then a further 15 patients will be entered. Should
23 (51%) or more respond overall then the randomised component will be undertaken in unselected patients
but if 5 (11%) or fewer respond then olaparib will be rejected. Otherwise with 6-22 responders (13%-49%), biomarker analysis of tissue collected from all 45 patients will be undertaken with the aim of identifying a sensitive
subgroup, with a response rate which is compatible with a 50% response rate. If such a subgroup is found, a
confirmatory single stage 44 patient trial will be undertaken in this group; this will also yield experience of prospective biomarker testing in a multi-centre clinical trial setting.
Randomised component : a phase II assessment of the results generated in the non-randomised part, offering
more secure evidence before proceeding to phase III. 180 patients will be randomised 2:1 to olaparib or an
appropriate standard of care (? 1-sided 10%, power 80%).
P117
Designing Trials for Proving Efficay of Multifunctional Food:
Some Notes on the Need for Multiplicity Adjustment
Federica Zobec, Marco Ghidina, Giada Morpurgo, Ileana Baldi, Dario Gregori
ZETA Research Ltd, Trieste, Italy University of Padova, Padova, italy
Food can have very different effects in terms of health, because of nutrient composition and dosage. In nutritional field, multiple outcomes or multiple hypotheses related to the inter-relationships among those outcomes
are common. This induces several statistical issues related to the inflation of the statistical error. Such aspects
are not commonly taken into account in nutritional research, whereas are very commonly accomplished for in
the drug-related investigations. In the context of multi-functional food, there can be both multiple effects on the
health target of a given nutrient, or multiple nutrients acting toward a single target or perhaps even on multiple
targets. In nutritional fields it unrealistic to take hypothesis and outcomes as independent, mostly because nutrient effects are strongly related to each other. This induces a different correlation structure among outcomes
and targets. Basically, if no health claims intended for components, then the composite endpoint is tested at
a predefined alpha-level and components are not statistically tested: then adjustment for multiplicity is needed,
and the basic choice would be on how to consider the concurrent outcomes. If claims are intended for components, then a sequential testing scheme might be applied: the composite endpoint is statistically significant ant
the alpha-level, and then tests for components are made in sequence for the same significance level alpha. No
claims can be made if sequence breaks. The usage of more complex models allows for instance to approach the
problem as a fallback testing strategy: allow to continue testing even if sequence breaks, testing the hypothesis
after the failed using a weighted Bonferroni method. This paper discuss the issues arising in multifunctional
research by multiplicity in testing, both with regard to multiple nutrients and to multiple effects of a single or
more nutrients on the people’s health.
156
P118
Could Methods Be a Factor in Early Closures of
HIV Pre-Exposure Prophylaxis Trials?
Madzouka Kokolo, William Cameron, Dean Fergusson
Ottawa Hospital Research Institute, University of Ottawa, Canada
BACKGROUND. In the past few decades, it has become increasingly common for scientists based in richer countries to initiate clinical trials to be conducted in higher risk groups, in developing countries. This may creates
opportunities for exploitation, as some activists and authors have argued, following early closure of several trials aiming at testing antiretrovirals for HIV prevention (PrEP), in 2004-2005. We aimed to compare the scientific
methods of trials involving recruitment in developing countries to trials involving recruitment only in industrialized
countries. METHODS. We conducted a systematic review, with a focus on efficacy/effectiveness trials. Based
on guidance documents for the ethical conduct of HIV biomedical prevention trials (by UNAIDS/ WHO and by
the Institute of Science), we developed a list of 33 key items. We searched Medline, Embase, Central, trial
registries and the World Wide Web to identify eligible trials; and we communicated with investigators to obtain
protocols and reports. Each protocol was fully reviewed by two independent assessors. RESULTS. We identified
nine eligible trials, among which four had closed early at least one study site. We obtained full- text protocols
for all efficacy trials. All but one trial had a Jadad score of 3/5 or more. On average, 20/33 validity items were
reported in PrEP efficacy trials (61%). This average was 19/33 (58%) for trials closed early versus 2/33 (67%)
for other trials. DISCUSSION. Early closures in HIV PrEP efficacy trials might be related to methodological issues.
It is unclear how methods might have affected the ethical design and/or conduct of those trials.
157
158
Author
Session
Abdul-Karrim, Suheila
Poster
Abolafia, Jeff
Workshop P7
Abraham, Charles CPS 3C A’Hern, Roger
Abstract #
Poster
P88
Author
Session
Balduini, Anna CPS 4A Ball, Leslie
Invited Session 11
Invited Session 9
Invited Session 27
Baldi, Ileana
P109
A59
Poster
Abstract #
P117
A71
Abramson, Natalie Walders Poster
P61
Ballman, Karla
Affuepper-Fink, M.
Poster
P58
Barendse, Renée
CPS 1A A02
A’Hern, Roger
Poster
P116
Barnard, Lorna
Poster
P90
Poster
P05
P03, P50
Akers, Rachel
Poster
P69
Barrett, Jon
Akolkar, Beena
Poster
P41
Barry, Michael
Poster
Alai, Sherita
CPS 2B A36
Basch, EM CPS 4C
A88
Battenhouse, Holly
Poster
P52
Alexander, Karen P. CPS 4E A97
Allen, Colleen
CPS 4C
Poster
A83
P09, P19
Bauza, Colleen
Poster
P101, P102
Bayman, Levent
Poster
P24
Almukhtar, Talat
Poster
P04
Bedding, Alun CPS 3D A66
Alster, Joan
Poster
P10
Beiser, Julia
CPS 2D
A45
Altman, Doug G. CPS 3C CPS 3D A62
A64
Benavente, Marie-France
Workshop P2
Bennett, Antonia
CPS 4C
An, Ming-Wen
CPS 3A A54
Berry, Don
Invited Session 23
Anderson, Emily E.
Invited Session 14
Berry, Jennifer
Poster
Anderson, James R.
CPS 4D
Invited Session 27
Berry, Seth
Invited Session 13
Anderson, Keaven
Invited Session 3
Invited Session 13
Bertolet, Marnie
Poster
P82, P83
P26
A89
Betts, Robert F.
Poster
Invited Session 7
A88
P61
Anderson, Maija
Poster
P66
Billot, Laurent
Anderson, Erica
CPS 2D
A46
Blazeby, Jane CPS 3C Anderson, Karen CPS 3E A67
Blume, Jeffery
Invited Session 8
Poster
P32
P46, P47
A62
Andringa, Jennifer
Poster
P69
Boardman, Kathy
Annechiarico, Robert
CPS 2B A37
Boaz, Annette
Poster
P26
Boruch, Robert CPS 2C
CPS 2C
A39
A41
Bossuyt, Patrick
Poster
P96
Bramucci, Ezio
CPS 4A A71
Brandt, Diane
Poster
CPS 2C
P108
A42
Breckenridge, Ellen
Poster
P17
Breeman, Suzanne
CPS 4C
A87
CPS 2C
CPS 2C
A39
A41
Annunziato, Paula W.
Poster
Anwar, Shamaila
CPS 3E Poster
A69
P42, P43, P90
Applasamy, Pramen
Poster
P11
Archdeacon, Patrick
Invited Session 11
Arcury, Thomas
Poster
P67
Arenz, Dorothee
CPS 1D
A24
Aristoteles, Pagaltzis
CPS 1D
A24
Armstrong, Roma
CPS 1D
A22
Brehaut, Jamie C. Arturo, Raisaro
CPS 4A A71
Bretz, Frank
Invited Session 3
Asztalos, Elizabeth CPS 3E Poster
Poster
Poster
Poster
A68
P06, P07, P33, P34
P36, P40, P62, P63
P70, P95, P98
P103, P104
Brewer, Brenda
CPS 1E A26
CPS 2A A34
PosterP35
Briggs, Andrew H. CPS 3D A64
Avery, Elizabeth F. Poster
P64, P73
Brittain, Erica CPS 1C A15
Azuara-Blanco, Augusto
CPS 2E A47
Brittain, Karen
Poster
Bacik McCormack, Jennifer Poster
P09
Brittenden, Julie
CPS 3B A58
Bademosi, Bambi
A42
Brosteanu, Oreana
Poster
P45
Poster
P51
CPS 2C
P10, P11
Bahnson, Tee
CPS 1D
A19
Brott, Thomas
Bailey, Ryan
CPS 1D
A19
Brown, Julia
CPS 2A A32
Baker, Carol
Workshop P7
Brown, Melissa
Poster
P34
Poster
Brown, Sarah
CPS 2A A31
Brown, Sheldon T.
Poster
P89
Baker, Laurence
P110
159
Author
Session
P41
Chen, Ying Qing
Author
Session
Bruckner, Thomas
Bryant, Maria
Poster
P84
Poster
CPS 3E P42
A69
Chen, Zhengjia
CPS 1B
CPS 1B
Cheung, Ken
Invited Session 10
Budrevich, Rich CPS 1D
A19
Cheung, Ying-Kuen
Invited Session 12
Buhr, Kevin
Invited Session 13
Bullen, Chris CPS 4A A75
Chew, Emily Y.
CPS 1E CPS 2E Buncher, C. Ralph
Poster
P69
Chi, Eric
Invited Session 4
CPS 4B A77
A97
Brown, William M.
Poster
Abstract #
Invited Session 8
Burke, Brian
Poster
P37
Ching-Ju, Lu
Burr, Jennifer CPS 2E A47
Chiswell, Karen
CPS 4E Invited Session 4
Abstract #
A08
A11
A29
A49
Burton, Kayleigh
CPS 3E A69
Chow, Shein-Chung
Burzykowski, Tomasz
CPS 1E A27
Chrischilles, Elizabeth CPS 3D Bush, E. Michelle
Poster
P109
Chrolavicius, Susan
Poster
P105
Poster
P48
A65
Butler, Nicole
Poster
P49
Chulada, Patricia C.
Buyse, Marc CPS 1E A27
Churley-Strom, Ruth
CPS 3B A57
Cidlowski, John
Poster
P97
Byrne, Margaret M.
Poster
P101, P102
Caban-Holt, Allison
Poster
P01
Clark III, John D.
CPS 3A A53
Calatroni, Agustin
Poster
P28
Clarke, Mike CPS 3C A62
Poster
P24
Calhoun, Peter
Poster
P81
Clarke, William
Califf, Robert M.
CPS 4E A97
Cambria, Roy
Poster
P94
Cameron, William
Poster
P118
Clemons, Traci E. CPS 1E A29
CPS 2C
A42
CPS 2E A49
PosterP108
Campanella, Maria
Invited Session 2
PosterP19
Campbell, Aimee N. C.
Invited Session 14
Clingan, Kathy
Poster
CPS 1E CPS 2A P35
A26
A34
Campbell, Marion
Invited Session 5
CPS 1C CPS 4C
A17
A87
Close, Nicole C.
CPS 4C
CPS 1E A85
A25
Cochran, Claire
CPS 2E A47
Cantor, Alan
Poster
P03
Carter, Shelly
CPS 2D
A46
PosterP38
Poster
P94
CPS 3D CPS 3D Workshop P5
Poster
A65
A66
Cesar, Marie-Antoinette
Coffey, Christopher S.
Chadwick, Jennifer
Poster
P100
Cohen, Dena
CPS 2A A32
Chakraborty, Bibhas
Invited Session 12
Chakravarty, Eliza CPS 1C A15
Chamberlain, James CPS 2C
A42
Chan, Ivan S.F.
Poster
P26
Chan, Sunny
Poster
P63
Chandler, Danielle
Poster
P53
Chang, Nancy
Poster
P37
Chang, Yu-Ming
CPS 4C
Chappell, Rick
P24, P39
Colaert, Dirk CPS 1D
A24
Collins, Cal
CPS 4C
A84
Collins, Joseph
Poster
P85
Conner, Cassidy
Poster
P52
Connor, Jason
Workshop P4
Cook, Jonathan A.
CPS 3D Copeland, Kenneth
Poster
A86
Cornely, Oliver CPS 1A CPS 1D
A03
A24
Workshop P9
CPS 4D
A93
Cotton, Seonaidh
CPS 3B CPS 4C
A58
A87
Chaudhry, Shazia H.
CPS 2C
A39
Cottrell, David
CPS 4E A96
Check, Devon K.
CPS 2E A48
Crann, Mary
Poster
P38
Chen, Henian
CPS 4D A91
Creel, Darryl
Poster
P86
Chen, Li
Invited Session 24
Workshop P5
CPS 3A CPS 3D Crockett, Patrick W.
Poster
P27
A51
A66
Crowe, Emily
Poster
P93
Cudkowicz, Merit
Poster
P39
Chen, Sophie CPS 3D A63
Cullen, Michael
Poster
P88
160
A64
P100
Author
Session
Author
Session
Czajkowski, Susan
Invited Session 21
D’Agostino, Jr., Ralph
Poster
P67
Edwards, Allison
Poster
P55
D’Almeida, Heraldo
Poster
P101, P102
Eilidh, Duncan
CPS 3C A60
Dai, James
Invited Session 8
El ghormli, Laure
Poster
P61
Daniel, Mary
Poster
P100
Elbourne, Diana CPS 1C A17
Das, Abhik
Poster
P86, P115
Elgie, Bill
Poster
P14
Ellenberg, Susan
Invited Session 3
Invited Session 19
Cumber, Serena
Abstract #
Poster
P10, P11
Davis, Barry R.
Poster
P17
Dawn, Caron
CPS 4C
A86
Dawson, Liza
CPS 2C
A40
PosterP77
De Gruttola, Victor
Invited Session 8
de Lange, Stefanie
Poster
CPS 1A De Rosa, Marisa
De Silvestri, Annalisa
DeBono, Johann
Poster
Dekker, Evelien
CPS 1A DeMets, Dave
Invited Session 18
Demotes, Jacques
Invited Session 17
Deng, Hongjie
CPS 3A A51
Devereaux, PJ CPS 1E A30
Devidas, Meenakshi
Invited Session 27
Diaz, Mireya
CPS 4E A99
Diener, Markus
Poster
P45
Dignam, James
Invited Session 9
Dillon, Catherine
Edelstein, Sharon
Abstract #
Poster
CPS 4B P49
A79
Elm, Jordan
Poster
P52
Elmore, Bekki
Poster
P48
Emerson, Scott S.
Workshop P9
P58
A04
Emery, Erin E.
Poster
Endrenyi, Laszlo
Invited Session 4
CPS 1D
A20
Englert, Stefan
Poster
P84
CPS 4A A71
Erb-Alvarez, Julie
Poster
P100
P116
Escalera, Jasmine
Poster
P57
A02
Espeland, Mark A.
Poster
P31
Fagerlin, Angie
Poster
P101, P102
Falkner, Karen L.
Poster
P31
Fan, Shenghua
CPS 1B
A07
Fan, Xiaoyin Frank
Invited Session 18
Fang, Wes
CPS 4C
Farrin, Amanda
Poster
CPS 4E CPS 1C CPS 3E P43, P87, P90
A96
A16
A69
Invited Session 10 Invited Session 25
PosterP52
Fayers, Peter M.
CPS 3D A64
Federico, Carole A.
CPS 4A A74
Disorda, Melissa
CPS 4B A78
Feeney, Patricia
Poster
P76
Doffagne, Erik
CPS 1E A27
Feig, Denice
Poster
P95, P98
Felton, Beverly
Poster
P100
Poster
CPS 4A CPS 4A CPS 4B P118
A73
A74
A81
P30, P72, P74, P75
A55
A61
P73
A86
Doig, Gordon S.
Poster
CPS 3B CPS 3C Donner, Allan CPS 2C
CPS 2C
A39
A41
Fergusson, Dean A.
Doria-Rose, V. Paul
CPS 2A A34
Ferlini, Marco
CPS 4A A71
Figueroa, Maria
Poster
P09
Fillius, Michael
Poster
P109
Fisher, Helen
Poster
P46, P47
Dragalin, Vlad
Invited Session 29
Drake, David
Poster
P65
Drapkin, Anne
Invited Session 20
Dreier, Gabriele
CPS 1A A05
Flaxman, Linda
Poster
P51
Dress, Jochen
CPS 1A Invited Session 17
A06
Fleming, Lora E.
CPS 3A A53
Fleming, Thomas R.
CPS 4D
A90
Durkalski, Valerie
Invited Session 25
Invited Session 28
Flood, Marion
CPS 1D
A22
Flynn, Kathryn E.
CPS 2E A48
Eccles, Martin P. CPS 2C
CPS 2C
CPS 3C Flynn, Robert
Poster
P13
Fockens, Paul CPS 1A A02
Ford, Charles E.
Poster
P17
Ford, Ian CPS 1D
CPS 1D
CPS 2E A22
A23
A50
Forsyth, Paul CPS 4E A95
Ecklund, Dixie J.
Poster
Workshop P1
Edelman, Bonnie
Poster
A39
A41
A59
P39, P65
P94
161
Author
Session
Author
Session
Foulkes, Mary
Invited Session 20
Fragoso, Carlos
Poster
P08
Harney, Deneil
Invited Session 25
Harris, Darrin
Poster
P71
Francis, Jill
CPS 3B CPS 3C A58
A60
Hartley, Ben CPS 3D A66
Friedman, Lawrence M.
Invited Session 30
Hartley, Suzanne
Poster
Hartline, Jo Ann
CPS 3E Gallo, Paul
A67
Invited Session 29
Harvey, Ian M. CPS 3D A64
Galvez, Jose
Invited Session 22
Gamer, Anna-Lena
Poster
P45
Harvin, Lea N.
CPS 4B A77
PosterP08
Gantz, Marie
Poster
P86
Hawley, Sarah
Poster
Garantziotis, Stavros
Poster
P97
McRobbie, Hayden CPS 4A Garden, Pauline CPS 2E A47
Haynes, Shana
Poster
P10, P11
Gareen, Ilana F.
CPS 2A A34
Hayslip, Jay
Poster
P111
Gargon, Elizabeth
CPS 3C A62
PosterP93
Heighes, Philippa T.
Poster
P30
Henning, Alice K.
Poster
P54
Gassman, Jennifer
Poster
P10, P11
Hermos, John
Poster
P57
Gaussoin, Sarah
Poster
P31
Hickey, Jan
Poster
P32
Gaydos, Brenda CPS 3D A66
Higgins, Rosemary
Poster
P86, P115
Gersten, Iris
Poster
P38
Hillmen, Peter CPS 2A A32
Ghebregiorgis, Ghideon
CPS 1C A14
Hilner, Joan
Poster
P41
Ghidina, Marco
Poster
P117
Hislop, Jennifer M. CPS 3D A64
Gibb, Jonathan
CPS 1D
A21
Ho, Lindsey A.
Poster
P27
Gilbert, Peter
Poster
P114
Hoac, Trinh
Poster
P36, P40, P70
Gill, Thomas
Poster
CPS 4B P08
A77
Hogan, Patricia
Poster
P71
Glass, Aenne
Poster
P21
Holland, Nicole C.
Poster
P15
Glover, Marewa
CPS 4A A75
Holloway, Ivana
CPS 1C Poster
Goldmuntz, Ellen CPS 1C Gonzalez, Martha
Poster
Gordon, Mae
CPS 2D
Graham, Liz
CPS 3E A69
CPS 4E A96
PosterP42
Greenhouse, Joel
Foster, Nicole
Abstract #
Poster
P25
Hardeman, Wendy
A15
Abstract #
CPS 3C A59
P42, P90
P101, P102
A75
A16
P43, P87
Hooft, Lotty
Poster
Horigian, Viviana
Invited Session 30
Houston, Collette
Poster
P80, P94
Houweling, Adrielle
Poster
P106
Hu, Joan
Invited Session 24
Invited Session 19
Hu, Lian
Poster
P19
Greenlaw, Nicola
CPS 4E Huang, Bin
Poster
P112
Gregori, Dario
Poster
Huang, Yunda
Poster
P113, P114
Poster
P51
P101, P102
A45
A95
P117
P96
Grimes, Imogene
CPS 3A A52
PosterP20
Hughes, Susan
Hung, H.M. James
Invited Session 3
Grimshaw, Jeremy
Invited Session 16
CPS 2C
CPS 2C
Hunt, Devin J.
Workshop P6
Hunt, Julie R.
Poster
P31
Grosser, Stella
Invited Session 4
Hunt, Devin
CPS 4C
A85
Grzywacz, Joseph
Poster
P67
Hurmiz, Charles
Invited Session 22
Guassoin, Sarah
Poster
P71
Hutton, Brian
CPS 4A A73
Hahnhaussen, Claire
Poster
P36, P40, P70
Huyck, Susan CPS 3D A66
Hair, Jane CPS 1D
Hwang, Elsa
Poster
P94
Halabi, Susan
Workshop P1
Workshop P8
Workshop P4
Iasonos, Alexis
CPS 2A A33
Jackson, Jami
Poster
P94
Jacobson, Alice
Poster
P82, P83
Hale, Mike CPS 3A Hall, Emma
Poster
Hallek, Michael
CPS 1D
A39
A41
A21
A51
P88, P116
A24
162
Jaemyung, Kim
CPS 4B A80
Jaffee, Katy
CPS 1D
A19
Jeffers, Daniel
CPS 4B A78
Author
Session
A05
Klier, Susan
Author
Session
Jenckes, Ann
Jenkins, Martin Poster
P80
Knipscher, Katie
Poster
CPS 3D A66
Knöll, Peter CPS 1A A03
Jenkins, Todd
Poster
P69
Ko, Mi Mi
Poster
P02
Jewell, Christine
Poster
P97
Kocherginsky, Masha
Invited Session 9
Jhund, Pardeep S.
CPS 4E A95
Koerbel, Glory CPS 3B Ji, Ming
Poster
P56
Kokolo, Madzouka
Poster
P118
Ji, Yuan
CPS 1B
A09
Kolbe, Henrike
Poster
P92
Jiang, Joy CPS 4A A75
Kollman, Craig
Poster
P55
Jiang, Yannan
CPS 4A A75
Kondapaka, Radhika
Poster
P19
Johnson, Gary
Poster
P16, P26
Kong, David
CPS 4E A97
P31
Kopetskie, Heather
Poster
P16
Koroshetz, Walter
Poster
P39
A53
Jena, Susanne
Abstract #
CPS 1A Poster
Abstract #
P14
P10, P11
A57
Johnson, Karen C.
Poster
Johnson, Kimberly
Invited Session 22
CPS 2B A37
Koru-Sengul, Tulay
CPS 3A Johnson, Stanley
Poster
P32
Koski, Beverly
Workshop P2
Johnston, Marie CPS 3C A59
Justice, Amy C.
Poster
P89
Kowalski, Jeanne
CPS 1B
CPS 1B
A08
A11
Kahn, Susan R.
Poster
P106
Kozloff, Rene
CPS 1E A28
Kai-Hsiung, Lin
CPS 4C
A86
Kairalla, John A.
CPS 3D A65
Invited Session 24
CPS 2E CPS 4E Invited Session 11 A48
A97
Kaiser, James
Kramer, Judith M.
Kalaitzaki, Eleftheria
Poster
P88, P116
Krishtul, Rita
CPS 4C
A86
Kang, Byoung Kab
Poster
P02
Kundt, Guenther
Poster
P21
Kaplan, Robert
Invited Session 21
Kappelman, Michael
CPS 4B Kunitz, Selma C.
CPS 1E A28
PosterP60
CPS 2B
A35
Karrison, Theodore
Invited Session 9
Kusek, John
Poster
Kass, Michael CPS 2D
A45
Kuznetsova, Olga
Invited Session 29
Kaufman, Kristopher
CPS 4C
A86
Kwok, Janice
Poster
P07
Kaufmann, Petra
Poster
Invited Session 10
P39
Kwong, Christine CPS 3B A57
Kyriakides, Tassos
Poster
P89
Kean, Sharon
CPS 1D
CPS 1D
CPS 1D
A22
A21
A23
Laber, Eric
Invited Session 12
Lachenbruch, Peter
Invited Session 4
Lachin, John M.
Invited Session 19
PosterP23
Lack, Gideon
Poster
Lan, K. K. Gordon
Workshop P8
Landray, Martin
Invited Session 11
A78
Keane, Dana
Poster
P29
Kearney, Marianne
Poster
P39
Keyes-Elstein, Lynette
CPS 1C A15
Khan, Sohail
Poster
P100
Kher, Uma
CPS 4D
A94
Khuri, Fadlo R.
CPS 1B
CPS 1B
A08
A11
Kidwell, Kelly
P50
P46, P47
Lansdorp-Vogelaar, Iris CPS 4A A72
Lawrence, Joseph
CPS 4A A73
Invited Session 15
Le, Quang
Poster
P14
Kim, Caroline
Poster
CPS 2C
P108
A42
Lee, David J. CPS 3A A53
Lee, Jeannette
Poster
P50, P91
Kimmelman, Jonathan CPS 4A A74
Lee, Ju Ah
Poster
P02
King, Denise
CPS 2C
A42
PosterP108
Lee, Myeong Soo
Poster
P02
Lee, Shing
Invited Session 10
King, Eileen CPS 4B A78
Lefering, Rolf
Poster
P58
Kirkwood, Katherine
Poster
P89
Legault, Claudine
Poster
P71
Kirton, Joanne
Poster
P36, P40, P70
Leibfritz, Hans
Poster
P45
Klein, Eric
CPS 3E A67
Lengfellner, Joseph
Poster
P94
Klersy, Catherine
CPS 4A A71
Lensing, Shelly
Poster
P91
163
Author
Session
Levy, Donna E.
Lew, Robert
Lewis, Roger J.
Workshop P4
Li, Li
Poster
Levin, Myron J.
Abstract #
P26
Marcellus-Duval, Debbie
Author
Session
Poster
P99
Marchenko, Olga
Invited Session 23
Poster
P57
Marcia, Latif
CPS 4C
A86
Marcus, Pamela M.
Invited Session 1
CPS 2A A34
Marler, John
Invited Session 2
PosterP51
Poster
P112
Li, Qian
Invited Session 24
Li, Xiaoming
Poster
P26
Li, Stan
CPS 1B
A12
Limacher, Marian
Poster
P31
Lin, Yunzhi
Invited Session 15
CPS 4D
A93
Lindblad, Robert
Abstract #
Poster
P94
Marrah, Dona CPS 3E A67
Martin, Roberto CPS 4C
A86
Mason, Dalah
Poster
Poster
Poster
Invited Session 2
PosterP19
CPS 2D
A46
Massaro, Elaine CPS 3B Massarweh, Suleiman A.
Poster
P112
Liu, Jiajun
Poster
P22
Mathes, Tim
Poster
P58
Liu, Ping CPS 1B
A09
Mazer, David CPS 4A A73
CPS 4A A76
P05, P33, P34
P70, P95, P98
P103, P104
A57
Liu, Yanhong
Poster
P69
Mazroui, Yassin
Liu, Yuan
CPS 1B
A10
Löffler, Thorsten
Poster
P45
McBee, Wendy L.
CPS 1E CPS 2E A29
A49
Logtenberg, Sabine
Poster
P44
London, Wendy B.
Invited Session 27
McCleary, Nicola
CPS 3C CPS 3B CPS 3C A60
A58
A59
Long, Christen
Poster
P37
McConnachie, Alex CPS 4E A95
Longbottom, Mary
Poster
P51
McCrimmon, Scott
Poster
P09
Lovato, Laura
Workshop P1
McDermott, Mary
Poster
P08
Lowrie, Richard CPS 4E A95
Lu, Ching-Ju
Poster
P08
Lu, Ying
CPS 1B
A07
McDonald, Alison
Workshop P2
CPS 2E CPS 4C
A47
A87
Lu, Yun
CPS 2B
A35
McDonnell, Patrick
Poster
P13
Ma, Yong
Poster
P23
McGurk, Lauren
Workshop P2
Maca, Jeff
CPS 3D A66
McKevitt, Christopher
Poster
MacDonald, Mary
CPS 1D
A23
MacDonald, Thomas M.
Poster
P13
MacGregor, Joan M.
CPS 3B A57
Mackenzie, Isla S.
Poster
P13
Mackrell, Jack
Poster
MacKrell, Jack
Poster
MacLennan, Graeme
P46, P47
McLeod, Laurie CPS 1D
A19
McMurray, John J.V.
CPS 4E A95
McNeil, Elizabeth
Poster
P39
P10
McPherson, Gladys CPS 1C CPS 2E CPS 4C
A17
A47
A87
P11
McQuellon, Cynthia
Poster
P31
Invited Session 5
CPS 4C A87
McRae, Andrew D. CPS 2C
CPS 2C
A39
A41
Maddison, Ralph CPS 4A A75
Madeline, Carroll
CPS 2B A37
Melia, Michele
Poster
Workshop P1
Madero, Rodrigo
Poster
P11
Magee, Laura A.
Poster
P36, P40, P70
Mendizabal, Adam M.
CPS 2D
A46
PosterP38
Mai, Yabing
Poster
P22
Menon, Kusum CPS 4B A81
Mair, Frances S.
CPS 4E A95
Menzies, Jennifer M.
Poster
P40
Mandrekar, Sumithra
CPS 3A Workshop P5
A54
Mergler, Sonya
Poster
P05
Meyer, Daniel CPS 3D A66
Poster
P85
P25, P53, P55
Mangat, Pam
CPS 4B A79
PosterP49
Mi, Zhibao
Michie, Susan CPS 3C A59
Mangoff, Kathryn
Poster
Miclaus, Kelci
CPS 2D
A43
Manley, Geoff
Invited Session 10
Miele, Gloria
Invited Session 14
Mann, Geoffrey
CPS 2D
Mighton, Lisa
CPS 3B P05
A44
164
A57
Author
Session
Miller, Kristy CPS 2B
Miller, Michael E.
Poster
CPS 4B Miller, Rosemary
Poster
Miller, Anthony B. CPS 2A Abstract #
Author
Session
A35
Oude Rengerink, Katrien
P08
A77
Owonikoko, Taofeek K.
CPS 1B
CPS 1B
A08
A11
P69
Oxman, Michael N.
Poster
P26
Pabon, Amara G.
Poster
P15
A34
CPS 1A Poster
Abstract #
A02
P44, P96
Miller, Tony
Invited Session 1
Miller, J. Phillip CPS 2D
A45
Pachucki, Constance
Poster
P26
Minami, Manabu
Poster
P79
Paine, Susan
Poster
P10, P11
Poster
P80
P02
Mirabelli, Maria
Poster
P67
Parikh, Supriya
Miskulin, Dana
Poster
P10, P11
Park, Tae Yong
Poster
Parke, Tom
Invited Session 23
Paterson, Caron
CPS 1D
Patton, David
Invited Session 22
Pauls, Keith
CPS 4B A80
PosterP52
Paulus, Ursula
CPS 1A A04
PosterP92
Payan, Marisa
Poster
P37, P100
Paynter, Elizabeth
Poster
P16
Poster
CPS 1E P35
A26
A03
Mitchell, Herman
Poster
P28
Moenkemann, Heike
CPS 1A A04
PosterP92
Mohammad, Farid
CPS 2B Mol, Ben Willem
CPS 1A A02
Invited Session 20
Poster
P18, P44, P96
Molenberghs, Geert
Workshop P5
Morgan, Caroline
CPS 3D Morpurgo, Giada
Poster
Morris, Patricia CPS 2D
A45
Payte, Nancy
Morrison, Vicki A.
Poster
P26
Peer, Eysel
CPS 1A Mosnaim, Giselle
Poster
P64
Pennello, Gene
Workshop P5
Poster
P41
P52
A37
A66
P117
A21
Muller, Keith E.
CPS 3D A65
Perdue, Letitia H.
Murayama, Toshinori
Poster
P79
Perlmutter, Aaron
Poster
Murphy, Lisa
Poster
P97
Perney, Teresa
CPS 3D Poster
P109
A66
Mutham, Mahesh
Poster
P09
Peterson, Jan S.
Myers, Jane
Poster
P94
Pettinger, Mary
Poster
P31
Pham, Trang
Poster
P37
Phipps, Kathy
Poster
P65
Naar-King, Sylvie
Invited Session 21
Naughton, Michelle
Poster
Neaton, James D.
Workshop P9
Pierce, June J.
Poster
P41
Workshop P6
Pilger, Rita CPS 1A A04
Piller, Linda B.
Poster
P17
Pinheiro, José
Invited Session 13
Invited Session 23
Workshop P4
Workshop P8
Piper, Ben
Poster
P60
Nelson, Kristine
P71
Neugebauer, Edmund A.M. CPS 1A A01
PosterP58
Newman, Anne
Poster
Nishimura, Hiromi
Poster
Norrie, John
CPS 4E CPS 2E CPS 4C
Invited Session 5
CPS 3D Nutman, Thomas B.
P08
P79
A100
A47
A87
Pleasants, Debbie
Poster
P71
Pogue, Janice
CPS 1E A30
A64
Poland, Hans CPS 1A A06
Poster
P15
Pontoppidan, Maiken
CPS 1C A13
Ocasio, Manuel A.
CPS 3A A53
Porter, Kristin
Poster
P37
Odem-Davis, Katherine
CPS 4D
A90
Powell, Lynda
Invited Session 21
Odenkirchen, Joanne
Invited Session 10
Powers, Carolyn
Poster
P69
Offen, Walter
Invited Session 3
Prapavessis, Harry CPS 4A A75
Olinger, Tamara
Poster
Pratt, Jesse CPS 4B A78
O’Neal, Scott M.
CPS 3B Pressel, Sara L.
Poster
P17
O’Neill, Robert
Invited Session 3
Invited Session 19
Pressman, Alice
Poster
P82, P83
Ou, San-San
Poster
Pritchett, Yili
CPS 3D A66
Probstfield, Jeffrey L.
Poster
P17
P64, P73
A57
P66
165
Author
Session
Proschan, Michael
Workshop P8
Puehn, Karen
Poster
P14
Purkayastha, Das
CPS 1B
A12
Pyle, Laura
Poster
Prorok, Phil
Invited Session 1
Abstract #
Author
Session
Sanya, Kara
Abstract #
Poster
P48
Sapre, Aditi
CPS 4D
A94
Sargent, Daniel
Invited Session 9
CPS 3A A54
P61
Sather, Mike
Poster
P32
Saunkeah, Bobby
Poster
P100
Schanuel, Jill
Poster
P37
Schenning, Sherrie
CPS 2E CPS 1E A49
A29
Schindler, Jerry
Invited Session 18
Poster
Quandt, Sara
Poster
P67
Quinlan, Judith
Invited Session 29
CPS 3D A66
Quinn, Daniel J.
Poster
P99
Qureshi, Asma
Poster
P95, P98
Rae, Brian CPS 4E A95
Schmader, Kenneth E.
P26
Ramsay, Craig R. CPS 3D A64
Schmaltz, Cornelius
Invited Session 17
Redaelli, Marcus
Poster
P58
Schmitz, Susan L.
Poster
A14
Schoenfelder, John CPS 3A A52
P101, P102
Rees, Renee
CPS 1C Reeve, Russell
Invited Session 23
Schwartz, Leonard
CPS 3B A57
Reinecker, Sylvia
CPS 1A Scott, Anisa
CPS 2B A38
Reynolds, Jeri
Poster
Scotti, Valeria
CPS 4A A71
Richardson, Michelle
CPS 3C A59
Sébastien, Marque
CPS 4A A76
A75
Seidel, Doerthe
Poster
CPS 1A P58
A01
Self, Steve
Poster
Shah, Nilay CPS 2D
Shahin, Seta
Invited Session 24
Shao, Yiming
Poster
A04
P111
Roberts, Vaughan
CPS 4A Robertson, Julia
Poster
P71
Robinson, Cerisé
Poster
P103
Rochon, James
Invited Session 30
Rochon, Justine
Poster
P84
Rodavitch, Ann
Poster
P80
Roehrborn, Claus
Poster
P03
Shapiro, Stan
CPS 4A A73
PosterP106
Rogatko, Andre
CPS 1B
A10
Sheffet, Alice
Poster
Rosa, Carmen L.
Poster
Invited Session 14
P19
Shentu, Yue
Poster
P22
Rosenbaum, Jennifer
CPS 1E A26
CPS 2A A34
PosterP35
Sherer, Susan
Poster
P10, P11
Sherif, Hanna
CPS 4B A79
PosterP49
Rosenberg, Yves
Workshop P1
Shi, Michael X.
Poster
Ross, Sue
Poster
Shiowjen, Lee
CPS 1C A14
CPS 3D A65
P36, P40, P70
P113, P114
A46
P113, P114
P51
P06, P07, P63
Rossion, Inga
Poster
P45
Shorr, Ronald I. Rothschild, Steven K.
Poster
P73
Shortreed, Susan M.
Invited Session 12
Ruddock, Sharon
Poster
P90
Saade, George
Invited Session 20
Shugarts, Patti
CPS 2B
A35
CPS 1E A28
PosterP60
Sabbatini, P.
CPS 2A Sackett, David L.
Invited Session 6
Saginur, Raphael
CPS 2C
CPS 2C
A39
A41
Saleem, Mariam
Poster
Sampson, Margaret CPS 4A Sanchez, Johanna CPS 3E A68
Poster
P05, P06, P33, P34
Poster
P36, P40, P62, P70
Poster P95, P98, P103, P104
Sandhu, Shahneen
Poster
SanGiovanni, John Paul CPS 1E CPS 2E Sansing, Veronica
CPS 3B A33
Shumaker, Sally A.
Poster
P31
Silverman, Milena
CPS 4C
A86
Simo, Saray
Poster
P62
Simpson, Fiona
Poster
CPS 3B A74
Simpson, Lara M.
Poster
P17
Skoler-Karpoff, Stephanie Poster
P80
Slone, Stacey
Poster
P111
Smith, Danielle
Poster
P68
Smith, Lynette
CPS 4D
A89
A29
A49
Soukup, Mat
Invited Session 13
Spates, Kathryn E.
Poster
A57
Speakman, John
Invited Session 22
P116
166
P94
P72, P74, P75
A55
P15
Author
Spong, Catherine
Session
Invited Session 20
Abstract #
Author
Session
A33
Thorlund, Kristian
CPS 1E A30
P106
Tibbals, Melinda
CPS 2D
A46
Tighiouart, Mourad
CPS 1B
A10
Tinmouth, Alan CPS 4A Tobin, Siobhan
Poster
P95, P98
Thomson, Elizabeth
Abstract #
CPS 2E A50
Spriggs, DR CPS 2A Springmann, Vicky
Poster
Spychala, Meagan
CPS 1C Stableford, Sue
Poster
Starr, A. Zoe CPS 4E A97
Starr, Kath CPS 4C
A87
Tom, Jennifer
Poster
P94
Start, Fawna L.
CPS 1E A25
Tom, MeeLee
Poster
P51
Stefanick, Marcia L.
Poster
P31
Stein, Gregor
CPS 1A A03
Tomino, Carlo
CPS 3B A56
PosterP12
Stenning, Sally
Poster
P88
Torner, James C.
CPS 3D A65
Stephens, Robyn Davis
Poster
P48
Trejo, Grisel
Poster
P67
A60
Treptau, Tilman
Poster
P58
Trigiani, Katherine
CPS 3E A68
Trollinger, Stacie CPS 2B
A35
Tsai, Midi CPS 4A A75
Tseng, Jenny
Poster
P66
Tucker, Glenn
Poster
P09
Tunis, Sean
Invited Session 6
Turnbull, Bruce
Invited Session 18
Usdin, Martine
Poster
Stewart, Fiona CPS 3C Stockbridge, Norman
Invited Session 3
Stoehr, Andreas
Poster
Stoermer, Kati
Poster
Stowe, Cynthia L.
Poster
CPS 4B Straus, Michele
Invited Session 30
Studts, Jamie L.
Poster
P102
A15
P101, P102
P92
P110
P08
A77
P101
A73
P116
Stumpf, Maik
CPS 1D
A24
Utset, Tammy
CPS 1C A15
Suresh, Ramachandran
CPS 1C CPS 3D
A18
A63
Vale, Luke D. CPS 3D A64
Sverdlov, Oleksandr
Invited Session 28
van Ballegooijen, Marjolein CPS 4A A72
Sweetman, Elizabeth A.
CPS 3B CPS 3C Poster
Szentendrei, Tibor
Poster
P60
Taljaard, Monica
CPS 2C
CPS 2C
Invited Session 16
A39
A41
Talton, Jennifer
Poster
Tang, Rui (Sammi)
van Hees, Frank CPS 4A Van Meter, Emily
Poster
Van Veldhuisen, Paul
Poster
CPS 4C
P19
A83
Vanessa, Jakob
CPS 1A A01
VanVeldhuisen, Paul
Poster
P09
Vella, Gustav
CPS 1D
A24
P67
Venet, David CPS 1E A27
CPS 3A A51
Vertrees, Julia
Poster
P32
Tang, Tz-Yang
CPS 4C
A86
Vickers, AJ CPS 4C
A88
Tanguy, Jérôme
CPS 4A A76
Villarreal, Miguel
Poster
P28
Tate, Janet
Poster
P89
Vinard, Andrea
Poster
P101, P102
Taylor, Stephanie
Poster
P91
Vincent, Jessica
Poster
P107
Taylor, William CPS 1D
A19
Temprosa, Ella
Poster
CPS 4B P49
A79
Visness, Cynthia
CPS 1D
A19
PosterP28
Teuschler, Hoa
Poster
P41
Thabane, Lehana
Invited Session 6
Thaler, H. CPS 2A Thom, Elizabeth
Invited Session 20
PosterP18
Thomann, Mitchell A.
CPS 3D A65
Thomas, Fridtjof
Poster
P31
Thomas, Michelle
Poster
P94
Wallace, Dennis
Poster
Thomas, Stephen B.
CPS 3B A57
Wallstein, Markus
CPS 1A A06
Thompson, Paul A.
CPS 4B A82
Walter, Gregory
CPS 2A A32
A55
A61
P30, P74
A33
167
A72
P111, P112
Vo, Dong
Poster
P59
Voeks, Jenifer
Poster
P51
von Dadelszen, Peter
Poster
P36, P40, P70
Wade, Karen
Workshop P7
Wade, Rich Poster
P86
Wahle, Aimee
Poster
P09
Wakim, Paul
Workshop P3
Invited Session 30
P115
Author
Session
Wang, Sue-Jane
Invited Session 18
Invited Session 28
Invited Session 3
Workshop P5
CPS 1B
Wang, William CPS 3D Wang, Zhibo
CPS 1B
Wang, Lei
Poster
Abstract #
P66
Author
Session
Yamal, Jose-Miguel
Abstract #
Poster
P17
Yan, Jun
CPS 4C
A86
Yan, Lihan
CPS 1C A14
A09
Yang, Bo
CPS 3D
CPS 1C A63
A18
A66
Yang, Chengwu
CPS 4D
A92
A11
Yang, Jun
Invited Session 4
Poster
P24
P114
Wang, Sijian
CPS 4D
A93
Yankey, Jon
Wang, You-Gan
CPS 1B
A07
Yao, Lena
Poster
Wang, Zhibo
CPS 1B
A08
Yao, Ruji
CPS 1C Yin Yeung, Wai
Invited Session 15
Ward, Roxanne
CPS 4B A81
Warden, Beverly A.
Poster
P48
A18
Yokode, Masayuki
Poster
P79
You, Zhiying
Poster
P56
Yuan, Ying
Invited Session 28
Ware, James H.
Invited Session 6
Ware, JeanAnne M.
Poster
P15
Warren, Derek CPS 2E A50
Yusuf, Salim
CPS 1E A66
Zager, Phil
Poster
P10, P11
P36, P40, P70
Wathen, Kyle CPS 3D Watterberg, Kristi
Poster
P115
A30
Zahid, Ainy
Poster
Invited Session 2
Wauters, Aimee
Poster
P37
Zajicek, Anne
Weaver, Kathryn E.
Poster
P31
Zarghooni, Kourosh
CPS 1A Wei, Li
Invited Session 7
Deborah Zarin
Invited Session 22
Weijer, Charles
CPS 2C
CPS 2C
Invited Session 16
A39
A41
Zarychanski, Ryan
Invited Session 5
Weinfurt, Kevin P.
CPS 2E A48
Weiss, Heidi
Poster
P111, P112
Weitz, Jürgen
Poster
P45
Wharton, David
Poster
P100
White, Angela
Invited Session 16
CPS 2C
Whitehead, Nicole
Poster
Wicharz, Margarete
CPS 1A Wiggins, Kimberly
Poster
Wildfire, Jeremy
Poster
CPS 1D
P28
A19
Willenberg, Kelly
Poster
P110
Williams, O. Dale
Poster
P56
Williamson, Paula CPS 3C A62
Wilson, Roger
Poster
P80
Wittes, Janet
Invited Session 11
Invited Session 19
PosterP20
Wohlford, Neil
Poster
P76
Wolfinger, Russ CPS 2D
A44
Woodhead, Gail CPS 3B A57
Woolson, Rob
Workshop P7
Wright, Elizabeth
CPS 4E A98
Wright, Jonathan CPS 3E A69
Wright-Hughes, Alex
CPS 4E A96
Wruck, Lisa
CPS 1C A15
Wu, Bingyan
Poster
P99
Xiong, Chengjie
CPS 3E A70
A41
P101, P102
A03
P10, P11
168
A03
Zauber, Ann
CPS 4A A72
Zhang, Jane H.
Poster
P26
Zhang, Nan
Invited Session 4
Zhao, Wenle
CPS 4B A80
CPS 4D
A92
Invited Session 25
Invited Session 28
PosterP52
Workshop P6
Zhou , Yijie
CPS 1C A18
Zink, Richard C.
CPS 2B CPS 2D
A38
A44
Zobec, Federica
Poster
P117
Zombeck, Andrea
Poster
P48
Zwarenstein, Merrick
CPS 2C
CPS 2C
A39
A41

Final Program - Society for Clinical Trials

Transcription

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