International - GGD Amsterdam

Transcription

HIV
HCV
STI
Oslo
Amsterdam
Berlin
London
Vienna
Paris
Bern
Calgary
Madrid
International epidemiological studies on HIV, HCV and STI Jannie van der Helm
Sydney
Rome
Athens
Paramaribo
Johannesburg
Jannie van der Helm
International
epidemiological studies
on HIV, HCV and STI
International
on HIV, HCV and STI
Jannie van der Helm
International epidemiological studies on HIV, HCV and STI
ISBN/EAN: 978-90-6464-807-6
http://dare.uva.nl/dissertaties
Cover design and lay-out: Sergei Teresuk (www.teresuk.nl)
Printing: GVO drukkers & vormgevers BV, Ede, the Netherlands
Financial support for the publication of this thesis by Academic Medical Centre/University of
Amsterdam, AbbVie, BD Diagnostics, Condomerie, DDL Diagnostic Laboratory, Fonds Tropische
Dermatologie, GGD Amsterdam, Gilead Sciences, Huidstichting Chanfleury van IJsselsteijn, and ViiV
Healthcare is gratefully acknowledged.
© 2014 Jannie van der Helm, Amsterdam, the Netherlands
Published articles were reprinted with permission from the publishers. No part of this thesis may be
reproduced, stored or transmitted without the prior permission of the author or, when appropriate,
the publishers of the articles.
International
on HIV, HCV and STI
Academisch proefschrift
ter verkrijging van de graad van doctor
aan de Universiteit van Amsterdam
op gezag van de Rector Magnificus
prof. dr. D.C. van den Boom
ten overstaan van een door het college voor promoties
ingestelde commissie, in het openbaar te verdedigen in de Agnietenkapel
op vrijdag 26 september 2014, te 10:00 uur
door
Jannie Johanna van der Helm
geboren te Meppel
Promotiecommissie
Promotores:
Prof. dr. H.J.C. de Vries
Prof. dr. M. Prins
Co-promoter:
Dr. R.B. Geskus
Overige leden:

Prof. dr. R.A. Coutinho
Prof. dr. P.R. Klatser
Prof. dr. K. Porter
Prof. dr. J.M. Prins
Prof. dr. M.A. de Rie
Prof. dr. J. Schuitemaker
Faculteit der Geneeskunde
Table of contents
9
Chapter 1
Introduction
Chapter 2
HIV progression
25
Long-term non-progression of HIV-1 infection. (Submitted).
27
HIV and HCV coinfection
47
2.1
Chapter 3
3.1
The hepatitis C epidemic among HIV-positive men who have sex
with men: incidence estimates from 1990-2007.
AIDS 2011 May 15;25(8):1083-1091.
49
3.2
Effect of hepatitis C infection on cause-specific mortality after HIV seroconversion, before and after 1997.
Gastroenterology, 2013 Apr;144(4):751-760.e2.
65
Chapter 4
Chlamydia infections in Suriname and the Netherlands
87
4.1
Urogenital Chlamydia trachomatis infections among ethnic groups in Paramaribo, Suriname; determinants and ethnic
sexual mixing patterns.
PLoS One. 2013 Jul 17;8(7):e68698.
89
4.2
Chlamydia trachomatis transmission networks between
Suriname and Amsterdam.
PLoS One. 2013 Nov 13;8(11):e77977.
107
4.3 Distinct transmission networks of Chlamydia trachomatis in men
having sex with men and heterosexual adults in Amsterdam, the
Netherlands.
PLoS One. 2013;8(1):e53869
127
STI diagnostic test evaluations
145
Point-of-care test for detection of urogenital chlamydia in
147
Chapter 5
5.1
women shows low sensitivity. A performance evaluation study
in two clinics in Suriname.
PLoS One. 2012;7(2):e32122.
5.2
High performance and acceptibility of self-collected rectal
swabs for diagnosis of Chlamydia trachomatis and Neisseria
gonorrhoeae in men who have sex with men and women. Sex Transm Dis. 2009 Aug;36(8):493-7.
161
5.3
Clinical value of Treponema pallidum real-time PCR for diagnosis of syphilis.
J Clin Microbiol. 2010 Feb;48(2):497-502.
173
General discussion
187
Chapter 6
Appendix
201
Summary
203
Samenvatting
207
Dankwoord
211
Curriculum Vitae
213
List of publications
214
Portfolio
216
List of abbreviations
95% CI 95% confidence interval
aHR adjusted hazard rate
AIDS acquired immune deficiency syn-
drome
ART antiretroviral therapy
cART combination antiretroviral therapy
CASCADEConcerted Action on SeroConver-
sion to AIDS and Death in Europe
COD cause of death
CRT Chlamydia rapid test
CSW commercial sex worker
Ct / CT Chlamydia trachomatis
DAA direct-acting antivirals
DNA desoxyribonucleic acid
FDA United States Food and Drug Admi-
nistration
FP family planning (clinic)
FTA fluorescent treponemal antibody (test)
GP general practitioner
HAART highly-active antiretroviral therapy
HAV hepatitis A virus
HBV hepatitis B virus
HCV hepatitis C virus
HIV human immunodeficiency virus
HLA human leucocyte antigen
HPTN HIV prevention trials network
HSV herpes simplex virus
IATA international air transport association
IDU injecting drug user
IFU inclusion forming units
IQR interquartile range
LGV lymphogranuloma venereum
LPS lipopolysaccharide
LTNP long-term non-progression
MLST multi-locus sequence typing
MSM men who have sex with men
MSMO men who have sex with men only
MSMW men who have sex with both men and women
MSW
NA
NAAT NG
NPV
ompA
OR
PCR
PEP
PID
POC
PPV
PrEP
PRS
PY
RNA
rRNA
RPR
SDA
SNP
SPSS
SRS
ST
STARD
STI
TasP
TPPA
WHO
sex between men and women
not available
nucleic acid amplification test
Neisseria gonorrhoeae
negative predictive value
gene that encodes the major outer
membrane protein
odds ratio
polymerase chain reaction
post-exposure profylaxis
pelvic inflammatory disease
point-of-care (test)
positive predictive value
pre-exposure profylaxis
provider-collected rectal swab
person-years
ribonucleic acid
ribosomal ribonucleic acid
rapid plasma reagin (test)
strand displacement amplification
single-nucleotide polymorphism
statistical package for the social
sciences
self-collected rectal swab
sequence type
STAndards for the Reporting of Diagnostic accuracy studies
sexual transmitted infection
treatment as prevention
Treponema pallidum particle agglutination (test)
World Health Organization
1
Introduction
9
10
Chapter 1
HIV worldwide
AIDS is caused by the human immunodeficiency virus (HIV) and was diagnosed for the first
time in 1981.1 Since then, more than an estimated 25 million people have died from the
disease. In 2012, an estimated 35 million people were living with HIV/AIDS worldwide, with
2.3 million new infections occurring in that year.2,3 Sub-Saharan Africa is hardest hit, and
is still the area where most infections occur. As more than 1% of the general population is
affected, the Sub-Saharan African situation is considered a generalised epidemic. However,
though on another scale, the HIV epidemic is also growing rapidly in Eastern Europe and
Central Asia. In Europe, the epidemic is a concentrated epidemic as the HIV prevalence is
<1% among the general population, but >5% in at least one high-risk subpopulation.4 The
predominant mode of HIV transmission in Western Europe is sex between men, while in
Eastern Europe injecting drug use is the predominant mode. Modes of transmission have
changed over time, for example, most haemophiliac patients in high-income countries
acquired HIV at the beginning of the HIV epidemic as screening of donated blood was not
introduced until 1985. Over time, the proportion of HIV-positive men and women infected
through heterosexual contact has increased. The introduction and widespread use of
combined antiretroviral treatment (cART) in high-income countries in the mid-1990s has
led to a strong decline in the overall mortality and morbidity among HIV-infected persons.5
In the Netherlands, it was estimated that between 20.000 and 34.000 individuals were
living with HIV in 20126 of whom 27% were likely to be unaware of their infection.7 The HIV
epidemic in the Netherlands, which was concentrated among injecting drug users (IDU) and
men having sex with men (MSM) in the 1980s, remains concentrated among MSM, but is
also observed heterosexuals originating from HIV-endemic countries.
Natural history of HIV infection
HIV impairs the function of the immune system by targeting CD4 cells which are a crucial
element of the immune system.8 A typical pattern of HIV infection is characterised by three
phases: the acute or primary infection, the asymptomatic, and the symptomatic phase or
development of AIDS (Figure 1). Acute infection is characterised by a dramatic decrease in the
number of CD4 cells, followed by a return to a near normal level within 3 to 4 months.9 During
the asymptomatic phase a gradual decline in the number of CD4 cells occurs over time.9 The
plasma viral load is very high during the primary phase and therefore HIV is transmitted more
easily during this phase.10 Without therapy, the median time to development of AIDS is 10
years, but depending on age can vary between 5 and 11 years after HIV-1 acquisition.11,12
However, some individuals progress to AIDS within 2 to 5 years after seroconversion, the
so-called rapid progressors, while others remain clinically and immunologically stable for
more than 10 years after seroconversion, the so-called long-term non-progressors.9 Another
special group are those who are able to naturally suppress the virus (HIV or elite controllers)
11
10 7
1250
Asymptomatic phase
750
10 5
CD4 + lymphocytes
10 4
500
Plasma virus load
250
10 3
Primary
infection
6
12
Time (weeks)
2
4
6
8
Time (years)
10
Virus RNA load (copies/ml plasma)
10 6
CD8 + lymphocytes
Cells (
10 6 /l plasma)
1000
AIDS
for an extended period.
Studies among these
specific groups of patients
may yield important
information
on
the
correlates of control of
infection, which might
be beneficial for the
development of effective
vaccines [Chapter 2.1].
12
Hepatitis C worldwide
Hepatitis C virus (HCV)
was identified in 198913
and an estimated 130-170
million people are chronically infected with the hepatitis C virus. HCV is the leading cause
of chronic liver disease.14 It is estimated that 3-4 million new HCV infections occur every
year and more than 350.000 people die from HCV-related liver disease.15 Prevalence of
HCV is highest in Egypt (15-20%) because of a mass parenteral treatment campaign against
schistosomiasis that took place from 1920 to 1980 in which the injection materials were not
sufficiently sterilised before re-use.16 After HCV screening of donor blood was introduced
in high-income countries, IDU became the main risk group acquiring new HCV infections.17
As with HIV, haemophiliac patients and other recipients of blood products were among
the main HCV risk groups prior to donor blood screening in 1991.18 HIV is considered a
bloodborne and sexually transmitted infection. However, sexual transmission of HCV is
considered inefficient based on studies among discordant heterosexual couples. Acute HCV
infections among HIV-positive men who have sex with men (MSM) have been identified in
the Netherlands and across the Western world since 2000. As most of the men with acute
HCV denied injecting drug use, this reopened the discussion on the importance of sexual
transmission.19 Interestingly, a phylogenetic study indicated that the spread started before
2000.20 To reveal more about the onset of the HCV epidemic, we estimated the incidence of
HCV among HIV-positive MSM, mainly from Western Europe, from 1990-2007 [Chapter 3.1].
In recent years several studies have been conducted in the Netherlands to gain
insight into HCV seroprevalence among the general population21 and in subpopulations
at increased risk.22-24 The estimated national seroprevalence was 0.22% (95% confidence
interval, 0.07-0.37%), corresponding to 28.100 HCV-infected individuals. First-generation
migrants from HCV-endemic countries accounted for the largest group, followed by IDU and
HIV-positive MSM.21
Figure 1. Course of HIV-1 disease progression among individuals not using antiretroviral therapy.⁸
12
Chapter 1
Natural history of HCV infection
HCV is mainly an asymptomatic disease, and in its acute phase around 30% of cases
experience aspecific flulike symptoms.25,26 Natural clearance of HCV occurs in about 25%30% of the patients, usually within 6 months following acute infection.27,28 After 20-30 years
of chronic HCV infection without treatment, serious complications such as liver cirrhosis
occur in 2-30% of the patients, of whom 1-4% develop hepatocellular carcinoma.25 Standard
treatment of HCV with peg-interferon and ribavirin became available in 1998 and successful
treatment outcome varied between 50% and 80% depending on HCV genotype and the
severity of HCV-associated disease.29,30 Since 2011 two new treatment options became
available and currently major improvements have been made in the development of more
effective and tolerable HCV therapy, and combination direct-acting antivirals (DAA) therapy
will be generally available in the near future.31
HIV and HCV co-infection
Due to shared routes of transmission, co-infection with both HIV and HCV occurs relatively
frequently. It is estimated that 20-30% of HIV-infected persons are co-infected with HCV.27
The effect of HIV on HCV progression is well known and is associated with lower rates of
spontaneous HCV clearance (<10%), accelerated progression of liver disease, increased risk
of cirrhosis and hepatocellular carcinoma, and a less favourable HCV treatment outcome.27,32
Because HIV-infected persons live longer in the cART era, they are increasingly more likely to
die from non-HIV-related causes33, including the sequels of hepatitis infections.34 However,
controversy remained as to whether HCV co-infection affected HIV disease progression.35-37
Therefore, in Chapter 3.2, we studied the impact of HCV co-infection on cause-specific
mortality, including HIV and/or AIDS and hepatitis or liver-related mortality, and evaluated
whether the introduction of cART had any effect.
Sexually transmitted infections worldwide
In total, it is estimated that 500 million new infections of curable STI such as syphilis,
gonorrhoea, chlamydia, and trichomoniasis occur globally every year.38 In Europe, chlamydia
(caused by the bacteria Chlamydia trachomatis) is the most prevalent STI, mainly affecting
young heterosexual persons below 24 years of age.39,40 The chlamydia prevalence in low
and middle-income countries has been studied to a much lesser extent, but is considered
even higher in comparison with high-income countries.41 Gonorrhoea (caused by the
bacteria Neisseria gonorrhoeae) is most frequently reported among MSM, especially HIVpositive MSM, compared with heterosexual adults in the Netherlands.42,43 Both chlamydia
and gonorrhoea are important causes of infertility among men and women. Moreover,
they can cause debilitating gynaecological conditions like pelvic inflammatory disease and
ectopic pregnancy.44 Syphilis is an infection caused by the spirochete Treponema pallidum,
13
subsp. pallidum, characterised by three stages and can result in serious sequellae when
left untreated, such as cardiovascular syphilis and neurosyphilis. In high-income countries,
it is mainly observed among MSM, especially ≥35 years of age. In Sub-Saharan Africa,
congenital syphilis (transmitted from mother to child during pregnancy) is a major cause
of peri- and ante-natal mortality and morbidity.45 Chlamydia, gonorrhoea, and syphilis can
all be treated well with antibiotics. However, emerging antimicrobial resistance against the
last empirically proven effective drug for gonorrhoea makes this STI a future health problem
with possibly significant implications.38,46 In the Netherlands, STI are concentrated in highrisk groups such as specific migrant populations, young adults, and MSM. At the STI clinics
in the Netherlands in 2012, chlamydia was the most frequently diagnosed condition (12% in
the total population), with a positivity rate of 19% among heterosexual men and women of
15-19 years. Overall the positivity rate of gonorrhoea was 3.6%, but 9.3% among MSM. The
positivity rate of syphilis was 2.1% among MSM.43
HIV and STIs
STI co-infections are common in HIV-infected individuals and in the last decade the
incidence and prevalence of HCV has increased among HIV-positive MSM.19 STIs increase
the risk of HIV transmission by increasing both the infectiousness of, and the susceptibility
for HIV infection.10,45 HIV infectiousness is enhanced by a higher concentration of HIV in
genital secretions among STI co-infected individuals. Furthermore, the replication of HIV is
increased in the presence of STI such as chlamydia.10 STI enhance HIV susceptibility by leading
immune cells (which are the potential target cells for HIV infection) to the site of infection.
Moreover, ulcerative STI like syphilis and genital herpes break down the protective mucosal
barrier facilitating the transmission of HIV. Some STIs, like genital herpes, can increase the
risk of HIV acquisition among HIV-negative individuals three-fold or more.10,38,47 Although
it has been suggested that STI co-infections might influence HIV disease progression45, firm
evidence is lacking and an effect is not likely.48
Preventive measures for HIV, HCV, and STI
Prevention methods can be classified into primary, secondary, and tertiary methods,
depending on the stage in the natural history of a disease at which they are implemented.49
Primary prevention is focused on avoidance of infection, such as interventions that lead to
reduced risk behaviour and vaccination. For example, the widespread coverage of harm
reduction programmes, including needle exchange and opiate substitution therapy, have
contributed to the decline in HIV and HCV transmission among IDU in Amsterdam.50,51
Reduction of the number of partners, consistent condom use, and regular checks for STI are
important HIV transmission preventive strategies.52 Vaccination is one of the most powerful
primary preventive measures in public health and has had a major impact on the spread of,
14
Chapter 1
for example, hepatitis B.53 Unfortunately, no effective vaccinations are currently available
to prevent HIV and HCV infection. Likewise, vaccination against bacterial STIs (gonorrhoea,
syphilis and chlamydia) is not foreseeable in the near future.54 Secondary prevention is
aimed at detection of infection at the earliest possible stage, before the occurrence of
clinical symptoms, and to intervene in ways that prevent or reduce the risk further spread
of infection among the population. An example is screening to detect a disease such as
chlamydia among individuals without symptoms.55 Detection of disease will be discussed in
more detail below. Tertiary prevention is aimed at the reduction of disease progression and
maximising quality of life. For example, treatment of HIV has significantly reduced morbidity
and mortality among HIV-positive individuals.5 For preventive measures to be effective and
measurable one needs to know the factors that drive the epidemic, such as transmission
routes, risk behaviour, risk populations, and characteristics of the infectious agent [Chapter
4]. Also, for a high uptake it is essential to know how to reach and motivate target populations
to undergo the intervention. Moreover, economic and political factors play a major role, as,
for example, lack of resources hamper implementation of interventions. In addition, certain
countries criminalise MSM or IDU, and as such harm-reduction interventions may not be
implemented.
Detection of disease
Timely HIV testing and counselling have always been critical but became especially important
when cART became available in the mid-1990s. Knowledge of HIV status and timely start of
treatment greatly improves the patient’s prognosis and cART use reduces transmission to
partners. Currently, HIV testing is offered as a standard part of an STI check-up at STI clinics
in the Netherlands and many other countries, in accordance with the opt-out strategy,
which has greatly increased the number of tested individuals.56 A wide spectrum of HIV test
options is available such as lab-based blood tests with very short window periods to detect
early infection, rapid (point-of-care) tests, and also HIV self tests using oral mucosal swabs.
Standard HCV testing in high-income countries includes screening for HCV antibodies.
If positive an HCV RNA test will be performed to establish the presence of replicative HCV
infection. In response to the high HCV prevalence found among HIV-infected MSM,57 HCV
antibody screening has been offered to all HIV-positive MSM and MSM who opt out of HIV
testing visiting the Amsterdam STI outpatient clinic since November 2007. In addition, a
rise in alanine aminotransferase (ALT) is considered a reason to test for acute HCV in HIVinfected MSM in HIV treatment centres.58
Studies have shown that acute HIV infections substantially contribute to further
spread.59 For HCV the contribution of acute infections to further spread is less clear.60 To
detect HIV or HCV at a very early stage (resp. 1 week and 1-3 weeks after infection), an RNA
test is necessary as an antibody response will appear up to 3 months for HIV infection and
15
20-150 days for HCV mono-infection.25,59
For the detection of chlamydia and gonorrhoea in high-income countries, Nucleic Acid
Amplification Tests (NAAT) have become the standard diagnostic method. NAAT tests are far
more sensitive and specific than cultivation and other now obsolete diagnostic methods.
We have evaluated a NAAT test for primary syphilis in a clinical setting [Chapter 5.3]. Apart
from provider-collected samples, NAAT can also be performed on self-collected samples
by the patient [Chapter 5.2]. However, NAAT are expensive and require sophisticated
laboratory conditions and are therefore not available in most low-resource settings.38,61
In settings were resources to test for STI are completely lacking, syndromic algorithms
based on the symptomatology can be used to guide treatment. However, as most STI occur
without symptoms, this approach lacks sensitivity.38,62 The World Health Organization
(WHO) has launched a priority programme that is designated to develop affordable and
reliable point-of-care (POC) tests for STIs that are predominant in low-resource countries.
In this programme, WHO has formulated the ASSURED acronym built on the criteria that
POC tests have to meet: Affordable, Sensitive, Specific, User-friendly, Robust and rapid,
Equipment-free, and Deliverable to those who need them.63 The POC test result should be
readily available while the patient waits to ensure prompt treatment. POC tests available
for systemic infections like HIV and syphilis are highly sensitive since they are based on
the detection of serum antibodies.64 However, as development of antibodies for HIV can
take up to 12 weeks after infection, antibody-based tests will not detect acute infections.
Infections such as chlamydia and gonorrhoea are caused by organisms that, in most cases,
remain confined to mucosal tissue and normally invoke little to no production of antibodies.
Therefore, the development of POC tests to diagnose mucosal chlamydia infections based
on the detection of serum antibodies is, at least for the present, not an option. One POC test
for urogenital chlamydia (Diagnostics of the Real World, Cambridge, UK) has been developed
based on detecting chlamydial antigen (LPS) and the manufacturer asserted a sensitivity of
over 80%. We evaluated the performance of this promising POC test in Suriname, with the
objective of using this test as a diagnostic tool to halt the chlamydia epidemic [Chapter 5.1].
Data used in this thesis
The two main data sources for this thesis were the CASCADE Collaboration in EuroCoord and
CUSTEPA study (Table 1). In addition, data collected at the Amsterdam and South Limburg
STI clinics was used.
CASCADE: Concerted Action on SeroConversion to AIDS and Death in Europe
CASCADE collaboration was first established in 1997, is currently part of EuroCoord (www.
EuroCoord.net), and is a collaboration between the investigators of 28 cohorts following
persons with well-estimated dates of HIV seroconversion (seroconverters). Twenty-one of
16
Chapter 1
Table 1. Overview of data sources and study populations used in this thesis.
Data source
CASCADE
Collaboration in
EuroCoord
Study population
HIV-positive
MSM,
heterosexual men
and women,
those with
haemophilia,
and IDU
Countries
Australia, Austria,
Canada, France,
Germany,
Greece, Italy,
the Netherlands,
Norway, Spain,
Switzerland,
United Kingdom,
Uganda and
Zimbabwe
France,
Germany, Italy,
the Netherlands,
Norway, Spain,
Switzerland,
United Kingdom
N
4979
Study period
1979-2011
Chapter
2.1
CASCADE
Collaboration in
EuroCoord
HIV-positive MSM
3014
1990-2007
3.1
CASCADE
Collaboration in
EuroCoord
HIV-positive MSM,
heterosexual men
and women,
those with
haemophilia,
and IDU
Canada, France,
Greece,
the Netherlands,
Norway, Spain,
Switzerland,
United Kingdom
9164
1979-2007
3.2
CUSTEPA study
Heterosexual men
and women, and
a few MSM
included at an STI
clinic and a family
planning clinic
Suriname
1508
2008-2010
4.1
CUSTEPA study
Chlamydia positive
heterosexual men
and women
included at two
STI clinics and a
family planning
clinic
Suriname,
The Netherlands
420
2008-2010
4.2
CUSTEPA study
and MSM
network study
Chlamydia positive
heterosexual men
and women,
and MSM
The Netherlands
526
2008-2010
4.3
CUSTEPA study
Heterosexual
women
MSM and
heterosexual
women
Suriname
912
2009-2010
5.1
The Netherlands
2394
2006-2007
5.2
MSM and
heterosexual men
and women
The Netherlands
849
2006-2008
5.3
STI clinics in
Amsterdam and
South Limburg
STI clinic in
Amsterdam
17
these cohorts are European, including the Amsterdam Cohort Studies among drug users
and homosexual men. It is currently a network of epidemiologists, statisticians, virologists,
and clinicians from lead HIV institutions in Europe, Australia, Canada, and Sub-Saharan
Africa. Seroconverters are enrolled into the individual cohorts locally and nationally and are
typically followed up life-long. CASCADE’s main aim is to monitor newly infected individuals
and those already enrolled in studies, covering the entire duration of HIV infection. The
main premise is that through pooling data, this collaborative study is able to address
issues, which cannot be reliably addressed from single studies alone. The current dataset
(pooled in September 2013) includes data on 30.006 individuals with a documented HIV
seroconversion date.
CUSTEPA: Chlamydia Urogenitalis Snelle Test Evaluatie in Paramaribo en Amsterdam
[Urogenital Chlamydia Rapid Test Evaluation in Paramaribo and Amsterdam]
The CUSTEPA study was initiated to evaluate a Point-of-Care (POC) rapid test for the
detection of urogenital chlamydia infections in STI high-risk populations in Paramaribo,
Suriname, and Amsterdam, the Netherlands. Sub goals were to estimate the prevalence of
urogenital chlamydia in STI high-risk and low-risk populations in Suriname, to investigate
the effect of travelling between Suriname and the Netherlands on the transmission of
urogenital chlamydia between the 2 countries, and establishing chlamydia NAAT diagnostics
in Suriname. Between 2008 and 2010 participants were recruited at the STI clinic of the
Dermatological Service and at Stichting Lobi (a family planning clinic) both located in
Paramaribo, Suriname, and at the outpatient STI clinic of the Public Health Service of
Amsterdam, the Netherlands. All participants filled out a questionnaire about demographic
characteristics and sexual behaviour, men provided a urine sample, and nurses collected
vaginal swabs from women.
MSM network study
The MSM network study was initiated to identify high-risk transmission networks and
bridges between subpopulations of MSM, as epidemiological data suggest that not all
MSM are at increased risk for STIs. Recruitment of MSM aged ≥18 years took place at the
outpatient STI clinic of the Public Health Service of Amsterdam from July 2008 to August
2009. Standard STI testing was performed including chlamydia, gonorrhoea, and syphilis,
plus HIV using an opt-out strategy. Moreover, hepatitis B serology was done unless a client
was known to have a (past) hepatitis B infection. HIV-infected MSM and those who opted
out for HIV testing were tested for hepatitis C antibodies. In this study epidemiological and
behavioural data, including characteristics of up to four partners, from a computer-assisted
self-interview (CASI) or a paper version of CASI was combined with molecular typing of
Chlamydia trachomatis and Neisseria gonorrhoeae.
18
Chapter 1
Epidemiology
Epidemiology as a research discipline plays an important role in the control of infectious
diseases through, for example, identifying new and ongoing infections, identifying risk
groups, describing transmission networks, characterising risk factors, estimating predictors
of disease progression, and evaluating prevention strategies. Certainly, epidemiology
is most powerful when it is combined with other data sources coming from adjacent
fields like clinical data, immunology, virology, genetics, and psychosocial sciences. Such a
multidisciplinary approach can enrich the analysis, conclusions and recommendations.65
Most studies in this thesis had a multidisciplinary approach. Furthermore, different study
designs have been used depending on the research question. The cohort studies within
the CASCADE collaboration collect longitudinal data from the same individuals over time,
providing incidence estimates and information about the natural history. Furthermore,
risks of various end points like, risk of acquisition, AIDS, or death can be determined. The
CUSTEPA study has a cross-sectional design. Since data were collected at one moment in
time, prevalence could be estimated and associations between determinants and presence
of a disease could be described. Cross-sectional studies are relatively quick and easy
but cannot distinguish between cause and effect. As cohort studies measure events in
chronological order they can be used to distinguish between cause and effect, but a problem
can be residual confounding. For example, when individuals do not randomly receive an
intervention, variables that cause one group to receive more interventions compared with
the other group might remain unmeasured. Also, loss to follow-up of some individuals might
be a problem.66 A randomised controlled trial would be the best study design to determine
causal relations of the effect of interventions, however, several practical issues make these
trials difficult to accomplish, including high costs, participant noncompliance with the
treatment regimen, and the need to maintain high follow-up rates over extended periods
of time.49 Also ethical concerns about the use of placebo controls need to be addressed.49
Apart from selecting the appropriate study design, it is important to minimise bias and
apply the appropriate analysis techniques. For example, in this thesis (Chapter 3.2) we
used competing risks analyses. This is important within a cohort setting when the event of
interest (e.g., liver-related deaths), might be preceded by another event (e.g., non-natural
death) which prevents us from observing the event of interest.67 Also, when data collection
was incomplete, we used multiple imputation techniques to deal with missing data (Chapter
2 and 3), as missing data can cause serious bias.68 However, imputation techniques also
need to be applied carefully. When missing data is not at random, multiple imputation may
provide misleading results.
Furthermore, molecular epidemiology was applied. With this approach the
detection and characterisation of the genetic variability of a microorganism is combined
with demographic and behavioural characteristics of its host.69 For example, Chlamydia
19
trachomatis-positive samples collected in CUSTEPA study were genotyped using a distinctive
new typing method, multi-locus sequence typing (MLST), unveiling additional information
on transmission networks.70
Outline of this thesis
This thesis is divided into four parts. The first and second part describes several aspects of
the epidemiology of HIV and HCV; the third part describes the epidemiology of Chlamydia
trachomatis, and the fourth part various diagnostic strategies for STIs. All but one study
were conducted in collaboration with institutes other than the Public Health Service of
Amsterdam (GGD Amsterdam), often combining data from several countries (Table 1).
The studies in Chapter 2 and 3 were conducted in Europe and Canada among HIVseroconverters, of whom a substantial proportion is co-infected with HCV. The study in
Chapter 2 describes individuals with immunological and clinical control of HIV-1 infection
in the first 10 years following seroconversion and factors that were associated with loss of
this control. The first study in Chapter 3 estimated the incidence of HCV among HIV-positive
MSM, in order to gain insight into the emerging HCV epidemic in this group. The second
study reports the effect of HCV co-infection on cause-specific mortality, including mortality
from HIV/AIDS- and hepatitis/liver-related causes of deaths.
Chapter 4 includes three studies on the epidemiology of urogenital chlamydia. The
first study describes the epidemiology of chlamydia in Suriname, mainly focused on ethnic
sexual mixing patterns. In the second study molecular techniques are used to understand
chlamydia transmission networks between Suriname and the Netherlands. The third study
describes transmission networks of Chlamydia trachomatis among MSM and heterosexual
adults in the Netherlands.
Chapter 5 includes three studies evaluating STI diagnostic procedures. The first
study evaluated a POC test to detect urogenital chlamydia in women. The second study
evaluated the performance and acceptability of self-collected rectal swabs for the diagnosis
of chlamydia and gonorrhoea among MSM and women. In the third study the clinical value
of a Treponema pallidum real-time PCR for the diagnosis of syphilis was assessed.
Chapter 6 concludes with a general discussion in which main findings of the work
described in this thesis are discussed and related to recent literature. Recommendations for
prevention and suggestions for future research are presented.
20
Chapter 1
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Chapter 1
2
HIV progression
and HCV co-infection
25
26
Chapter 2.1
Long-term non-progression
of HIV-1 infection
Jannie van der Helm1
Ronald Geskus1,2
Sara Lodi3
Laurence Meyer4
Hanneke Schuitemaker5
Barbara Gunsenheimer-Bartmeyer6
Antonella d’Arminio Monforte7
Ashley Olson8, Giota Touloumi9
Caroline Sabin10
Kholoud Porter8
Maria Prins1,11
on behalf of CASCADE Collaboration in EuroCoord
(Submitted for publication)
1
Public Health Service Amsterdam, Amsterdam, the Netherlands; 2Department of Clinical
Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam,
Amsterdam, the Netherlands; 3Instituto de Salud Carlos III, Madrid, Spain; 4Service d'Epidémiologie
et de Santé Publique, Hôpital de Bicêtre, AP-HP; INSERM U1018; Univ Paris Sud, France; 5Department
of Experimental Immunology, Sanquin Research, Landsteiner Laboratory and Center for Infectious
Diseases and Immunity Amsterdam (CINIMA), Academic Medical Center, University of Amsterdam,
Amsterdam, The Netherlands; 6Robert Koch Institute, Berlin, Germany; 7Department of Infectious
Diseases and Tropical Medicine, Università degli Strudi di Milano H. S. Paolo, Milan, Italy; 8MRC
Clinical Trials Unit at University College London, London, UK; 9Department of Hygiene, Epidemiology
and Medical Statistics, Athens University Medical School, Greece; 10Research Department of Infection
and Population Health, UCL, London, United Kingdom; 11Depertment of Infectious Diseases, CINIMA,
Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands.
Abstract
Background: The characterization of long-term non-progression (LTNP) in HIV infection
may yield important information on the correlates of control of infection. We estimated
long-term progression-free survival after HIV seroconversion and identified determinants
associated with loss of LTNP status.
Methods: We used data on individuals with well-estimated dates of HIV seroconversion from
the CASCADE Collaboration. Non-progression was defined as being HIV-positive without
AIDS, antiretroviral therapy-naive and with CD4 cell counts ≥500 cells/mm3. Longitudinal
methods were used to characterize LTNP.
Findings: Of 4979 included seroconverters, 74·5% were men. Median time to progression
was 2·07 years (95%CI=1·96-2·17) giving estimated progression-free survival at 5, 10 and
15 years of 18·4% (95%CI=17·2–19·6), 4·0% (95%CI=3·6–4·5), and 1·4% (95%CI=0·9–1·5),
respectively. The rate of progression did not change beyond 10 years after seroconversion.
At 10 years of HIV seroconversion, 283 individuals were exhibiting LTNP, of whom 202 lost
this status subsequently (median time to loss 2·5 (95%CI=2·0–2·9) years). In univariable
analyses, loss of LTNP status was significantly associated with CD4 and HIV RNA, but not age,
mode of infection, sex, or calendar year of seroconversion. In the multivariable analyses,
loss of LTNP status was significantly associated with lower CD4 counts at 10 years following
seroconversion.
Interpretation: Progression-free survival is a rare but real phenomenon. Most individuals
exhibiting LTNP will lose immunological and clinical control of HIV infection eventually.
Funding: European Union Seventh Framework Programme (FP7/2007-2013), EuroCoord
grant n° 260694.
28
Chapter 2.1
Introduction
I
n the pre-combination antiretroviral therapy (ART) era, median time from primary infection
to AIDS development ranged from 5-11 years.1 With widespread use of combination ART,
this period has lengthened substantially. Of interest, some individuals appear able to remain
AIDS-free with a high and stable CD4 cell count without ART for many years.2 In the mid1990s, there was a strong focus on studying such individuals with long-term non-progression
(LTNP). When viral load measurements became available,3 the interest shifted to those who
were able to naturally suppress the virus (HIV or elite controllers).4 Studies among these
specific groups of patients may yield important information on the correlates of control of
infection, which might be beneficial for the development of effective vaccines.5
Studies on LTNP are difficult to compare because of heterogeneity in the definitions
of non-progression, study design, and lengths of follow-up.6-10 Moreover, these studies are
often limited by small sample size and lack of knowledge of the date of seroconversion.
In addition, LTNP has generally been determined cross-sectionally at a fixed time, e.g., at
8 years following infection.6,7 It has been suggested that those with LTNP consist of slow
progressors11 who eventually will experience disease progression rather than being a
distinct subpopulation able to naturally control HIV disease.12,13 Moreover, it is unknown
how rare/common non-progression is beyond 10 years after infection, and whether those
with LTNP completely lack signs of HIV disease progression with continued follow-up.
The CASCADE Collaboration comprises one of the largest groups of HIV-positive
individuals worldwide with known dates of HIV seroconversion, of diverse risk groups,
and with long follow-up. As such, the study provides a unique opportunity to study LTNP.
We, therefore, examined the probability of progression-free survival, the rate of loss
of non-progression status and characteristics of those exhibiting LTNP at 10 years of HIV
seroconversion. Furthermore, we studied the probability of retaining LTNP status, and
factors associated with loss of LTNP status after 10 years of HIV infection.
Methods
Study population
CASCADE (Concerted Action on SeroConversion to AIDS and Death in Europe) is a
collaboration within EuroCoord (www.EuroCoord.net), currently consisting of 28 HIV
seroconverter cohort studies in Europe, Australia, Canada, and sub-Saharan Africa. All
collaborating cohorts received approval from their regulatory or national ethics review
boards (see Appendix). Details of CASCADE are described elsewhere.14 In brief, CASCADE
29
data comprise a total of 25,629 HIV-positive individuals who had their seroconversion date
estimated by the midpoint between a last negative and first positive test separated by ≤3
years (n=21,670; 85%), the date of laboratory evidence of seroconversion (n=3231; 13%),
the date of seroconversion illness together with negative and positive tests separated by ≤3
years (n=522; 2%), or the most likely date that infected factor VIII concentrate infusion for
men with haemophilia was given (n=206; 1%). The first enrolment into an individual cohort
was in 1979 and data pooled in May 2011 were used.
For these analyses we included individuals aged ≥15 years at seroconversion who
had at least two CD4 cell count measurements ≥6 months following seroconversion, of
which at least one was in the first 10 years following seroconversion. The estimated date of
seroconversion had to be at least 10 years before the administrative censoring date of each
individual cohort.
Definition of long-term non-progression
Non-progression was defined as being HIV-positive AIDS-free, ART-naive and never having
a CD4 cell count <500 cells/mm3. The end of non-progression status was signalled by ART
initiation, development of an AIDS event, or first measurement of a CD4 count <500 cells/
mm3, whichever occurred first. We excluded CD4 cell counts measured in the first 6 months
following HIV seroconversion as CD4 counts may drop sharply soon after seroconversion
and subsequently rebound.2 LTNP was defined as non-progression during the first 10 years
following seroconversion. AIDS diagnosis was based on the Centers for Disease Control
revised case definition.15
Statistical analyses
Follow-up was calculated from HIV seroconversion until the date of event or censoring.
Individuals were included in the risk set from the later date of cohort enrolment or first CD4
cell count measurement ≥6 months after seroconversion. Patient follow-up was censored
at the date when they were last assessed for CD4 cell count or ART, whichever occurred
first. Kaplan-Meier methods were used to estimate the probability of progression-free
survival among all individuals and among those who were free of progression at 10 years
after seroconversion. To investigate trends in the rate of loss of non-progression status,
hazard rates over time since seroconversion were estimated using Poisson regression. A Cox
proportional hazards model was used to identify determinants associated with loss of LTNP
status beyond 10 years. Factors considered were age at seroconversion, mode of infection,
sex, calendar year of seroconversion, baseline CD4 cell count (first measurement between
6 months and 3 years following HIV seroconversion), nadir CD4 cell count in the first 10
years following seroconversion, CD4 cell count at 10 years from HIV seroconversion (or the
latest in the 3 years preceding this), baseline HIV RNA load (first measurement between
30
Chapter 2.1
6 months and 3 years following HIV seroconversion) and HIV RNA load at 10 years of HIV
seroconversion (or the latest in the 3 years preceding this). Restricted cubic splines were used
to model the effect of CD4 cell count and HIV RNA. Missing HIV RNA values and values below
the detection limit were imputed using multiple imputation techniques. Missing mode of
infection (4 individuals) was imputed at random using the distribution of the corresponding
variable. SPSS version 19.0 (SPSS Inc., Chicago, USA), STATA version 11.2 (College Station,
Texas, USA), and R version 3.0.1 (Vienna, Austria)16 were used for the analyses.
The robustness of the estimated progression-free survival and retention of LTNP
status was checked with sensitivity analyses with respect to the role of CD4 count <500
cells/mm3 in the definition of non-progression:
1A). We estimated the time when the CD4 count would have dropped below 500 cells/mm3
based on individual CD4 slopes (which were based on CD4 counts measured prior to ART
initiation only). These were obtained by fitting a linear regression model for each individual
with time as the only covariate. A square root transformation was applied to the CD4 cell
count to better normalize the marker distribution as previously described.17 Individuals were
excluded from the analysis if the estimated CD4 value was <500 cells/mm3 at the moment of
the first observed CD4 measurement.
1B). Using the same method as method 1A, we required at least four CD4 cell count
measurements to estimate the individual slopes instead of two.
2). Progression was defined as two consecutive observed CD4 cell count measurements
<500 cells/mm3 rather than one. Therefore, individuals had to have at least three CD4 cell
count measurements. Follow-up on individuals who did not experience two consecutive
CD4 counts below <500 cells/mm3 was censored at the date of the penultimate CD4 cell
count measurement. When an individual had two consecutive CD4 counts <500 cells/mm3,
the time to crossing the CD4 <500 cells/mm3 threshold was estimated by interpolation
between the first measurement CD4 <500 cells/mm3 and the previous one.
Role of the funding source
The sponsor of the study had no role in study design, data collection, data analysis, data
interpretation, or writing of the report. The corresponding author had full access to all the
data in the study and had final responsibility for the decision to submit for publication.
Results
Study population
The 4979 included seroconverters had a median age at seroconversion of 28 years
31
32
Chapter 2.1
Those exhibiting LTNP
N=283
2742·3
26·7 (22·9-31·1)
115 (40·6)
65 (23·0)
74 (26·1)
4 (1·4)
21 (7·4)
4 (1·4)
204 (72·1)
182 (64·3)
50 (17·7)
13 (4·6)
38 (13·4)
1990 (1987-1993)
55 (19·4)
87 (30·7)
141 (49·8)
19 (11-28)
9 (4-18)
0·47 (0·30-0·64)
840 (690-1078)
629 (567-740)
1090 (825-1342)
756 (627-971)
6 (2-13)
3·20 (2·70-3·84)
2·76 (2·26-3·36)
3·79 (3·25-4·36)
3·43 (2·70-4·13)
Total study population
N=4979
12478·2
28·4 (24·1-34·0)
2371 (47·6)
1088 (21·9)
1035 (20·8)
74 (1·5)
312 (6·3)
99 (2·0)
3708 (74·5)
3084 (61·9)
631 (12·7)
250 (5·0)
1014 (20·4)
1992 (1989-1996)
1202 (24·1)
1162 (23·3)
2615 (52·5)
22 (10-38)
2 (1-5)
0·40 (0·25-0·56)
700 (590-875)
315 (180-468)
881 (713-1115)
12 (5-20)
4·04 (3·30-4·65)
2·30 (1·69-3·14)
4·77 (4·15-5·29)
IQR, interquartile range; LTNP, long-term non-progression.
a
Mixed route (i.e. sex between men and injection drug use; injection drug use and heterosexual contact) or other (e.g., nosocomial infection).
b
Excluding CD4 cell count measurements and HIV RNA measurements in the first 6 months following HIV seroconversion.
c
Missing values ; 1040 for total study population and 87 for LTNP.
Person years of follow-up
Median age at HIV seroconversion (IQR)
Mode of HIV infection (%)
Sex between men
Sex between men and women
Injection drug use
Haemophilia
Mixed route or other a
Unknown
Sex (%)
Male
Origin (%)
Originating from the same country where enrolment into the cohorttook place
Western Europe
Other
Unknown
Median calendar year of HIV seroconversion (IQR)
Hepatitis C virus infection ever (%)
No
Yes
Unknown
CD4 cell count characteristics
Total median number of CD4 cell count measurements since seroconversion (IQR) b
Median number of CD4 cell count measurements during follow up (IQR) b
Median time (years) between CD4 cell count measurementsduring follow up (IQR) b
Median first CD4 cell count (cells/mm3) following HIV seroconversion (IQR) b
Median nadir CD4 cell count in the first 10 years following HIV seroconversion (cells/mm3) (IQR) b
Median maximum CD4 cell count in the first 10 years following HIV seroconversion (cells/mm3) (IQR) b
Median CD4 cell count at 10 years following HIV seroconversion (or latest before)(IQR) b
HIV RNA characteristics
Median number of HIV RNA load measurements in the first 10 years following HIV seroconversion (IQR) b,c
Median first HIV RNA load (log 10 copies/mm3) (IQR)b,c
Median nadir HIV RNA load in the first 10 years following HIV seroconversion (log10 copies/mm3) (IQR) b,c
Median maximum HIV RNA load in the first 10 years following HIV seroconversion (log 10 copies/mm3) (IQR) b,c
Median HIV RNA load at 10 years following HIV seroconversion (or latest before)(IQR ) a,b
Characteristic
Table 1. General characteristics of 4979 HIV-positive individuals with a known date of HIV-seroconversion, and of the 283 who exhibited
long-term non-progression. CASCADE Collaboration, 1979-2011.
Figure 1. Kaplan-Meier estimate of the probability of HIV-1 progression free survival (i.e. antiretroviral therapynaïve, measured CD4+ cell counts ≥500 cells/mm3 and free from clinical AIDS) of 4979 HIV-positive individuals with
a known interval of HIV-seroconversion, 1979-2011, CASCADE Collaboration.
1.0
0.8
0.6
0.4
0.2
0.0
0
0
5
1174
10
283
15
50
20
7
years since seroconversion
Gray area is 95% confidence interval.
[interquartile range (IQR), 24–34] and 74·5% were men. Sex between men was the most
frequent route of infection (47·6%), followed by sex between men and women (21·9%),
injection drug use (20·8%), and receipt of contaminated Factor VIII concentrate in people
with haemophilia (1·5%). The median year of HIV seroconversion was 1992 (Table 1).
Progression-free survival probability and rate of progression
A total of 4246 individuals progressed within 10 years of HIV infection; 3253 due to a CD4
cell count <500 cells/mm3, 729 due to initiation of ART, 81 due to an AIDS event, and 183
due to a combination of these events at the same time. The median time to progression was
2·07 years (95%CI, 1·96-2·17). The estimated progression-free survival probability at 5, 10
and 15 years from seroconversion was 18·4% (95%CI, 17·2–19·6), 4·0% (95%CI, 3·6-4·5), and
1·4% (95%CI, 0·9–1·5) respectively (Figure 1).
The rate of progression over time since HIV seroconversion is shown in Figure 2.
It decreased sharply in the first years after seroconversion from 0·45 (95%CI, 0·43-0·48)
per person year (PY) in the first year to 0·32 (95%CI, 0·30-0·33) per PY at 5 years after
seroconversion. Thereafter the rate continued to decrease, but slowly, to 0·24 (95%CI, 0·190·29) per PY at 15 years after seroconversion and 0·18 (95%CI, 0·10-0·33) per PY at 20 years
after seroconversion.
Long-term non-progression at 10 years following seroconversion
33
Table 2. Cox proportional hazard analyses of factors associated with of loss of long-term non-progression (LTNP) status among 283
HIV-infected individuals with known dates of HIV-seroconversion identified as exhibitingLTNP at 10 years following HIV seroconversion, 1979-2011, CASCADE Collaboration.
Characteristic
HR
p-value
aHR a
p-value
Age at HIV seroconversion (per 10-year increase)
Age at HIV seroconversion
15-24
25-29
30-34
>35
Mode of HIV infection b
Sex between men or sex between men and women
Injection-drug use or people with haemophilia
Sex
Male
Female
Calendar year of HIV seroconversion (per year increase)
Calendar year of HIV seroconversion
<1989
1989-1992
1993-1996
1997
Baseline CD4 cell count (cells/mm 3) c
600
900
Nadir CD4 cell count in the first 10 years following seroconversion (cells/mm3) c
600
900
CD4 cell count at 10 years of HIV seroconversion (cells/mm3) c
600
900
all values
Baseline HIV RNA (log10 copies/mm3) bc
3
4
HIV RNA at 10 years of HIV seroconversion (log 10 copies/mm3) bc
3
4
all values
0·94 (0·77-1·15)
0·544
0·319
1·07 (0·83-1·38)
0·588
1
0·90 (0·65-1·25)
0·66 (0·42-1·04)
0·86 (0·55-1·34)
1
1·08 (0·80-1·44)
1
1·07 (0·78-1·46)
0·98 (0·95-1·02)
1
0·86 (0·62-1·20)
0·83 (0·58-1·19)
0·80 (0·35-1·81)
1
0·80 (0·52-1·23)
1
0·63 (0·40-0·99)
1
0·36 (0·23-0·55)
1
1·27 (0·85-1·91)
1
1·40 (0·92-2·13)
0·621
0·676
0·397
0·719
1
1·04 (0·70-1·54)
1
1·29 (0·87-1·22)
0·82 (0·49-1·38)
0·851
0·197
0·449
0·290
0·084
<0·001
0·090
0·005
1
0·39 (0·24-0·62)
see Figure 4A
1
1·24 (0·81-1·86)
see Figure 4B
<0·001
0·120
LTNP, long-term non-progression
a
Hazard ratios in the multivariable model were adjusted for all factors for which adjusted HR’s are shown. Due to the strong correlation between the measurements of baseline CD4 count, nadir CD4 count and CD4 count at 10 years, these three covariates were not
included together in the multivariable model. Similarly, baseline HIV RNA and HIV RNA at 10 years were not included together in the
same model.
b
Missing mode of HIV infection (n=4) and missing HIV RNA values (n=87) were imputed.
c
HR was estimated using restricted cubic splines. In the table, HR of one value relative to chosen reference value is given.
After 10 years of HIV infection, 283 individuals were classified as exhibiting LTNP. Their
median age at seroconversion was 27 [IQR, 23–31] years and 72.1% were men (Table 1).
Median baseline CD4 cell count was 840 cells/mm3 [IQR, 690-1078] and median baseline
HIV RNA load was 3·20 log copies/mm3 [IQR, 2·70-3·84].
Loss of LTNP status after 10 years
Of the 283 people with LTNP, 202 lost this status after 10 years of HIV seroconversion; 150
due to a decline in CD4 cell count to <500 cells/mm3, 28 due to initiation of ART, 7 due to
development of an AIDS event, and 17 due to a combination of these events simultaneously.
Median time to loss of LTNP status was 2·49 years, (95%CI, 2·05–2·92 years) (Figure 3).
The estimated progression-free survival among those with LTNP at 15 and 20 years from
seroconversion was 29·6% (95%CI 23·8–35·6) and 8·6% (95%CI 4·3–14·8) respectively.
Table 2 shows the results of univariable and multivariable analysis of factors associated
with loss of LTNP status. In univariable analysis the loss of LTNP status was significantly
associated with lower baseline CD4 cell count, lower CD4 cell count at 10 years following
HIV seroconversion, higher baseline HIV RNA, and higher HIV RNA at 10 years following
34
Chapter 2.1
Figure 2. Rate of progression by year since HIV seroconversion of 4979 HIV-infected individuals, 1979-2011,
CASCADE Collaboration.
0.6
rate (per py)
0.4
0.2
0.0
0
5
10
15
20
Restricted cubic splines were used to allow for smoothly varying trends of the hazard rate over time.
Figure 3. Kaplan-Meier estimate of the probability of retaining long-term non-progression status after 10 years of
HIV-seroconversion, 1979-2011, CASCADE Collaboration.
1.0
0.8
0.6
0.4
0.2
0.0
0
0
5
0
10
283
15
50
20
7
35
Figure 4. Association of CD4 cell count and HIV RNA at 10 years after seroconversion with loss of long-term
non-progression (LTNP) status among 283 HIV-positive individuals with a known interval of HIV-seroconversion
identified as exhibiting LTNP at 10 years following HIV seroconversion, 1979-2011, CASCADE Collaboration.
2.00
1.50
1.00
relative hazard
0.75
0.50
0.33
0.25
0.15
500
700
900
CD4
1100
1300
2.00
relative hazard
1.50
1.00
0.75
0.50
0.25
1
2
3
log RNA
4
5
A. Adjusted hazard of CD4 cell count with reference 600 cell/mm3 together with rug plot of CD4 values for those
with event (upper part) and without event (lower part).
B. Adjusted hazard of log HIV RNA with reference 3 log HIV RNA together with rug plot of RNA values for those with
event (upper part) and without event (lower part).
36
Chapter 2.1
cd4
rna
2000
4.0
3.5
1500
●
●
●●
1000
500
●
●
1
●
●
3.0
1
●
●
2.5
2.0
●
1.5
2000
4.0
3.5
1500
●
●
1000
●
●
●
●●
● ●●
●
2
●
●
●
●
●
500
●
3.0
2
2.5
●
●● ●●
●
●
●
●
●
●●
●
●
Figure 5. CD4 and HIV RNA patterns
of 7 individuals who remained free
of progression for ≥20 years after
HIV seroconversion, 1979-2011,
● ● ●
●
2.0
●
●
●
Dots represent observed values;
black dots representing values
during follow-up, grey stars values
after an individual’s follow up was
censored, grey dots values after
an event had taken place. For the
HIV RNA loads, solid dots represent
values above the detection limit,
with the circles representing values
below the detection limit of the HIV
RNA test.
1.5
2000
●
4.0
●
●
●
●
1500
●
●
●
●
●
3
●
3.0
●
●
●
3
2.5
●
2.0
●
500
●
●
●
●
●
●●
●
● ●
●
1000
3.5
●
1.5
2000
4.0
cells/mm³
4
●
1000
●
●
●
3.0
4
2.5
●
●
500
log copies/mL
3.5
1500
●
●
●
●
●
2.0
●
●
1.5
2000
4.0
●
1500
●
●
●
●
● ● ●●
● ● ●● ●● ● ●
●
●
●
●●●●●
●
● ● ●●● ● ●
●
●
●
● ● ●●
1000
●
●
●●
5
●
●
●
5
2.0
●
●
●
●●
3.0
2.5
● ●
● ●
500
3.5
●
●
1.5
2000
4.0
3.5
1500
●
●
●
1000
●
●
6
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
3.0
6
●
2.5
●
●
●
2.0
500
● ●
●
● ●
1.5
2000
4.0
3.5
1500
7
1000
●
500
●
● ● ● ●●
●
●
●
●
●
0
years)
20
●●
●
2.5
●
● ●
●
● ●
●●
10
3.0
7
●
2.0
1.5
●
●
●●
●
●
0
10
years)
20
37
HIV seroconversion. In multivariable analysis, the loss of LTNP status was independently
associated with a lower CD4 count at 10 years following seroconversion (p<0·001). Figure 4A
shows that the adjusted hazard of loss of LTNP status decreased with increasing CD4 cell count.
Although not significant, the adjusted hazard of loss of LTNP status increased with increasing
HIV RNA at 10 years of HIV seroconversion (p=0·12) (Figure 4B). No significant associations
were observed with age at HIV seroconversion, mode of infection, sex or calendar year of
seroconversion. When excluding CD4 cell count from the model because it was part of the
definition of non-progression, higher HIV RNA at 10 years of HIV seroconversion became
independently associated with loss of LTNP status (p=0·009). When baseline CD4 counts and
HIV RNA were included in the model instead of the values measured at 10 years following
seroconversion, results for HIV RNA were comparable (p=0·18), however baseline CD4 cell
count was not significantly associated with loss of LTNP status (p=0·72).
Long-term non-progression at 20 years following HIV infection
Figure 5 shows the CD4 cell count and HIV RNA trajectories for the 7 individuals who still
qualified as exhibiting LTNP at 20 years after HIV seroconversion. They were heterogeneous
with respect to demographic characteristics; 6 of them were male, all modes of infection
were present, age at HIV seroconversion ranged between 19 and 33 years and they
originated from 6 different cohorts. Two of the individuals lost LTNP status (individuals
4 and 7) subsequently. Individual 1 experienced an increase in viral load, which might
indicate progression. The other 4 individuals did not have signs of clinical or immunological
progression and viral load remained relatively stable.
Sensitivity analysis
In the first and third sensitivity analyses the median durations to progression and the median
progression-free survival times after LTNP were very similar. In the second sensitivity analyses
the median progression-free survival time slightly increased to 2·87 years (95%CI, 2·693·00). The estimated progression-free survival at 5, 10 and 15 years from seroconversion
was slightly higher at 26·3% (95%CI, 24·7-27·8), 6·7% (95%CI, 6·0-7·5), and 2·5% (95%CI,
2·0–3·0) respectively. Median progression-free survival time after LTNP was comparable.
Discussion
Our main finding is that LTNP is rare. We also found that progression-free survival decreased
rapidly and was 18·4% (95%CI, 17·2–19·6) and 4·0% (95%CI, 3·6-4·5) at 5 and 10 years after
seroconversion, respectively. To the best of our knowledge, our study is the first to report
38
Chapter 2.1
on median time from seroconversion to loss of non-progression which was 2·07 years [IQR,
1·14-3·99]. In contrast, cross-sectional estimates of LTNP from other studies have ranged
from 0·2% to 22·3%, depending on the definition used.6,7,18,19 Estimating the prevalence
of individuals exhibiting LTNP, especially when the date of HIV seroconversion is unknown,
might result in the exclusion of persons with more rapid progression and, therefore, lead
to an overestimation of the prevalence. In our study, the rate of progression decreased
rapidly over the first few years following seroconversion but remained relatively constant
beyond 5 years. Whilst our data support previous suggestions that individuals with LTNP are
more likely to represent the end of the tail from a distribution than a distinct subpopulation,
we cannot exclude the possibility that some individuals will never experience disease
progression.8,11,12
Those identified with LTNP at 10 years were heterogeneous regarding their
demographic characteristics and viral load, as were those who remained free of progression
for ≥20 years. To identify underlying mechanisms of LTNP, stringent and uniform definition
criteria are important as a small change in definition might have a major impact on the
apparent outcome.6,20 The criteria we used to define LTNP were quite stringent with respect
to follow-up and CD4 cell counts.6,7 The results of retention of LTNP status did not change in
the sensitivity analyses, and all analyses confirmed that LTNP is uncommon.
Although it is not clear what causes the slow, or lack of progression among those with
LTNP, it is likely to be multifactorial,21,22 including infection with an attenuated virus.23,24
However, studies also suggest that non-progressors are infected with a pathogenic virus,
supporting that host, rather than viral, factors are primarily responsible for lack of disease
progression.22 Host genetic factors such as CCR5Δ32 deletion and heterozygous HLA-B57
alleles have been described.21 Recently, a genome-wide association study identified 5
single-nucleotide polymorphisms (SNP) located from class I and III major histocompatibility
complex subregions which were significantly associated with LTNP.5 The literature on
immunologic parameters among those with LTNP is limited and the authors of a recent
review recommended the study of T-cell subsets with pro- and anti-inflammatory properties
such as Th17 and regulatory T-cells, and their role in the preservation of normal CD4 counts
among those with LTNP.22 A recent review reported on the effect of heritability of HIV on
viral load.25 It might be of interest to determine the location of individuals exhibiting LTNP
in a phylogenetic tree to identify any role of heritability of the virus on LTNP.
Only two studies have reported on the loss of LTNP status, using data from HIV
seroconverters. A study from San Francisco reported a median time to loss of LTNP status
after 10 years of HIV infection of 14 years (95%CI, 13·0-14·7), slightly longer than our
estimate of 12·5 years (95%CI, 12·1-12·9).2 A study from France reported a time to loss of
LTNP status comparable to ours, but this was estimated after 8 rather than 10 years since
HIV infection.26 It is well known that older age at HIV seroconversion is associated with more
39
rapid progression to AIDS and death1 and also in our study age was significantly associated
with loss of non-progression in the total study population (data not shown). Interestingly,
our study showed that once someone had been free of progression for ≥10 years, age was
no longer significantly associated with progression, which was also found in the French
study.26
Identifying people with LTNP may become challenging in the future if the trend towards
earlier initiation of combination ART continues; whilst the individual benefits of earlier ART
remain debatable, treatment guidelines now recognise the possibility that the initiation of
ART at a very early time during HIV infection to prevent HIV transmission (‘treatment as
prevention’) may have public health benefits.27,28 Progression-free survival in our study was
low, indicating that, if earlier start of ART is implemented, for the majority this earlier start
will be a few years, which might be short in comparison with the many years of therapy to
follow.
An overlap between the LTNP group and HIV- and elite- controllers has been
reported.18,29 In our study, 30 (21·4%) of the identified people with LTNP also met the
criteria for HIV control, as described in a recent study from CASCADE Collaboration that
identified 140 HIV controllers (data not shown).30
Study limitations include that we were not able to estimate ethnicity-specific
progression-free survival and, therefore, our results might not be generalizable to nonWestern countries. However, both Western and non-Western individuals were identified as
LTNP, suggesting that this phenomenon is not restricted to a single ethnic group.
In conclusion, progression-free survival is uncommon but does appear to be a real
phenomenon. The rate of progression does not seem to slow down after 10 years following
seroconversion, suggesting that most individuals exhibiting LTNP will lose immunological
and clinical control of HIV infection eventually. Although lifetime natural control of HIV
is unlikely, studies on the few unique individuals with durable control might help in the
development of prophylactic and therapeutic vaccines.
Panel: research in context
Systematic review
We searched PubMed using the search term ‘HIV’ along with ‘long-term non-progression’,
‘long-term non-progressor’, ‘LTNP’, ‘long-term survivor’, ‘survivor’. Most studies on long-term
non-progression (LTNP) are from the mid-1990s. When viral load measurements became
available, the interest shifted to HIV and elite controllers. The few, more recent, studies on
LTNP were discussed in a review in 20138 that concluded that prevalence estimates differ
40
Chapter 2.1
widely as they partly depend on the required period of follow-up. Also, very few individuals
defined as LTNP have been followed beyond 8 years and remained without any evidence of
disease progression. Most studies report prevalence estimates of LTNP. In contrast, we did
not identify a single study that reported on median time from HIV seroconversion to loss of
non-progression status.
Interpretation
Our large study, consisting of a collaboration between 28 cohort studies, on long-term
non-progression among HIV seroconverters with more than a decade of follow-up, found a
low progression-free survival (median time to loss of status 2·07 years and 18% at 5 years
following infection). This is of interest in this era with ongoing debate on the benefits of
earlier ART. Most individuals exhibiting LTNP will lose immunological and clinical control of
HIV infection eventually. Progression-free survival is a rare but real phenomenon. Studies on
host and viral factors of these individuals exhibiting LTNP may yield important information
on the correlates of control of infection.
Acknowledgements
The research leading to these results has received funding from the European Union Seventh
Framework Programme (FP7/2007-2013) under EuroCoord grant agreement number
260694.
Conflicts of interest
We declare that we have no conflict of interests.
Contributors
JvdH; acquisition of data, study design, drafting of the manuscript, statistical analysis,
analysis and interpretation of data. RG; acquisition of data, study design, statistical analysis,
analysis and interpretation of data and critical revision of the manuscript for important
intellectual content, analysis supervision. SL: acquisition of data, statistical analysis, analysis
and interpretation of data and critical revision of the manuscript for important intellectual
content.
LM, HS, BGB, AdAM, AO, GT, CS; acquisition of data, analysis and interpretation
of data and critical revision of the manuscript for important intellectual content. KP;
acquisition of data, coordination of the data pooling, analysis and interpretation of data
41
and critical revision of the manuscript for important intellectual content, obtaining funding.
MP; acquisition of data, study concept and design, analysis and interpretation of data,
provision of important input for the drafting and critical revision of the manuscript for
important intellectual content, study supervision. All authors approved the final version of
the manuscript.
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2013;27:1839–46.
29. Okulicz JF, Marconi VC, Landrum ML, et
al. Clinical outcomes of elite controllers,
viremic controllers, and long-term nonprogressors in the US Department of Defense HIV natural history study. J Infect Dis
2009;200:1714–23.
30. Madec Y, Boufassa F, Porter K, et al. Natural
history of HIV-control since seroconversion.
AIDS 2013;27:2451–60.
Appendix
Ethics
Ethics approval has been granted by the following committees: Austrian HIV Cohort
Study: Ethik-Kommission der Medizinischen Universität Wien, Medizinische Universität
Graz – Ethikkommission, Ethikkommission der Medizinischen Universität Innsbruck,
43
Ethikkommission des Landes Oberösterreich, Ethikkommission für das Bundesland Salzburg;
PHAEDRA cohort: St Vincent's Hospital, Human Research Ethics Committee; Southern
Alberta Clinic Cohort: Conjoint Health Research Ethics Board of the Faculties of Medicine,
Nursing and Kinesiology, University of Calgary; Aquitaine Cohort: Commission Nationale
de l'Informatique et des Libertés; French Hospital Database: Commission nationale de
l'informatique et des libertés CNIL; French PRIMO Cohort: Comite Consultatif de Protection
des Personnes dans la Recherché Biomedicale; SEROCO Cohort: Commission Nationale de
l'Informatique et des Libertés (CNIL); German HIV-1 Seroconverter Study: Charité, University
Medicine Berlin; AMACS: Bioethics & Deontology Committee of Athens University Medical
School and the National Organization of Medicines; Greek Haemophilia Cohort: Bioethics &
Deontology Committee of Athens University Medical School and the National Organization of
Medicines; ICoNA cohort: San Paolo Hospital Ethic Committee; Italian Seroconversion Study:
Comitato etico dell’Istituto Superiore di Sanità; Amsterdam Cohort Studies in Homosexual
Men and IDUs: Academic Medical Centre, University of Amsterdam; Oslo and Ulleval Hospital
Cohorts: Regional komite for medisinsk forskningsetikk - Øst- Norge (REK 1); Badalona IDU
Hospital Cohort: Comité Ético de Investigación Clínica del Hospital Universitari Germans Trias
i Pujol; CoRIS-scv: Comité Ético de Investigación Clínica de La Rioja; Madrid Cohort: Ethics
Committee of Universidad Miguel Hernandez de Elche; Valencia IDU Cohort: Comité Etico
de Investigación Clínica del Hospital Dr. Peset-Valencia; Swiss HIV Cohort Study: Kantonale
Ethikkommission, spezialisierte Unterkommission Innere Medizin, Ethikkommission beider
Basel, Kantonale Ethikkommission Bern, Comité départemental d'éthique de médecine et
médecine communautaire, Commission d'éthique de la recherche clinique, Université de
Lausanne, Comitato etico cantonale, Ethikkommission des Kantons St.Gallen; UK Register of
HIV Seroconverters: South Birmigham REC; Early Infection Cohorts: Kenya Medical Research
Institute, Kenyatta National Hospital, Uganda Virus Research Institute Science and Ethics
Committee, Uganda National Council for Science and Technology, Uganda Virus Research
Institute Science and Ethics Committee, Uganda National Council for Science and Technology,
University of Zambia Research Ethics Committee, Emory IRB, National Ethics Committee of
Rwanda, University of Cape Town Research Ethics Committee, University of Kwazulu Natal
Nelson R Mandela School of Medicine; Genital Shedding Study Cohort: University Hospitals
of Cleveland, IRB for Human Investigation (CWRU), AIDS Research Committee (ARC), STD/
AIDS Control Programme, Uganda Ministry of Health, Committee on Human Research (CHR),
Office of Research Administration (UCSF), Biomedical Research & Training Institute (BRTI) –
Zimbabwe, Institutional Review Office, Fred Hutchinson Cancer Research Center, Medical
Research Council of Zimbabwe (MRCZ).
CASCADE Steering Committee: Julia Del Amo (Chair), Laurence Meyer (Vice Chair),
Heiner C. Bucher, Geneviève Chêne, Osamah Hamouda, Deenan Pillay, Maria Prins, Magda
Rosinska, Caroline Sabin, Giota Touloumi.
CASCADE Co-ordinating Centre: Kholoud Porter (Project Leader), Ashley Olson, Kate
44
Chapter 2.1
Coughlin, Lorraine Fradette, Sarah Walker, Abdel Babiker.
CASCADE Clinical Advisory Board: Heiner C. Bucher, Andrea De Luca, Martin Fisher,
Roberto Muga.
CASCADE Collaborators: Australia PHAEDRA cohort (Tony Kelleher, David Cooper, Pat
Grey, Robert Finlayson, Mark Bloch) Sydney AIDS Prospective Study and Sydney Primary HIV
Infection cohort (Tony Kelleher, Tim Ramacciotti, Linda Gelgor, David Cooper, Don Smith);
Austria Austrian HIV Cohort Study (Robert Zangerle); Canada South Alberta clinic (John Gill);
Estonia Tartu Ülikool (Irja Lutsar); France ANRS CO3 Aquitaine cohort (Geneviève Chêne,
Francois Dabis, Rodolphe Thiebaut), ANRS CO4 French Hospital Database (Dominique
Costagliola, Marguerite Guiguet), Lyon Primary Infection cohort (Philippe Vanhems), French
ANRS CO6 PRIMO cohort (Marie-Laure Chaix, Jade Ghosn), ANRS CO2 SEROCO cohort
(Laurence Meyer, Faroudy Boufassa); Germany German HIV-1 seroconverter cohort (Osamah
Hamouda, Claudia Kücherer, Barbara Bartmeyer); Greece AMACS (Anastasia Antoniadou,
Georgios Chrysos, Georgios L. Daikos); Greek Haemophilia cohort (Giota Touloumi, Nikos
Pantazis, Olga Katsarou); Italy Italian Seroconversion Study (Giovanni Rezza, Maria Dorrucci),
ICONA cohort (Antonella d’Arminio Monforte, Andrea De Luca.) Netherlands Amsterdam
Cohort Studies among homosexual men and drug users (Maria Prins, Ronald Geskus,
Jannie van der Helm, Hanneke Schuitemaker); Norway Oslo and Ulleval Hospital cohorts
(Mette Sannes, Oddbjorn Brubakk, Anne-Marte Bakken Kran); Poland National Institute of
Hygiene (Magdalena Rosinska); Spain Badalona IDU hospital cohort (Roberto Muga, Jordi
Tor), Barcelona IDU Cohort (Patricia Garcia de Olalla, Joan Cayla), CoRIS-scv (Julia del Amo,
Santiago Moreno, Susana Monge); Madrid cohort (Julia Del Amo, Jorge del Romero), Valencia
IDU cohort (Santiago Pérez-Hoyos); Switzerland Swiss HIV Cohort Study (Heiner C. Bucher,
Martin Rickenbach, Patrick Francioli); Ukraine Perinatal Prevention of AIDS Initiative (Ruslan
Malyuta); United Kingdom Public Health England (Gary Murphy), Royal Free haemophilia
cohort (Caroline Sabin), UK Register of HIV Seroconverters (Kholoud Porter, Anne Johnson,
Andrew Phillips, Abdel Babiker), University College London (Deenan Pillay). African cohorts:
Genital Shedding Study (US: Charles Morrison; Family Health International, Robert Salata,
Case Western Reserve University, Uganda: Roy Mugerwa, Makerere University, Zimbabwe:
Tsungai Chipato, University of Zimbabwe); International AIDS Vaccine Initiative (IAVI) Early
Infections Cohort (Kenya, Rwanda, South Africa, Uganda, Zambia: Pauli N. Amornkul, IAVI,
USA; Jill Gilmour, IAVI, UK; Anatoli Kamali, Uganda Virus Research Institute/Medical Research
Council Uganda; Etienne Karita, Projet San Francisco, Rwanda).
EuroCoord Executive Board: Julia del Amo, Instituto de Salud Carlos III, Spain;
Geneviève Chêne, University of Bordeaux II, France; Dominique Costagliola, Institut National
de la Santé et de la Recherche Médicale, France; Carlo Giaquinto, Fondazione PENTA, Italy;
Jesper Grarup, Københavns Universitet, Denmark; Ole Kirk (Chair), Københavns Universitet,
Denmark; Laurence Meyer, Institut National de la Santé et de la Recherche Médicale,
France; Ashley Olson, University College London, UK; Alex Panteleev, St. Petersburg City AIDS
45
Centre, Russian Federation; Lars Peters, Københavns Universitet, Denmark; Andrew Phillips,
University College London, UK, Kholoud Porter, University College London, UK; Peter Reiss
(Scientific Coordinator), Academic Medical Centre University of Amsterdam, Netherlands;
Claire Thorne, University College London, UK.
EuroCoord Council of Partners: Jean-Pierre Aboulker, Institut National de la Santé et
de la Recherche Médicale, France; Jan Albert, Karolinska Institute, Sweden; Silvia Asandi ,
Romanian Angel Appeal Foundation, Romania; Geneviève Chêne, University of Bordeaux
II, France; Dominique Costagliola (chair), INSERM, France; Antonella d’Arminio Monforte,
ICoNA Foundation, Italy; Stéphane De Wit, St. Pierre University Hospital, Belgium; Peter
Reiss, Stichting HIV Monitoring, Netherlands; Julia Del Amo, Instituto de Salud Carlos
III, Spain; José Gatell, Fundació Privada Clínic per a la Recerca Bíomèdica, Spain; Carlo
Giaquinto, Fondazione PENTA, Italy; Osamah Hamouda, Robert Koch Institut, Germany; Igor
Karpov, University of Minsk, Belarus; Bruno Ledergerber, University of Zurich, Switzerland;
Jens Lundgren, Københavns Universitet, Denmark; Ruslan Malyuta, Perinatal Prevention of
AIDS Initiative, Ukraine; Claus Møller, Cadpeople A/S, Denmark; Kholoud Porter, University
College London, United Kingdom; Maria Prins, Academic Medical Centre, Netherlands;
Aza Rakhmanova, St. Petersburg City AIDS Centre, Russian Federation; Jürgen Rockstroh,
University of Bonn, Germany; Magda Rosinska, National Institute of Public Health, National
Institute of Hygiene, Poland; Manjinder Sandhu, Genome Research Limited; Claire Thorne,
University College London, UK; Giota Touloumi, National and Kapodistrian University of
Athens, Greece; Alain Volny Anne, European AIDS Treatment Group, France.
EuroCoord External Advisory Board: David Cooper, University of New South Wales,
Australia; Nikos Dedes, Positive Voice, Greece; Kevin Fenton, Public Health England, USA;
David Pizzuti, Gilead Sciences, USA; Marco Vitoria, World Health Organisation, Switzerland.
EuroCoord Secretariat: Kate Coughlin, University College London, UK; Silvia Faggion,
Fondazione PENTA, Italy; Lorraine Fradette, University College London, UK; Richard Frost,
University College London, UK; Dorthe Raben, Københavns Universitet, Denmark; Christine
Schwimmer, University of Bordeaux II, France; Martin Scott, UCL European Research &
Innovation Office, UK.
46
Chapter 2.1
3
HIV and HCV coinfection
47
The hepatitis C epidemic
among HIV-positive MSM:
incidence estimates
from 1990 to 2007
Jannie J. van der Helm1
Maria Prins1, 2
Julia del Amo3
Heiner C. Bucher4
Geneviève Chêne5
Maria Dorrucci6
John Gill7
Osamah Hamouda8
Mette Sannes9
Kholoud Porter10
Ronald B. Geskus1,11
on behalf of the CASCADE Collaboration
AIDS 2011 May 15;25(8):1083-1091
Cluster of Infectious Diseases, Public Health Service Amsterdam, 2Department of Internal Medicine,
Center for Immunity and Infection Amsterdam (CINIMA), Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands, 3Instituto de Salud Carlos III, Madrid, Spain, 4Basel Institute for
Clinical Epidemiology and Biostatistics, University Hospital Basel, Basel, Switzerland, 5INSERM U897,
University Victor Ségalen, Bordeaux, France, 6Istituto Superiore di Sanitá, Rome, Italy, 7Department
of Medicine, University of Calgary, Calgary, Alberta, Canada, 8Robert Koch Institute, Berlin, Germany,
9
Ulleval University Hospital, Oslo, Norway, 10MRC Clinical Trials Unit, London, UK, and 11Department
of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
1
Abstract
Background: Outbreaks of acute hepatitis C virus (HCV) infection among HIV-infected MSM
have been described since 2000. However, phylogenetic analysis suggests that the spread
of HCV started around 1996. We estimated the incidence of HCV in HIV-infected MSM with
well estimated dates of HIV seroconversion from 1990 to 2007.
Methods: Data from 12 cohorts within the Concerted Action on SeroConversion to AIDS and
Death in Europe (CASCADE) Collaboration were used. HCV incidence was estimated using
standard incidence methods and methods for interval-censored data. We accounted for the
fact that routine HCV data collection in each cohort started in different calendar years.
Results: Of 4724 MSM, 3014 had an HCV test result and were included. Of these, 124 (4%)
had only positive HCV test results, 2798 (93%) had only negative results and 92 (3%) had
both. In 1990, HCV incidence ranged from 0.9 to 2.2 per 1000 person-years, depending
on the analysis strategy used. HCV incidence increased up to 1995 when it was estimated
to range between 5.5 and 8.1 per 1000 person-years. From 2002 onwards, it increased
substantially to values between 16.8 and 30.0 per 1000 person-years in 2005 and between
23.4 and 51.1 per 1000 person-years in 2007.
Conclusion: Our data support phylodynamic findings that HCV incidence had already
increased among HIV-infected MSM from the mid-1990s. However, the main expansion of
the HCV epidemic started after 2002. Incidence estimates obtained from cohort studies may
help identify changes in the spread of important infections earlier and should guide routine
testing policies to minimize further disease burden.
50
Chapter 3.1
Introduction
H
epatitis C virus (HCV) infection is a major public health problem for HIV-infected
individuals. HCV is primarily a blood-borne infection and is common in individuals
who frequently received blood and blood products before 1991, as well as in IDU.1,2 On
the basis of studies in HCV-discordant heterosexual couples, sexual transmission of HCV
was considered to be inefficient and was rarely reported, even in the presence of HIV coinfection.3,4 Since 2000, however, outbreaks of sexually acquired HCV infection among HIVinfected men who have sex with men (MSM) have been described in several high-income
countries, suggesting that the epidemiology of HCV infection is changing.5-10
Recent phylogenetic analysis, using data from five countries, revealed the presence
of international sexual HCV transmission networks among MSM. Interestingly, using a
molecular clock analysis, the study also indicated that the spread started earlier than 2000,
namely around 1996.11 The 4-year time lag in the detection of these HCV outbreaks may have
been due to the fact that routine testing for HCV infection started mainly after the first acute
cases of sexually acquired HCV infection in MSM were reported. Furthermore, because HCV
testing was not implemented before 1991, as HCV test kits were not commercially available
then, HCV incidence before that date could only be studied through retrospective testing in
cohorts for whom stored blood samples were available.
Only a few longitudinal studies with data before and after 2000 have evaluated time
trends in HCV incidence among MSM, but all are from single countries.12-14 These studies
used data from initially HCV-negative individuals with repeated tests to estimate incidence
and, consequently, these estimates were based on very few HCV seroconverters (N =
26, 4 and 8, respectively). Using data from 12 large cohorts, we estimated the incidence
and the timing of the spread of HCV in HIV-infected MSM with documented dates of HIV
seroconversion over the last two decades. We used a standard incidence estimation method
as well as a method that allowed us to also use data from HCV-infected individuals without
previous HCV-negative test results.
Methods
Study populations
Data from Concerted Action on SeroConversion to AIDS and Death in Europe (CASCADE),
a collaboration of 25 HIV seroconverter cohort studies in Europe, Australia, Canada and
sub-Saharan Africa were used for this analysis. Details of CASCADE have been described
elsewhere; in short, all cohorts included HIV-infected persons for whom a date of HIV
51
seroconversion could be estimated reliably.15 Analyses were restricted to MSM, who are
assumed to have become HIV-infected sexually, from 11 cohorts in eight European countries
and one in Canada that collected information on HCV. HCV positivity was defined as detection
of anti-HCV antibodies and/or HCV-RNA according to individual laboratory procedures. Each
cohort provided information about the start date of routine HCV data testing and collection
in their respective country/cohort. Routine HCV data collection is defined by testing all
individuals for HCV according to the prevailing guidelines so that testing is irrespective of
HCV status.
Two of the 12 cohorts provided HCV test results for all participants from the start of these
cohorts. For the other 10 cohorts, the start of routine HCV testing was later than the start
of the cohort [which differed by cohort, earliest January 1991 (Table 1)]. HCV incidence was
estimated using three methods. We used two variations of standard incidence estimation
techniques. A third method was based on a nonparametric estimation method for intervalcensored data.
Standard estimation of hepatitis C virus incidence
HCV incidence per year was calculated as the number of HCV seroconversions divided by
total person-years under observation for all MSM at risk, with HCV seroconversion date
defined as the midpoint between the last HCV-negative and first HCV-positive test dates.
Table 1. Distribution of the hepatitis C virus (HCV) test results and start date of systematic HCV testing for 3014 MSM-HIV seroconverters by
individual cohort within the CASCADE Collaboration.
Number of MSM with at least one HCV test result
(percentage of those tested)
Cohort
Number of
MSM in
cohort
At least one
HCV-positive test
result and no
negative results
(N = 124)
At least one
HCV-negative
test result
and no positive
results (N = 2798)
HCV-negative
test result
followed by a
positive result
(N = 92)
Date of
routine
HCV testing
Proportion
without HCV
test results
after routine
HCV testing (%)
Badalona IDU hospital
cohort, Spain
Italian Seroconverter Study,
Italy
Amsterdam Cohort Study
among MSM,
the Netherlands
Oslo and Ulleval hospital
cohorts, Norway
Southern Alberta clinic,
Canada
UK Register of HIV
seroconverters, UK
HCV, hepatitis C virus.
52
Chapter 3.1
We consider individuals to be at risk from the latest date of routine HCV testing, HIV
seroconversion or cohort entry. Standard application of this method is hampered by the fact
that the first information with respect to HCV status may have been obtained after the date
that an individual became at risk (e.g. at risk in 1999, first HCV test result in 2000). Individuals
with only HCV- positive test results after becoming at risk were excluded, although their
HCV infection may have occurred while they were at risk. Hence, this is likely to give an
underestimation of HCV incidence. To correct for these excluded individuals, an alternative
approach was used as well. In this approach, only data from initially HCV-negative MSM with
at least two HCV test results were included, and they were only considered at risk from the
latest date of first HCV-negative test after routine HCV data collection, HIV seroconversion or
cohort entry. However, this approach is only valid if the reason to test is independent of HCV
status. As an HCV-negative test result may make it less likely to perform HCV tests earlier
in time, this assumption may be violated, which can result in an overestimation of HCV
incidence. Incidence rate curves were modeled using Poisson regression with calendar year
as a continuous variable, allowing for smoothly varying trends via restricted cubic splines.16
Estimation of hepatitis C virus incidence based on interval-censored data
The information with respect to HCV seroconversion was, in fact, interval censored, that
is, the moment of HCV infection was not known exactly. We calculated the nonparametric
maximum likelihood estimate for the cumulative HCV incidence17 based on the intervalcensored HCV status information. For individuals who remained HCV negative during followup, the date of last HCV-negative test was used; for individuals for whom only HCV-positive
test results were available, the date of first HCV-positive test was used; and for individuals
who seroconverted to HCV during follow-up, the dates of the last negative HCV test and
the date of the first positive HCV test were used. Cumulative HCV incidence was estimated
from 1990 until May 2007. Most individuals, however, were not in follow-up and at risk
from the beginning of this period as they either seroconverted for HIV after 1990 or were
enrolled into the cohort after 1990 or because routine HCV testing had begun at a later
date. As the current version of the statistical program used has no option to correct for such
left-truncated data, we performed separate analyses for the calendar periods 1990–1994,
1995–1999 and 2000–2007, only including persons who were at risk and in follow-up in at
least part of each period.
For individuals who only had test information available before the date of becoming
at risk, data handling can be done in different ways (see below).
53
Inclusion strategy for interval-censored data method
For individuals with HCV test information available before they became at risk and without
test results after that date, we employed four strategies. Individuals testing HCV positive
before they became at risk and who remained in follow-up after that date were included
in the risk set from the date they became at risk. For individuals testing negative before
the date of routine HCV testing and without a positive test result, but with follow-up after
date of routine HCV testing, two strategies were also used of excluding them (nM, ‘negative
missing’) or of assuming they remained HCV negative until they became at risk and including
them (nI, ‘negative include’).
For those who tested HCV positive, but with no follow-up after date of routine HCV
testing, two strategies were applied of either excluding (pM, ‘positive missing’) or including them (pI, ‘positive include’). Strategy pM is based on the idea that individuals who had
tested positive before they became at risk and who had no follow-up after that date would
have been missed and their information would not have been included. Under this scenario,
individuals who only had a negative test result and without follow-up after becoming at risk
were also excluded. Strategy pI is based on the idea that individuals who tested HCV positive
and died before the date of routine HCV testing do contribute to the HCV incidence. Their
date of first HCV-positive test is set to the date of becoming at risk, even though they had no
follow-up. When strategy pI was applied, individuals who only had a negative test result and
left the study before becoming at risk were also either included or excluded.
Strategy nM overestimates HCV incidence, as individuals testing positive before the
date of routine HCV testing and with follow-up after that date are included, whereas those
testing negative before that date were not. On the contrary, strategy nI may underestimate
HCV incidence, as some of the individuals who only had HCV-negative test results before the
date of routine HCV testing may have, in fact, seroconverted between their last negative test
date and that date. If the interval between those two dates is small, strategy nI is preferable
to strategy nM. Hence, the four strategies used were strategy 1 (pM-nM), strategy 2 (pI-nM),
strategy 3 (pM-nI) and strategy 4 (pI-nI).
In the chosen strategy 3 (pM-nI), we excluded individuals who did not have followup after the date of becoming at risk. For individuals who were followed after the date of
routine testing and only had test results before this date, their result was set at the date
of becoming at risk. This strategy might give an underestimation of the HCV incidence, as
some of the individuals who only had HCV-negative test results before the date of becoming
at risk may have seroconverted between their last negative test date and the date they
became at risk. The precise details are described in the above section together with three
other strategies of data handling for these individuals. On the basis of the estimates of the
cumulative incidence, the hazard of HCV infection over calendar time was estimated using
54
Chapter 3.1
kernel smoothing methods.18
Compared with the standard incidence estimation method, the advantage of this
nonparametric method for interval-censored data is that the individuals who only had an
HCV-positive test result could be included. A disadvantage is that we are not sure whether
HCV infection occurred after they became at risk. Particularly, HCV infection may have
occurred before HIV infection. Also, standard errors and confidence intervals (CIs) cannot
be obtained.
The basic analyses were performed using SPSS version 17.0 (SPSS Inc., Chicago,
Illinois, USA). R version 2.10.119 was used for the standard methods to estimate HCV
incidence trends, and the Icens package in R20 was used for the estimates based on intervalcensored data.
Results
Of 4724 MSM from the 12 eligible cohorts in CASCADE, 3020 had an HCV test result available.
The earliest enrolment date was July 1981 and the most recent March 2007. Most MSM
were tested for HCV during prospective follow-up, that is, after HIV seroconversion and
after cohort entry, but 288 only had HCV-negative test results shortly before cohort entry
(median time between last testing and enrolment, 0.9 months; interquartile range (IQR),
0.3–4.4 months), 16 only had positive HCV test results before cohort entry (median time
between last testing and enrolment, 0.6 months; IQR, 0.3–12.5 months) and 23 only had
negative HCV test results before HIV seroconversion (median, 16.0 months; IQR, 9.5–32.1
months). Six MSM had a positive HCV test before HIV seroconversion and were, therefore,
excluded from further analyses.
Table 2. Characteristics of HIV-infected MSM at risk of the hepatitis C virus co-infection in 1990–1994, 1995–1999 and 2000–2007 when using the
nonparametric incidence estimation method, CASCADE Collaboration.
1990–1994 (N = 904)
Calendar year of HIV
seroconversion, median
(IQR)
Age in years at start of period,
median (IQR)
Age in years at HIV seroconversion,
median (IQR)
Ethnicity
Whi te
O ther
Un k n o w n
U se of any H IV anti retrov i ral therapy
MSM followed in more than one
calendar period
1995–1999 (N = 1646)
2000–2007 (N = 2565)
1990 (1987–1992)
1993 (1990–1996)
1997 (1992–2002)
5 1 8 (5 7 % )
3 1 (3 % )
3 5 5 (3 9 % )
2 9 5 (3 3 % )
820 (91%) were also
followed in 1995–1999
and 717 (79%) also followed
in 2000–2007
1 0 2 4 (6 2 % )
5 5 (3 % )
5 6 7 (3 4 % )
1 1 5 9 (7 3 % )
1480 (90%) were also
followed in 2000–2007
1 5 8 7 (6 2 % )
8 7 (3 % )
8 9 1 (3 5 % )
1 8 4 9 (7 2 % )
IQR, interquartile range.
55
Table 3. Characteristics of HIV-infected MSM with only hepatitis C virus (HCV)-positive test results, only HCV-negative test results and with
both test results, CASCADE Collaboration.
At least one HCV-positive
test result and no
negative results ( N = 124)
Calendar year of HIV seroconversion,
median (IQR)
Ethnicity
Whi te
O ther
Un k n o w n
Use of any HIV antiretroviral therapy
during follow-up
At least one
HCV-negative test result
and no positive results
(N = 2798)
HCV-negative test result
followed by a positive result
(N = 92)
1993 (1990–1999)
1996 (1992–2002)
1996 (1992–2001)
7 3 (5 9 % )
2 (1 % )
4 9 (4 0 % )
100
1 6 8 1 (6 0 % )
8 8 (3 % )
1 0 2 9 (3 7 % )
1950
5 9 (6 4 % )
2 (2 % )
3 1 (3 4 % )
77
HCV, hepatitis C virus; IQR, interquartile range.
The median age at HIV seroconversion for the 3014 MSM included was 31.6 years (IQR,
26.5–38.1). Their median year of HIV seroconversion was 1996 (IQR, 1992–2002) and 2127
individuals initiated HIV antiretroviral therapy during follow-up. Ethnicity was known for
63%, of whom 95% were white and 2% were black. Characteristics of the MSM in three
calendar periods are shown in Table 2. The median age at HIV seroconversion and the
ethnicity distribution remained stable over time, although the median age at the start of
each calendar period slightly increased. As expected, uptake of HIV antiretroviral therapy
expanded after 1995.
Hepatitis C virus test results
Of the 3014 MSM, 124 (4%) had at least one positive HCV test result and no HCV-negative
results, 2798 (93%) had at least one negative result and no HCV-positive results and 92 (3%)
had a negative test result followed by a positive result and, thus, had a documented HCV
seroconversion (characteristics are shown in Table 3). Those who only had HCV test results
before routine HCV testing began (N=770) were treated according to the four strategies
described in the ‘Inclusion strategy for interval-censored data method’ section. Of these
770 individuals, 189 were only followed before routine HCV testing began and, thus, had
HCV results only before this date. Of 2825 individuals followed after routine HCV testing
began, 581 only had HCV test results before this date (median time between last HCV test
result and routine HCV testing was 1.1 years; IQR, 0.3–2.6). The results from strategy 3 are
presented, but did not differ substantially from the other three strategies (data not shown).
Among MSM who tested HCV positive, 30 (14%) had their first positive test between 1990
and 1994, 59 (27%) between 1995 and 1999 and 127 (59%) from 2000 onwards.
Hepatitis C virus incidence
In the standard incidence estimation method, 1354 MSM were included and the number
56
Chapter 3.1
60
HCV incidence per 1000 person−years
50
40
30
20
10
0
1990
1995
Calendar year
2000
2005
Fig. 1. Hepatitis C virus incidence in HIV-infected MSM according to three estimation methods in the CASCADE Collaboration.
Thin solid line, standard hepatitis C virus (HCV) incidence estimation method (gray stripes, 95% confidence interval); thick solid
line, alternative standard HCV incidence estimation method (gray area, 95% confidence interval); dashed line, estimation
method based on interval-censored data.
of person-years of follow-up for the periods 1990–1994, 1995–2000 and 2000–2007 was
645.15, 950.04, and 1779.83, respectively; after the correction for which we required
at least two HCV test results, the number included decreased to 774 and the number of
person-years of follow-up was 517.98, 758.23 and 1211.49, respectively. The number of
MSM included in each of the three calendar periods 1990–1994, 1995–1999 and 2000–2007
when using the estimation method for interval-censored data were 904, 1646 and 2565,
respectively. Figure 1 shows the HCV incidence according to the two standard approaches
and according to the interval-censored method. The temporal trend in HCV incidence is
comparable for the three estimates over the total study period 1990–2007. In 1990, HCV
incidence was low and estimated to be 0.9 (95% CI, 0.05–15.2), 1.4 (95% CI, 0.09–20.4) and
2.2 per 1000 person-years, depending on the method used. In 1995, HCV incidence was
already slightly increased and estimated to be 5.5, 5.9 (95% CI, 2.7–13.0) and 8.1 (95% CI,
3.7–19.0) per 1000 person-years, whereas in 2000, HCV incidence was estimated to be 8.0,
10.6 (95% CI, 6.0–18.8) and 13.7 (95% CI, 8.0–23.7) per 1000 person-years. HCV incidence
increased substantially after 2002 and was estimated to be 16.8 (95% CI, 10.3–27.4), 21.2
and 30.0 (95% CI, 18.6–48.3) per 1000 person-years in 2005, and 23.4 (95% CI, 8.2–66.9),
41.9 and 51.1 (95% CI, 19.5–134.0) per 1000 person-years in 2007.
57
Discussion
Since 2000, outbreaks of HCV infection have been reported in HIV-infected MSM.5-10 We
have estimated the incidence of HCV over the last two decades in a large group of HIVinfected MSM with documented dates of HIV seroconversion in Europe and Canada. Our
data show that, regardless of the estimation method applied, HCV incidence had already
increased in the period before 2000 and has continued to do so since. These results are in
agreement with a recent phylogenetic study in which the divergence of currently circulating
HCV viral strains was used to reconstruct the history of the HCV epidemic among HIVpositive MSM. Of all transmission events in that study, 15% was estimated to have occurred
before 1996, 22% in the period 1996–2000 and 63% after 2000.11 The few longitudinal
studies on the incidence of HCV in HIV-infected MSM that evaluated time trends have
limited statistical power owing to the small numbers of observed HCV seroconversions or
dichotomized calendar period. The HCV incidence among MSM in the French PRIMO cohort
was higher after 2003, 8.3 per 1000 person-years compared with 1.2 per 1000 person-years
before (study period 1996–2005).13 In the UK, a significantly higher HCV incidence of 4.6 per
1000 person-years was found after 2000 compared with less than 1 per 1000 person-years
before (study period 1997–2002),12 which is in line with a study from the Netherlands that
found a higher HCV incidence of 8.7 per 1000 person-years after 2000 compared with 1.8
per 1000 person-years before (study period 1984–2003).14 The sharpest increase in HCV
incidence in our study was found after 2002. The HCV incidence estimates that these studies
found before 2000 are comparable with the estimates we found around 1990. In 1995, we
estimated a slightly higher incidence than reported by others, ranging between 5.5 and 8.1
per 1000 person-years. The HCV incidence in HIV-negative MSM is still low, varying between
0 and 0.4 per 1000 person-years.21 One cohort from the UK reported HCV incidence up
to 5.8 per 1000 person-years;22 however, this study had some methodological limitations,
which might explain this finding. In high-income countries, HCV incidence in IDUs is still
high, ranging between 1 and 25 per 100 person-years, but decreased in the last decade in
some countries.8,23-25
None of the three estimation approaches could completely capture the data
structure with respect to HCV infection, but differences in outcome were small. Like the
two standard incidence estimation methods in our study, the method used in the French
HIV PRIMO cohort13 and in the Amsterdam Cohort studies14 excluded MSM who tested
HCV positive at study enrolment. In the French study, 19 men were detected with anti-HCV
antibodies at inclusion and were excluded, whereas only four men seroconverted for HCV
during follow-up. As the excluded men might have become HCV-infected around the date
of their HIV infection, only HCV incidence during established HIV infection was estimated.
58
Chapter 3.1
Although the method based on interval-censored data also had problems with respect
to the definition of the risk set, we prefer the latter one because individuals only having
HCV-positive test results could also be included and, therefore, it makes better use of the
available data. A problem is that HCV infection may have occurred before HIV infection, but
as HCV prevalence in HIV-negative MSM remains low,21 this is not very likely.
The HCV epidemic is changing and sexual transmission of HCV seems to have
become more important, as the majority of the recently HCV-infected MSM denied injecting
drug use. However, they more often reported specific sexual techniques, such as fisting and
group sex, often in the context of recreational drug use.21 In our study, all participants are
assumed to have become HIV-infected sexually, although we cannot exclude that some HCV
infections were acquired through routes other than sex, as we do not have data on HCV
transmission routes in these MSM. The availability of HAART since 1996 is associated with
a prolonged survival and increased sexual risk behavior in MSM.26,27 This suggests that,
with a stable or even increasing HIV incidence, the pool of HIV-infected MSM at risk of
HCV infection becomes larger.21 Within this context, both concurrent sexually transmitted
infections and serosorting (i.e. choosing to have unprotected anal intercourse with sexual
partners based on concordant HIV serostatus),28,29 which is practised as a risk reduction
strategy, might have contributed to the spread of HCV.30
Although follow-up started already in 1981, we were not able to estimate HCV
incidence before 1990 reliably, as only two of the 12 cohorts had retrospectively and
routinely tested their participants before that date. Including nonroutinely collected data
can introduce serious bias.31 Missing data after the date at which routine HCV testing was
introduced varied between 4 and 66% across cohorts in our study. This high rate is in line with
findings from a recent UK study,32 concluding that it is of concern that even nowadays not
all HIV-infected individuals under care are tested for HCV, despite recommendations from
guidelines. This is even more important for MSM given the recent outbreak. We assumed
that after the routine HCV testing date, missing data did not depend on actual HCV status,
but this assumption might not hold completely. If, for example, only those with elevated
alanine transaminase values were tested and, therefore, those with a higher likelihood of
being HCV negative were not tested, this will result in an overestimation of HCV incidence.
As it is unlikely that this testing approach changed over time, our finding that HCV incidence
already increased in the period 1990–1999 remains valid.
Despite the fact that HCV therapy became generally available in 2000, earlier
identification of the increasing incidence of HCV among HIV-infected MSM could have
limited the further spread through raising awareness of the risk of sexually acquired HCV
among MSM. Incidence estimates might help to identify changes in the spread of important
co-infections earlier, and might advance the response to these changes in the epidemic.
For this, observational cohort studies with sufficient power and timely supply of data are
59
necessary. As HIV-infected individuals are increasingly more likely to die from non-HIVrelated causes33,34 and HIV accelerates HCV disease progression,35 routine screening for
acute HCV as recommended by the European AIDS treatment network (NEAT) consensus
conference36 is needed to diagnose HCV infection in the early phase because current data
suggest that early treatment has the greatest chance of success.37 In addition, raising
awareness is necessary to minimize further spread of HCV among HIV-infected MSM. As the
HCV outbreak is not fully understood, further research on risk factors for sexually acquired
HCV in MSM and the role of HIV infection itself is urgently needed for targeted prevention.
Although HCV prevalence in the HIV-negative MSM population is still low,21 vigilance and
surveillance is required to detect and minimize possible spillover.
Acknowledgements
The research leading to these results has received funding from the European Union
Seventh Framework Programme (FP7/2007–2011) under EuroCoord grant agreement
number 260694. G.C. had received speaker’s honoraria from Boehringer-Ingelheim, fees
for consultancy from Roche and a research grant from Gilead. K.P. had received speaker’s
honoraria from Tibotec.
The authors had full responsibility in the design of the study, collection of the data,
the decision to submit the manuscript for publication and the writing of the manuscript.
CASCADE Collaboration
Steering Committee: J.D.A. (Chair), Laurence Meyer (Vice Chair), H.C.B., G.C., O.H., Deenan
Pillay, M.P., Magda Rosinska, Caroline Sabin and Giota Touloumi.
Co-ordinating Centre: K.P. (Project Leader), Sara Lodi, Kate Coughlin, Sarah Walker
and Abdel Babiker.
Clinical Advisory Board: H.C.B., Andrea De Luca, Martin Fisher and Roberto Muga.
Collaborators: Austria – Austrian HIV Cohort Study (Robert Zangerle); Australia –
Sydney AIDS Prospective Study and Sydney Primary HIV Infection cohort (Tony Kelleher,
Tim Ramacciotti, Linda Gelgor, David Cooper and Don Smith); Canada – South Alberta
Clinic (J.G.); Denmark – Copenhagen HIV Seroconverter Cohort (Louise Bruun Jørgensen,
Claus Nielsen and Court Pedersen); Estonia – Tartu Ülikool (Irja Lutsar); France – Aquitaine
cohort (G.C., Francois Dabis, Rodolphe Thiebaut and Bernard Masquelier), French Hospital
Database (Dominique Costagliola and Marguerite Gui- guet), Lyon Primary Infection cohort
(Philippe Vanhems), French PRIMO cohort (Marie-Laure Chaix and Jade Ghosn), SEROCO
cohort (Laurence Meyer and Faroudy Boufassa); Germany – German cohort (O.H., Claudia
Kücherer and Barbara Bartmeyer); Greece – Greek Haemophilia cohort (Giota Touloumi,
60
Chapter 3.1
Nikos Pantazis, Angelos Hatzakis, Dimitrios Paraskevis and Anastasia Karafoulidou); Italy
– Italian Seroconversion Study (Giovanni Rezza, M.D. and Claudia Balotta), ICONA cohort
(Antonella d’Arminio Monforte, Alessandro Cozzi-Lepri and Andrea De Luca); the Netherlands
– Amsterdam Cohort Studies among homosexual men and drug users (M.P., R.B.G., J.J.v.d.H.
and Hanneke Schuitemaker); Norway – Oslo and Ulleval Hospital cohorts (M.S., Oddbjorn
Brubakk and Anne- Marte B. Kran); Poland – National Institute of Hygiene (Magdalena
Rosinska); Spain – Badalona IDU hospital cohort (Roberto Muga and Jordi Tor), Barcelona
IDU Cohort (Patricia G. de Olalla and Joan Cayla), Madrid cohort (J.D.A. and Jorge del
Romero), Valencia IDU cohort (Santiago Pe ́rez-Hoyos); Switzerland – Swiss HIV Cohort Study
(H.C.B., Martin Rickenbach and Patrick Francioli); Ukraine – Perinatal Prevention of AIDS
Initiative (Ruslan Malyuta); UK – Edinburgh Hospital cohort (Ray Brettle), Health Protection
Agency (Gary Murphy), Royal Free Haemophilia Cohort (Caroline Sabin), UK Register of HIV
Seroconverters (K.P., Anne Johnson, Andrew Phillips, Abdel Babiker and Valerie Delpech),
University College London (Deenan Pillay), University of Oxford (Harold Jaffe).
African cohorts: Genital Shedding Study (USA – Charles Morrison, Family Health
International and Robert Salata, Case Western Reserve University; Uganda – Roy Mugerwa,
Makerere University; Zimbabwe – Tsungai Chipato, University of Zimbabwe); Early Infection
Cohorts (Kenya, Uganda, Rwanda, Zambia, South Africa – Pauli Amornkul, International AIDS
Vaccine Initiative).
Presented, in part, previously at the 46th Annual Meeting of the European Association
for the Study of the Liver, Berlin, Germany on 30 March to 3 April 2011 (poster 1175); at
the 17th Conference on Retroviruses and Opportunistic Infections, San Francisco, California,
USA on 16–19 February 2010 (abstract 643); and at the 18th International Society for STD
Research, London, UK on 28 June to 1 July 2009 (abstract P3.130).
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63
64
Effect of HCV infection
on cause-specific mortality
after HIV seroconversion,
before and after 1997
Jannie van der Helm1
Ronald Geskus1,2
Caroline Sabin3
Laurence Meyer4,5
Julia del Amo6
Geneviève Chêne7,8
Maria Dorrucci9
Roberto Muga10
Kholoud Porter11
Maria Prins1,12
on behalf of CASCADE Collaboration in EuroCoord
Gastroenterology, 2013 Apr;144(4):751-760
1
Public Health Service Amsterdam, Amsterdam, the Netherlands; 2Department of Clinical
Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam,
Amsterdam, the Netherlands, 3Research Department of Infection and Population Health, University
College London, London, United Kingdom; 4Service d’Epidémiologie et de Santé Publique, Hôpital
de Bicêtre, Assistance Publique-Hôpitaux de Paris (AP-HP); INSERM U1018; 5University Paris Sud,
Paris, France; 6Instituto de Salud Carlos III, Madrid, Spain; 7University Bordeaux Ségalen; INSERM
U897, Bordeaux, France; 8Centre d’investigation Clinique-Epidemiologie Clinique (CIC-EC7), CHU,
Bordeaux, France; 9Istituto Superiore di Sanità, Rome, Italy; 10Department of Internal Medicine,
Hospital Universitari Germans Trias i Pujol, Badalona, Spain; 11MRC Clinical Trials Unit, London, United
Kingdom; 12Academic Medical Center, University of Amsterdam, Center for Infection and Immunity
Amsterdam (CINIMA), Amsterdam, the Netherlands
Abstract
Background & aims: Individuals with human immunodeficiency virus (HIV) infection
frequently also are infected with hepatitis C virus (HCV) (co-infection), but little is known
about its effects on the progression of HIV-associated disease. We aimed to determine the
effects of co-infection on mortality from HIV and/or acquired immune deficiency syndrome
(AIDS), and hepatitis or liver disease, adjusting for the duration of HIV infection.
Methods: We analyzed data from the 16 cohorts of the Concerted Action on Seroconversion
to AIDS and Death in Europe (CASCADE) collaboration, which included information on HCV
infection and cause of death. A competing-risks proportional subdistribution hazards model
was used to evaluate the effect of HCV infection on the following causes of death: HIV- and/
or AIDS-related, hepatitis- or liver-related, natural, and non-natural.
Results: Of 9164 individuals with HIV infection and a known date of seroconversion, 2015
(22.0%) also were infected with HCV. Of 718 deaths, 395 (55.0%) were caused by HIV
infection and/or AIDS, and 39 (5.4%) were caused by hepatitis or liver-related disease.
Among individuals infected with only HIV or with co-infection, the mortality from HIV
infection and/or AIDS-related causes and hepatitis or liver disease decreased significantly
after 1997, when combination antiretroviral therapy became widely available. However,
after 1997, HIV and/or AIDS-related mortality was higher among co-infected individuals
than those with only HIV infection in each risk group: injection drug use (adjusted hazard
ratio [aHR], 2.43; 95% confidence interval [CI], 1.14–5.20), sex between men and women
or hemophilia (aHR, 3.43; 95% CI, 1.70–6.93), and sex between men (aHR, 3.11; 95% CI,
1.49–6.48). Compared with individuals infected with only HIV, co-infected individuals had a
higher risk of death from hepatitis or liver disease.
Conclusions: Based on analysis of data from the CASCADE collaboration, since 1997, when
combination antiretroviral therapy became widely available, individuals co-infected with
HIV and HCV have had a higher risk of death from HIV and/or AIDS, and from hepatitis or
liver disease, than patients infected with only HIV. It is necessary to evaluate the effects of
HCV therapy on HIV progression.
66
Chapter 3.2
Introduction
B
ecause of shared transmission routes, human immunodeficiency virus (HIV)-infected
persons are at risk of other blood-borne and sexually transmitted infections. Hepatitis
C virus (HCV) infection, which predominantly is transmitted parenterally, is common in this
group. Because HIV-infected persons live longer in the era of combination antiretroviral
therapy (cART), they are increasingly more likely to die from non-HIV-related causes,1 with
the sequelae of hepatitis infections being a leading cause of non-HIV deaths.2 HIV infection
adversely affects both the natural history and therapy outcome of HCV3 and even in the
cART era HIV continues to accelerate HCV disease progression.4 However, there is conflicting
evidence as to whether HCV co-infection accelerates HIV disease progression. A recent
meta-analysis including 10 studies from the pre-cART era and 27 studies from the cART era5
reported that HIV–HCV co-infected individuals were not at higher risk of all-cause mortality compared with those with HIV monoinfection in the pre-cART era, but were at a higher
risk of all-cause mortality in the cART-era. However, no effect of co-infection on the risk of
acquired immune deficiency syndrome (AIDS)-defining events in the cART era was observed.
Liver-related mortality was not studied in the meta-analysis but another study reported
an increased risk of liver-related mortality in HIV–HCV co-infected individuals compared
with HIV-monoinfected individuals in the cART era.6 The effect of HCV on specific causes of
mortality, other than HIV and/or AIDS and liver-related causes, in HIV co-infected individuals
is very limited.7
Only a few studies, all from individual countries, have explored changes in the impact
of HCV co-infection on HIV disease progression in the cART era compared with the precART era8-13 and reported conflicting results. These studies, however, were limited by their
design because they did not consider competing causes of death and accurate estimates
of the duration of HCV and HIV infection were not available, except for one study that
estimated HIV infection duration.8 Moreover, individuals with missing HCV status often
were excluded from analysis, which can introduce serious bias.14 Better estimates of the
effect of HCV co-infection on cause-specific mortality, including HIV and/or AIDS-related
mortality, are needed to improve our understanding of prognosis and to guide the care of
co-infected patients. The Concerted Action on SeroConversion to AIDS and Death in Europe
(CASCADE) collaboration, which includes a large group of HIV seroconverters, provides a
unique opportunity to study the impact of HCV co-infection on both HIV and/or AIDS and
hepatitis or liver-related mortality, adjusting for the duration of HIV infection. We studied
the impact of HCV co-infection in HIV-infected persons on deaths from different causes and
evaluated whether any effect changed after the introduction of cART.
67
Materials and methods
Study population
CASCADE is a collaboration within EuroCoord (www.EuroCoord.net), currently of 28
HIV seroconverter cohort studies in Europe, Australia, Canada, and sub-Saharan Africa.
Details of CASCADE are described elsewhere.15 In brief, all cohorts included HIV-1–infected
individuals for whom a date of HIV seroconversion could be estimated reliably. The end date
used for this analysis was June 2007, when 21 seroconverter cohorts were included in the
collaboration: 1 Canadian, 2 Australian, and 19 European cohorts.
Analyses were restricted to 16 cohorts from Europe and Canada for which the cause
of death was available for at least 50% of reported deaths, and HCV status was known for
at least 50% of study participants. Survival of individuals from the included and excluded
cohorts was compared and did not differ significantly. Individuals younger than 15 years
of age at HIV seroconversion and those with a time period of more than 3 years between
the last HIV-seronegative and first HIV-seropositive test were excluded. For each cohort
we collected information on the start date of routine HCV data collection/testing. HCV
positivity was defined as any positive HCV test (anti-HCV antibody, HCV RNA, or test for
HCV infection not recorded) during follow-up. HCV-positive individuals were assumed to be
HCV positive from HIV seroconversion onward. Classification of cause of death (COD) was
based on the 1993 clinical definition of AIDS from the Centers for Disease Control and the
International Classification of Diseases 10th revision. Furthermore, the Coding of Death in
HIV classification system was used to standardize causes of death reported by cohorts.16
COD were grouped into 4 categories: HIV and/or AIDS-related, hepatitis- or liver-related,
other natural causes, and non-natural death. When more than one cause of death was
given, the most likely underlying cause of death was scored independently by members of
the CASCADE Clinical Advisory Board.
Statistical analysis
Because effective cART became widely available in 1997, we split the follow-up period into
2 periods: pre-1997 and 1997 onward, reflecting the pre-cART and cART eras, respectively.
Follow-up was calculated from the estimated date of seroconversion until the earliest of
the following: death, loss to follow-up, or the cohort censor date, with the latest being June
2007. Individuals who contributed to both calendar periods were left-truncated for the cART
era at December 31, 1996. Those who were enrolled retrospectively after seroconversion
into the cohort were included in the risk set from their time of cohort enrolment (ie, left
truncation was applied to control for survivorship bias). Moreover, we applied additional
left truncation at the first date of routine data collection on HCV for the cohorts that started
68
Chapter 3.2
collecting this information later than the date of their cohort start because information on
HCV status before routine data collection might be biased (eg, retrospective testing may
be more likely for individuals suspected of having HCV infection).17 Because a substantial
number of individuals remained with missing HCV status after the start of routine HCV data
collection, we used multivariate imputation of HCV status by chained equations and created
5 imputed datasets.18,19 We assumed that after the start of routine data collection the decision to test for HCV was not related to HCV status. Missing COD also was imputed. The
same variables used in the survival analysis were used in the imputation models (ie, risk
group, sex, age at HIV seroconversion, co-infection status, cause of death, calendar period,
left truncation time, and follow-up time). For all analyses, the results from the 5 imputed
datasets were combined using Rubin’s 20 method. We validated the imputation procedure
and checked whether the imputed values were reasonable under the assumptions that
values were missing at random.21 Furthermore, the imputation model was checked by
including the country of the cohort site.
To describe whether differences in outcomes were related to use of cART, we
compared uptake of antiretroviral therapy, achieving an HIV RNA response of 500 copies/
mL or less after therapy initiation and virologic failure (defined as the first of 2 consecutive
viral loads >500 copies/mL) after initial suppression between monoinfected and co-infected
individuals using a Cox proportional hazards model, adjusting for sex, risk group, and age
at HIV seroconversion. Also, an interaction between age at HIV seroconversion and coinfection status was included. The adjusted hazard ratio (aHR) and 95% confidence interval
(CI) are presented.
We estimated all-cause mortality, stratified by cART period and co-infection status,
through Kaplan-Meier survival estimates. In a Cox proportional hazards model, the effects
of co-infection and calendar period, and their interaction, were adjusted for sex, risk group,
and age at HIV seroconversion. Furthermore, we included an interaction between risk
group and calendar period and an interaction between age at HIV seroconversion and coinfection status. This latter interaction was included to correct for time since HCV infection.
We assumed mortality was increasingly different between monoinfected and co-infected
individuals with increasing HCV infection duration. Therefore, age at HIV seroconversion
was used as a proxy for the duration of HCV infection. We did not include an interaction
between risk group and co-infection status as a result of colinearity (eg, all hemophilic men
were co-infected).
We estimated cause-specific cumulative incidence curves stratified by co-infection
status for the pre-cART and cART eras separately. In a multivariable model, the impact of
co-infection on each cause of death was analyzed using a proportional sub-distribution
hazards model. In contrast to a proportional cause-specific hazards model, a proportional
subdistribution hazards model quantifies the effect of each covariable on the cumulative
69
scale, taking into account the effects of other competing causes. Because some CODs
were rare, some effects of covariables were assumed to be equal for different CODs as
described in detail in the Supplementary Materials and Methods section.22 The effect of
HCV status was allowed to depend on age (ie, we included an interaction between age and
HCV status). We present the results for those aged 30 years because this was the median
age in the population. In a sensitivity analysis individuals who seroconverted for HIV in the
pre-cART era and contributed to the cART era were excluded because there may have been
differences in the proportions surviving into the cART era between monoinfected and coinfected individuals. For the competing risks analyses, we used the approach described by
Geskus,23 in which individuals who experienced a competing event remained in the risk
set with a weight that was determined by the censoring pattern. Analyses were performed
using R version 2.10.1 (Vienna, Austria).24 The package mstate25 was used to calculate the
weights.
All authors approved the final version of the manuscript.
Results
Description of the study population
Of the 9164 HIV seroconverters included in the analyses, 1279 contributed to both calendar
periods. HCV status was available for 7892 (86.1%) and imputed for 1272 (13.9%). After
imputation, 2015 (22%) were HCV co-infected. Total person-years of follow-up was 7158 in
the pre-cART era and 22,230 in the cART era (Table 1). Men having sex with men (MSM) was
the main risk for HIV transmission (57%), followed by sex between men and women (MSW)
(25%), injection drug use (IDU) (16%), and hemophilia (2%). Compared with the pre-cART
era, the proportion of IDU and hemophilic patients in follow-up was lower whereas that of
MSW and MSM patients was higher in the cART era. HCV infection was much more frequent
among those infected through IDU (90%) and hemophilia (99%) compared with MSM (7%)
and MSW (9%). Consequently, 936 (53%) were HCV co-infected in the pre-cART era and 1767
(20%) were HCV co-infected in the cART era. In both periods, co-infected individuals were
younger at HIV seroconversion than monoinfected individuals. In the cART era, co-infected
individuals were infected with HIV in an earlier calendar year than monoinfected individuals.
After adjustment for sex, risk group, age at HIV seroconversion, and the interaction between
age at HIV seroconversion and HCV status, neither uptake of therapy (aHR, 1.10; 95% CI,
0.93–1.31 for those aged 25–29 years) nor achieving an HIV-RNA response of 500 copies/mL
or less after therapy initiation differed significantly between monoinfected and co-infected
individuals from all age groups in the cART era (aHR, 0.97; 95% CI, 0.82–1.15 for those <25
70
Chapter 3.2
Table 1. General Characteristics of 9164 HIV-Infected Individuals With a Known Interval of HIV Seroconversion, Stratified by
HCV Infection Status and Period of Follow-Up in the CASCADE Collaboration
Pre-cART (n
Characteristic
Person-years of follow-up
Median age at HIV seroconversion,
y (IQR)
Mode of HIV infection (%)
Sex between men
Injection drug use
Hemophilia
Sex between men and women
Sex (%)
Men
Calendar year of HIV
seroconversion, median (IQR)
Total deaths
Causes of death (%)
HIV- and/or AIDS-related
Hepatitis or liver-related
Non-natural
Natural
HCV
1769)
c AR T (n
8674)
(N
(N
(n
4211
2947
6923
15307
(n
6907)
51 (5)
726 (78)
141 (15)
19 (2)
605 (73)
70 (8)
0 (0)
157 (19)
329 (19)
1,164 (66)
68 (4)
206 (12)
4,727 (68)
132 (2)
2 (0.03)
2046 (30)
696 (74)
719 (86)
1,254 (71)
5574 (81)
191
176
223
128
123 (64)
15 (8)
40 (21)
13 (7)
140 (80)
1 (1)
6 (3)
29 (16)
91 (41)
20 (9)
63 (28)
49 (22)
41 (32)
3 (2)
21 (16)
63 (49)
NOTE. Follow-up periods were as follows: pre-cART, before 1997; and cART, 1997 and later. There were 1279 individuals who contributed to both
periods. Because results in this table are based on rounded mean values ofthe 5 imputed datasets, results may not always count up exactly
to the total value.
IQR, interquartile range.
y; 0.92; 95% CI, 0.80–1.06 for those aged 25–29 y; 0.97; 95% CI, 0.80–1.17 for those aged
30–34 y; and 1.00; 95% CI, 0.82–1.21 for those aged ≥35 y). Virologic failure after initial
suppression was comparable for monoinfected and co-infected individuals in all age groups
of 25 years and older (aHR, 1.05; 95% CI, 0.85–1.30 for those aged 25–29 y; 1.02; 95%
CI, 0.80–1.31 for those aged 30–34 y; and 0.98; <95% CI, 0.75–1.26 for those aged ≥35
y). However, co-infected individuals aged younger than 25 years had a slightly higher risk
of virologic failure (aHR, 1.23; 95% CI, 1.02–1.48). In total, 718 individuals died. A specific
cause of death was available for 576 (80%) individuals and 142 (20%) causes of death were
imputed. After imputation, 395 deaths were caused by HIV and/or AIDS and 39 were caused
by hepatitis or liver-related causes.
All-cause mortality
All-cause mortality unadjusted for possible confounders is shown in Figure 1. In the pre-cART
era, all-cause mortality was higher, although not significantly, among monoinfected than coinfected individuals, with 78% (95% CI, 59%–88%) of the monoinfected group estimated
to die within 15 years after HIV seroconversion compared with 58% (95% CI, 50%–64%) of
the co-infected group. In contrast, in the cART era, co-infected individuals had significantly
higher mortality than monoinfected individuals, 35% (95% CI, 31%–39%) vs 11% (95% CI,
9%–14%), respectively, by 15 years after HIV seroconversion. After adjustment for sex, risk
group, and age, all-cause mortality did not significantly differ between co-infected and
monoinfected individuals in the pre-cART era (aHR, 0.75; 95% CI, 0.41–1.37), but remained
71
CART (>=1997)
PRE−CART (<1997)
1.0
Cumulative incidence
0.8
0.6
0.4
0.2
0.0
0
5
10
15
0
5
10
15
Time from HIV seroconversion (years)
Figure 1. Cumulative incidence of all-cause mortality for monoinfected and co-infected individuals in the pre-cART and cART eras
in the CASCADE collaboration. Dashed line, HIV-monoinfected individuals; solid line, HIV/HCV co-infected individuals; gray area
around line, 95% confidence interval.
higher in co-infected individuals in the cART era (aHR, 1.84; 95% CI, 1.16–2.93). In each
calendar period there was a significant difference in all-cause mortality by risk group (P<
.001). Compared with MSM, all-cause mortality in the pre-cART era was 62% higher for
IDU (aHR, 1.62; 95% CI, 0.97–2.71), almost equal in those with hemophilia (aHR, 0.98; 95%
CI, 0.55–1.74) and 54% lower (aHR, 0.46; 95% CI, 0.24–1.88) for MSW. In the cART era, allcause mortality was higher among all risk groups compared with MSM (aHR, 3.52; 95% CI,
2.35–5.26 for IDU; 4.77; 95% CI, 2.65–8.58 for those with hemophilia; and 1.51; 95% CI,
1.03–2.20 for MSW). Overall, there was a significant age effect, but the interaction between
age and HCV status was not significant (P= .55).
Cause-specific cumulative incidences
Cumulative incidences for each specific COD in the pre-cART era are shown in Figure 2 (upper
panel). In this era, deaths from HIV and/or AIDS had the highest cumulative incidence in both
co-infected and monoinfected individuals. The cumulative probability of dying from HIV
and/or AIDS within 15 years from HIV seroconversion was lower in co-infected individuals
than in monoinfected individuals. In contrast, the probability of dying of hepatitis or liverrelated causes within 15 years from HIV seroconversion was 4.1% (95% CI, 1.7–6.6) in co72
Chapter 3.2
AIDS
HEPATITIS
NATURAL
NON−NATURAL
0.6
0.5
PRE−CART (<1997)
0.4
0.3
Cause specific cumulative incidence
0.2
0.1
0.0
0.6
0.5
CART (>=1997)
0.4
0.3
0.2
0.1
0.0
0
5
10
15
0
5
10
15
0
5
10
15
0
5
10
15
Time since HIV seroconversion (years)
Figure 2. Cause-specific cumulative incidence of death from (A) HIV and/or AIDS, (B) hepatitis or liver-related causes, (C) natural
causes, and (D) non-natural causes for monoinfected and co-infected individuals in the pre-cART and cART eras in the CASCADE
collaboration. Dashed line, HIV-monoinfected individuals; solid line, HIV/HCV co-infected individuals; gray area around line, 95%
confidence interval.
infected individuals but only 0.4% (95% CI, 0–1.2) in monoinfected individuals.
In the cART era (Figure 2, lower panel), HIV and/or AIDS-related mortality decreased
drastically, compared with the pre-cART era for both monoinfected and co-infected
individuals, although it was less pronounced for the latter with a cumulative incidence at
15 years of 3.7% (95% CI, 2.2–5.1) and 14.5% (95% CI, 11.1–17.7) for monoinfected and coinfected individuals, respectively. HIV and/or AIDS and non-natural causes were the most
likely COD in co-infected individuals whereas HIV and/or AIDS and natural causes were the
most likely COD in monoinfected individuals. The probability of dying from hepatitis or liverrelated causes in monoinfected individuals in the cART era remained extremely low and was
comparable with that in the pre-cART era (0.4% within 15 years; 95% CI, 0–0.9). Deaths from
hepatitis or liver-related causes among co-infected individuals remained more frequent in
the cART era (2.4% within 15 years; 95% CI, 0.8–4.0) but still decreased and had a somewhat
later onset after HIV seroconversion.
Comparison of the risk of cause-specific mortality by HCV status
Subdistribution hazards ratios for the relationship between death from each specific cause
and HCV status are shown in Table 2. In the pre-cART era progression to HIV and/or AIDS73
Table 2. Subdistribution Hazards and 95% CIs for the Relationship Between Death From Each Specific Cause and HCV
Status in the Pre-cART and cART Eras: CASCADE Collaboration
COD by HCV status and risk group combinations
HIV and/or AIDS
HCV-negative MSM, MSW, or those with hemophilia
HCV-positive MSM
HCV-positive MSW or those with hemophilia
HCV-positive IDU
HCV-negative IDU
Hepatitis or liver a
or IDU
H C V-pos itive ID U
HCV-positive MSM or MSW or those with
hemophilia
Natural
HCV-negative MSM, MSW or those with hemophilia
HCV-positive MSM
HCV-positive IDU
HCV-negative IDU
Non-natural
HCV-positive MSM
HCV-positive IDU
HCV-negative IDU
1 (ref)
0.70 (0.42–1.17)
0.78 (0.56–1.07)
1 (re f)
1 (ref)
3.11 (1.49–6.48)
3.43 (1.70–6.93)
1 (re f)
2 1 . 8 (6 . 2 6 –7 5 . 9 )
27.9 (8.39–92.6)
7 . 8 6 (2 . 5 6 –2 4 . 1 )
10.0 (3.14–32.2)
1 (ref)
0.33 (0.13–0.84)
0.36 (0.16–0.82)
1 (ref)
1.49 (0.79–2.79)
1.64 (0.87–3.08)
1 (ref)
1.78 (0.50–6.35)
1.96 (0.58–6.66)
1 (ref)
2.64 (0.95–7.34)
2.91 (1.02–8.29)
NOTE. The aHR was adjusted by sex and age.
a Because of a low number of events, no further distinction between risk groups could be made.
related death was comparable for co-infected and monoinfected individuals from the
same risk group, except for IDU, whose risk was reduced if they were co-infected (aHR,
0.55; 95% CI, 0.33–0.90). In the cART era this association was reversed, with co-infected
individuals from all 4 risk groups having a higher risk of progression to HIV and/or AIDSrelated death than monoinfected individuals: IDU (aHR, 2.43; 95% CI, 1.14–5.20), MSW or
those with hemophilia (aHR, 3.43; 95% CI, 1.70–6.93), and MSM (aHR, 3.11; 95% CI, 1.49–
6.48), compared with monoinfected individuals of the same risk group. In the pre-cART
era, co-infected individuals had a much higher risk of hepatitis or liver-related mortality
than monoinfected individuals (aHR, 21.8; 95% CI, 6.26–75.9 for IDU and aHR, 27.9; 95% CI,
8.39–92.6 for all other risk groups combined). The same association was seen in the cART
era, although hazard ratios were slightly less increased (aHR, 7.86; 95% CI, 2.56–24.1 for IDU
and aHR; 10.0; 95% CI, 95% CI, 3.14–32.2 for all other groups). In the pre-cART era the risk
of dying from natural causes was lower for co-infected individuals from all risk groups (aHR,
0.36; 95% CI, 0.16–0.82 for MSW or those with hemophilia; aHR, 0.33; 95% CI, 0.13–0.84 for
MSM and aHR; 0.26; 95% CI, 0.10–0.63 for IDU), whereas in the cART era hazard rates for
this COD were comparable for co-infected and monoinfected individuals from the same risk
group. The risk of dying from non-natural causes did not differ significantly for co-infected
and monoinfected individuals from all risk groups in both the pre-cART and post-cART eras,
with the exception of a higher risk of mortality in the cART era among co-infected MSW individuals or those with hemophilia (aHR, 2.91; 95% CI, 1.02–8.29).
74
Chapter 3.2
Table 3. Subdistribution Hazards and 95% CIs for the Relationship Between Death From Each Specific Cause and Calendar
Period for HCV-Positive and HCV-Negative HIV-Infected Individuals: CASCADE Collaboration
HIV and/or AIDS
Pre-cART (within risk group)
cART MSM or MSW or those with
cART IDU
Hepatitis or liver a
Natural
cART IDU
Non-natural
Pre-cART MSM (within risk group)
cART IDU
HCV-positive aHR (95% CI)
HCV-negative aHR (95% CI)
1 (ref)
0.19 (0.10–0.35)
0.34 (0.22–0.52)
1 (ref)
0.04 (0.03–0.07)
0.07 (0.03–0.19)
1
0.36 (0.16–0.81)
NA
NA
hemophilia
1 (ref)
1.53 (0.62–3.74)
0.90 (0.41–1.94)
1 (ref)
0.34 (0.20–0.58)
0.20 (0.07–0.57)
hemophilia
1 (ref)
1.76 (0.72–4.30)
1.03 (0.64–1.66)
1 (ref)
1.18 (0.39–3.58)
0.70 (0.17–2.84)
hemophilia
hemophilia or IDU
NOTE. The aHR was adjusted by sex and age.
NA, not applicable.
a Because ofthe low number of events, no further distinction between risk groups could be made.
Changes in the risk of cause-specific death in the cART era within groups with the same
HCV status
Subdistribution hazards for the relationship between death from each specific cause and
calendar period are shown in Table 3. Among co-infected MSM or MSW or men with
hemophilia, the risk of death from both HIV and/or AIDS (aHR, 0.19; 95% CI, 0.10–0.35) and
hepatitis or liver-related causes (aHR, 0.36; 95% CI, 0.16–0.81) was significantly lower in
the cART compared with the pre-cART era within the same risk group. A similar pattern was
seen for co-infected IDUs (aHR, 0.34; 95% CI, 0.22–0.52 and aHR; 0.36; 95% CI, 0.16–0.81,
respectively). For the co-infected groups, the risk of natural and non-natural causes of death
did not differ significantly between the pre-cART and cART eras. Among monoinfected MSM,
MSW, or men with hemophilia the risk of death from both HIV and/or AIDS (aHR, 0.043; 95%
CI, 0.03–0.07) and natural causes (aHR, 0.34; 95% CI, 0.20–0.58) was lower in the cART
era compared with the pre-cART era, with similar patterns among the monoinfected IDUs
(aHR, 0.077; 95% CI, 0.031–0.19; and aHR, 0.20; 95% CI, 0.07–0.57, respectively). Because of
the small numbers of hepatitis or liver-related deaths among monoinfected individuals the
effect of risk group could not be estimated.
In a sensitivity analysis in which country of cohort site was included in the imputation
model, results did not change. In addition, in a sensitivity analysis that excluded individuals
from the cART era who seroconverted in the pre-cART era (n=4414), the direction of the aHR
for HIV- and/or AIDS-related causes remained unchanged, although the reduced size of the
sample meant that these sensitivity analyses were no longer sufficiently powered to detect
significant effects (data not shown).
75
Discussion
Our study had a number of clinically relevant findings. First, we found that although all-cause
mortality did not differ significantly between co-infected and monoinfected individuals in
the pre-cART era, it became significantly higher for co-infected individuals in the cART era.
This is in concordance with a recent meta-analysis that reported an increased risk of allcause mortality for co-infected compared with monoinfected individuals in the cART era.5
Second, among co-infected individuals, we found that their risk of hepatitis or liver- related
mortality decreased in the cART era compared with the pre-cART era. In addition, despite
the reduction in hepatitis or liver-related mortality in the cART era, co-infected individuals
still experienced a higher rate of death from these causes compared with monoinfected
individuals. Third, and importantly, we found that, in the cART era, HCV co-infection
increased the risk of HIV- and/or AIDS-related mortality. In fact, we found that co-infected
individuals from all risk groups were at increased risk of HIV- and/or AIDS-related mortality,
compared with monoinfected individuals from the same risk group. This is in contrast to the
meta-analysis whose investigators concluded that increased overall mortality was unrelated
to HIV disease progression in the cART era because the risk of AIDS-defining events was
not increased.5 Interestingly, although HIV- and/or AIDS-related mortality was not assessed
in that review, the pooled risk ratio of 1.49 reported for a combination of AIDS and death
as outcome was statistically significant and in line with our finding. Conflicting results
might be owing to differences in follow-up duration, inability to correct for duration of HIV
infection, different statistical methods, and differences in patient population (eg, ethnic
background).26,27
Thus, although the effect of HCV on HIV disease progression is still under debate, our
large study provides strong evidence of an increased risk of HIV- and/or AIDS-related mortality
among co-infected individuals in the cART era. The underlying mechanisms by which HCV
affects HIV disease progression are not known, however, although it has been suggested that
high levels of T-cell activation in co-infected individuals may lead to immune dysfunction.28
Cirrhosis and advanced liver disease might act as possible intermediate variables. These
conditions affect immune function, thereby promoting AIDS-defining conditions, which
might result in classification as an AIDS-related death. In addition, although therapy uptake
in the cART era is similar for co-infected and monoinfected individuals, it might be that
cART effectiveness was less in co-infected individuals by increasing the risk of drug-related
hepatotoxicity, which might explain the poorer outcome.29 Another explanation might be
lower adherence. In line with previous studies, we found no significant difference in the
probability of experiencing an initial viral load response after starting therapy between coinfected and monoinfected individuals.26,30 Moreover, virologic failure did not differ between
76
Chapter 3.2
co-infected and monoinfected individuals aged 25 years and older and differed only slightly
among the youngest age group. We cannot unravel whether this is the result of toxicity or
adherence. The difference in virologic failure is unlikely to be caused by progressive liver
disease because in general the duration of HCV infection is longer in older individuals. More
research on the effect of HCV co-infection on virologic failure is necessary.31
Co-infected individuals had a much higher risk of hepatitis or liver-related mortality
compared with monoinfected individuals in the pre-cART as well as the cART eras. This has
been reported previously,6 although a substantial proportion (>40%) of the study population
in that seroprevalent cohort with a missing HCV status were excluded. Individuals with
a missing HCV status often are excluded from studies6,8,11 and can bias the results.14 To
overcome this, we imputed missing HCV status and applied additional left truncation from
the start of routine HCV data collection in each cohort.
Among co-infected individuals in our study, mortality from hepatitis or liver-related
causes was lower in the cART era compared with the pre-cART era. This decrease might
be explained by the use of cART, and by the wide availability of HCV therapy since 2001.
We were not able to estimate at a population level the effect of cART before HCV therapy
became available owing to the small number of hepatitis or liver-related deaths observed
between 1997 and 2000. Furthermore, no data on HCV treatment were available in the
current CASCADE dataset. However, coverage and effectiveness of HCV treatment is low
in co-infected individuals,32 especially in co-infected drug users who account for the
majority of HCV infections in this population.33 Several studies have shown that use of cART
is associated with a lower rate of liver fibrosis and cirrhosis34,35 and that these benefits
outweigh the risks of hepatotoxicity caused by cART,36 but these studies are limited because
they did not take time since HIV infection into account.
In monoinfected patients, guidelines recommend that the decision to start treatment
for HCV infection is based on the degree of liver fibrosis and HCV genotype.37 An increased
risk of both HIV and/or AIDS and hepatitis or liver-related mortality among co-infected
individuals in the cART era might suggest that co-infected patients should start HIV and HCV
treatment sooner after diagnosis to reduce the likelihood of disease progression, even in
the absence of liver fibrosis.28,38 Direct-acting antivirals against HCV are likely to be available
in the near future; these may provide a cure to a large number of HIV/HCV co-infected
patients.39 Although results with the HCV protease inhibitors telaprevir and boceprevir
are highly encouraging, their effects in co-infected patients are still in the trial phase. This
emphasizes the need for careful evaluation of uptake and effectiveness of the direct-acting
antivirals in co-infected individuals. Extended follow-up in the cART era also will provide
insight into the effect of current and future HCV therapy regimens on mortality.
CD4 cell count and HIV RNA were not taken into account in our analysis because they
might be intermediate variables in the causal pathway of the effect of HCV on mortality. Then
77
the residual effect of HCV on mortality, over and above that driven through immunologic
or virologic progression, would be reflected instead of the effect of HCV on mortality in the
population. This would be of interest for future research. Because HCV status is measured
frequently in only a small group of individuals, HCV status could not be included as a timedependent covariable in our analyses. In addition, a substantial proportion of individuals
were not tested for HCV RNA, but it is most likely that they are chronically infected because
spontaneous clearance of HCV in HIV-infected individuals is rare.40
Although information on the duration of HIV infection is known for all patients,
information on the duration of HCV infection for all is lacking. Thus, co-infected individuals
were assumed to be HCV positive from the time of HIV seroconversion onward. This is likely
to be true for IDUs and those with hemophilia but MSM are more likely to be infected with
HIV before HCV infection because HIV is spread more efficiently sexually than HCV. Because
the main expansion of the HCV epidemic started after 2002,17 most of the MSM in our study
will have been infected with HCV for a relatively short time and this may be too short a time
for us to witness the sequelae of HCV infection.4 The increase in the proportion of recently
HCV-infected MSM in the cART era might, in addition to cART use, explain a later onset
of death after HIV seroconversion from hepatitis or liver-related causes among co-infected
individuals in the cART era compared with the pre-cART era. We included an interaction
between age at HIV seroconversion and co-infection status in the analysis as proxy for the
duration of HCV infection. Although the lack of direct information on the duration of HCV
infection is a potential limitation of our study, studies with information on the timing of
both infections and sufficient follow-up to permit analyses of mortality are non-existent.
Several potential limitations of our study should be mentioned. Because classification
of COD might not have been uniform within cohorts, we cannot exclude the possibility of
misclassification in COD. Furthermore, because all cohorts were initiated to evaluate the
consequences of HIV infection, COD might have been more likely to be classified as HIV
and/or AIDS when individuals had a low CD4 cell count. On the other hand, we did not have
sufficient information on hepatitis B status and alcohol use, which might have resulted in
hepatitis or liver-related death.41
To reliably impute missing HCV status and COD, the analyses were restricted to
cohorts for whom information on COD was available for at least 50% of reported deaths
and HCV status was known for at least 50% of individuals. There is no reason to expect the
effect of HCV on HIV disease progression to differ between cohorts that collect data on
COD and/or co-infection status and those that do not. Furthermore, the relative hazard of
dying did not differ significantly between the 16 included and the 5 excluded cohorts (data
not shown) and, given that our dataset was international, we believe that the results are
generalizable to high-income countries.42
In conclusion, HCV co-infected individuals appear to be at increased risk of HIV- and/
78
Chapter 3.2
or AIDS-related mortality in the cART era. Although the risk of hepatitis or liver-related
mortality has decreased since cART became available, it is higher among co-infected
individuals compared with those with only HIV. This underscores the importance of early
diagnosis of HCV infection in HIV-infected individuals and the need for routine screening
of HCV among high-risk groups, including those not (yet) infected with HIV. Our findings
highlight the importance of interventions to increase the uptake of HCV treatment in coinfected individuals.
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Received January 13, 2012. Accepted December 18, 2012.
Acknowledgments
The authors are grateful to the clinical board of Concerted Action on Seroconversion to AIDS
and Death in Europe (CASCADE), and Heiner Bucher, Andrea de Luca, Martin Fisher, and
John Gill for scoring the most likely underlying causes of death when more than one cause
of death was given. The authors also are grateful to the CASCADE Steering Committee: Julia
Del Amo (Chair), Laurence Meyer (Vice Chair), Heiner C. Bucher, Geneviève Chêne, Osamah
Hamouda, Deenan Pillay, Maria Prins, Magda Rosinska, Caroline Sabin, and Giota Touloumi;
the CASCADE Co-ordinating Centre: Kholoud Porter (Project Leader), Ashley Olson, Kate
Coughlin, Sarah Walker, and Abdel Babiker; the CASCADE Clinical Advisory Board: Heiner C.
Bucher, Andrea De Luca, Martin Fisher, and Roberto Muga; and the CASCADE Collaborators,
as follows: Austria: Austrian HIV Cohort Study (Robert Zangerle); Australia: PHAEDRA cohort
(Tony Kelleher, David Cooper, Pat Grey, Robert Finlayson, and Mark Bloch), Sydney AIDS
Prospective Study and Sydney Primary HIV Infection cohort (Tony Kelleher, Tim Ramacciotti,
Linda Gelgor, David Cooper, and Don Smith); Canada: South Alberta clinic (John Gill); Estonia:
Tartu U ̈likool (Irja Lutsar); France: ANRS CO3 Aquitaine cohort (Geneviève Chêne, Francois
Dabis, Rodolphe Thiebaut, and Bernard Masquelier), ANRS CO4 French Hospital Database
(Dominique Costagliola and Marguerite Guiguet), Lyon Primary Infection cohort (Philippe
Vanhems), French ANRS CO6 PRIMO cohort (Marie-Laure Chaix and Jade Ghosn), ANRS
CO2 SEROCO cohort (Laurence Meyer and Faroudy Boufassa); Germany: German cohort
(Osamah Hamouda, Claudia Kücherer, and Barbara Bartmeyer); Greece: AMACS (Vasilios
Paparizos, Panagiotis Gargalianos-Kakolyris, and Marios Lazanas); Greek Hemophilia cohort
(Giota Touloumi, Nikos Pantazis, and Olga Katsarou); Italy: Italian Seroconversion Study
(Giovanni Rezza and Maria Dorrucci), Italian Cohort of Antiretroviral Naive Patients (ICONA)
81
cohort (Antonella d’Arminio Monforte and Andrea De Luca); The Netherlands: Amsterdam
Cohort Studies among homosexual men and drug users (Maria Prins, Ronald Geskus, Jannie
van der Helm, and Hanneke Schuitemaker); Norway: Oslo and Ulleval Hospital cohorts
(Mette Sannes, Oddbjorn Brubakk, and Anne-Marte Bakken Kran); Poland: National Institute
of Hygiene (Magdalena Rosinska); Spain: Badalona injection drug user (IDU) hospital cohort
(Roberto Muga and Jordi Tor), Barcelona IDU Cohort (Patricia Garcia de Olalla and Joan
Cayla), Cohort of HIV Research Network - seroconverter (CoRIS-scv) (Julia del Amo, Santiago
Moreno, and Susana Monge), Madrid cohort (Julia Del Amo and Jorge del Romero), and the
Valencia IDU cohort (Santiago Pérez-Hoyos); Switzerland: Swiss HIV Cohort Study (Heiner
C. Bucher, Martin Rickenbach, and Patrick Francioli); Ukraine: Perinatal Prevention of AIDS
Initiative (Ruslan Malyuta); United Kingdom: Health Protection Agency (Gary Murphy),
Royal Free haemophilia cohort (Caroline Sabin), UK Register of HIV Seroconverters (Kholoud
Porter, Anne Johnson, Andrew Phillips, and Abdel Babiker), University College London
(Deenan Pillay); African cohorts: Genital Shedding Study (United States: Charles Morrison,
Family Health International; Robert Salata, Case Western Reserve University; Uganda: Roy
Mugerwa, Makerere University; Zimbabwe: Tsungai Chipato, University of Zimbabwe);
International AIDS Vaccine Initiative Early Infections Cohort (Kenya, Rwanda, South Africa,
Uganda, Zambia: Pauli N. Amornkul, International AIDS Vaccine Initiative, Unites States; Jill
Gilmour, International AIDS Vaccine Initiative, United Kingdom; Anatoli Kamali, Uganda Virus
Research Institute/Medical Research Council Uganda; Etienne Karita, Projet San Francisco,
Rwanda). The authors also thank the EuroCoord Executive Board: Geneviève Chêne,
University Bordeaux Segalen, France; Dominique Costagliola, Institut National de la Santé
et de la Recherche Médicale, France; Julia Del Amo, Instituto de Salud Carlos III, Spain; Carlo
Giaquinto, Fondazione Paediatric European Network for Treatment of AIDS (PENTA), Italy;
Di Gibb, Medical Research Council, United Kingdom; Jesper Grarup, Københavns Universitet,
Denmark; Ole Kirk, Københavns Universitet, Denmark; Bruno Ledergerber, University
of Zurich, Switzerland; Laurence Meyer, Institut National de la Santé et de la Recherche
Médicale, France; Alex Panteleev, St. Petersburg City AIDS Centre, Russian Federation;
Andrew Phillips, University College London, United Kingdom; Kholoud Porter (Chair), Medical
Research Council, United Kingdom; Caroline Sabin (Scientific Coordinator), University College
London, United Kingdom; Claire Thorne, University College London, United Kingdom; and
Stephen Welch, Fondazione PENTA, United Kingdom; EuroCoord Council of Partners: JeanPierre Aboulker, Institut National de la Santé et de la Recherche Médicale, France; Jan
Albert, Karolinska Institute, Sweden; Silvia Asandi, Romanian Angel Appeal Foundation,
Romania; Geneviève Chêne, University Bordeaux Segalen, France; Dominique Costagliola,
INSERM, France; Antonella d’Arminio Monforte, ICONA Foundation, Italy; Stéphane De Wit,
St. Pierre University Hospital, Belgium; Frank De Wolf (Chair), Stichting HIV Monitoring, The
Netherlands; Julia Del Amo, Instituto de Salud Carlos III, Spain; José Gatell, Fundació Privada
82
Chapter 3.2
Clínic per a la Recerca Bíomèdica, Spain; Carlo Giaquinto, Fondazione PENTA, Italy; Osamah
Hamouda, Robert Koch Institut, Germany; Igor Karpov, University of Minsk, Belarus; Bruno
Ledergerber, University of Zurich, Switzerland; Jens Lundgren, Københavns Universitet,
Denmark; Ruslan Malyuta, Perinatal Prevention of AIDS Initiative, Ukraine; Claus Møller,
Cadpeople A/S, Denmark; Andrew Phillips, University College London, United Kingdom;
Kholoud Porter, Medical Research Council, United Kingdom; Maria Prins, Academic Medical
Centre, The Netherlands; Aza Rakhmanova, St. Petersburg City AIDS Centre, Russian
Federation; Jürgen Rockstroh, University of Bonn, Germany; Magda Rosinska, National
Institute of Public Health, National Institute of Hygiene, Poland; Claire Thorne, University
College London, United Kingdom; Giota Touloumi, National and Kapodistrian University of
Athens, Greece; Alain Volny Anne, European AIDS Treatment Group, France; the EuroCoord
External Advisory Board: David Cooper, University of New South Wales, Australia; Nikos
Dedes, Positive Voice, Greece; Kevin Fenton, Centers for Disease Control and Prevention,
United States; David Pizzuti, Gilead Sciences, United States; Marco Vitoria, World Health
Organisation, Switzerland; and the EuroCoord Secretariat: Kate Coughlin, MRC Clinical Trials
Unit, United Kingdom; Michelle Ellefson, Københavns Universitet, Denmark; Silvia Faggion,
Fondazione PENTA, Italy; Richard Frost, MRC Regional Centre London, United Kingdom;
Christine Schwimmer, University Bordeaux Segalen, France; Martin Scott, UCL European
Research and Development Office, United Kingdom.
Jannie van der Helm was responsible for the acquisition of data, drafting of the
manuscript, statistical analysis, and analysis and interpretation of data; Ronald Geskus was
responsible for the acquisition of data, study concept and design, statistical analysis, analysis
and interpretation of data, critical revision of the manuscript for important intellectual
content, and analysis supervision; Caroline Sabin, Laurence Meyer, Julia del Amo, Geneviêve
Chène, Maria Dorrucci, and Roberto Muga were responsible for the acquisition of data,
analysis and interpretation of data, and critical revision of the manuscript for important
intellectual content; Kholoud Porter was responsible for the acquisition of data, coordination
of the data pooling, analysis and interpretation of data, critical revision of the manuscript
for important intellectual content, and obtained funding; and Maria Prins was responsible
for the acquisition of data, study concept and design, analysis and interpretation of data,
critical revision of the manuscript for important intellectual content, and study supervision.
Conflicts of interest
The authors disclose no conflicts.
Funding
Supported by the European Union Seventh Framework Programme (FP7/2007-2013) under
EuroCoord grant agreement 260694.
83
Supplementary materials
and methods
Quantifying the effects of the covariables on the subdistribution hazard
We provide a detailed description and motivation of the model that was used for quantifying
the effects of the covariables on the subdistribution hazard. The time origin of the survival
analyses was the moment of HIV infection. Because of the small number of events for some
causes of death and some covariable combinations, we had to assume several effects to be
equal. In total, we estimated 26 parameters.
Cause-specific and subdistribution hazards
In competing-risks situations, there are 2 types of hazards that can be estimated, the causespecific hazard and the subdistribution hazard. The cause-specific hazard quantifies the
progression rate to the different end points, given that an individual is still event free. A
regression model on the cause-specific hazard reflects how this progression rate depends
on covariables. The subdistribution hazard regression model, which we used, quantifies the
effect of each covariable on the cumulative scale, taking into account the effects of the
covariable on the competing causes. For example, individuals at risk may have the same
death rate for natural causes in both calendar periods (ie, same cause-specific hazard that
reflects etiology). However, the subdistribution hazard for natural causes, which also takes
into account calendar period effects on other causes, might decrease in the cART era because
fewer individuals die of AIDS and remain at risk for natural causes. Thus, the subdistribution hazard reflects a combination of etiology and cumulative effect. When estimating the
cause-specific hazard more effects can be assumed to be equal compared with using the
subdistribution hazard because the subdistribution hazard takes into account the effects
on competing causes. So, if we assume effects of covariables to be different for the causespecific hazard, then we certainly assume such effects to differ for the subdistribution
hazard.
Assumptions on calendar time effect and HCV
Individual CODs may have completely different hazards over time since HIV infection.
Therefore, we assume the baseline hazard to differ by COD.
Our main interest was to investigate the effect of hepatitis C co-infection on the
different CODs, and how this has changed after the introduction of cART. Therefore,
when studying mortality from each COD, the HCV status, calendar period, as well as their
interaction were included in the model. The only exception was that we assumed hepatitis
or liver-related mortality not to depend on calendar time in HIV-monoinfected individuals
84
Chapter 3.2
because of the small number of events. The following assumptions were applied.
Assumptions on sex effect and HCV
Males were the reference group. Although a sex effect in HCV progression has been
suggested, effects of sex were assumed not to depend on HCV status. In the pre-cART era
we allowed for a sex effect, which we assumed equal for every COD. In the cART era it
has been suggested that females are more likely to benefit from cART,1 which affects their
AIDS-specific hazard. The same effect is reflected in the AIDS subdistribution hazard and
therefore this also affects the subdistribution hazards for non-natural and natural death.
Because of the small number of events we did not assume a sex effect for hepatitis or liverrelated mortality between the calendar periods among monoinfected persons. Because we
assumed sex effects to be independent of HCV status, we assumed sex effects on hepatitis
or liver-related mortality to be independent of the calendar period among co-infected
persons as well.
In a sensitivity analysis we took into account a sex effect (ie, the effects of sex were
assumed to depend on HCV status), which did not change the results.
Assumptions on age effect and HCV
Among the monoinfected group, the effect of age was assumed to be equal for HIV- and/
or AIDS-related, hepatitis or liver-related, and natural death, but different for non-natural
death because mortality generally increases with increasing age, except for non-natural
causes. Among the co-infected group, the relative age effect on the subdistribution hazard,
compared with monoinfected persons, was assumed to be the same for the 3 CODs. For
hepatitis or liver-related mortality, we allowed this change in age effect to be different
because age at HIV infection is a proxy for time since HCV infection (eg, an HCV-infected
individual aged 50 at HIV infection is likely to have been HCV infected for a longer duration
than a person aged 20 at HIV infection). The effect of age was assumed to be independent
of calendar period.
Assumptions on risk group effect and HCV
IDUs especially are seen as a group for which effects of HCV on COD are different. Among
monoinfected persons, we assumed subdistribution hazards of MSW and those with
hemophilia to be equal to MSM of the same sex and age in both calendar periods for all
CODs. The subdistribution hazard of IDUs was assumed to differ for every COD in the precART era, except for hepatitis or liver-related causes. We assumed the effect in the cART era
to be different from the pre-cART era, but the effect on the relative subdistribution hazard
in the cART era, compared with the combined other risk groups, was assumed to be the
same for natural and non-natural death.
85
Among co-infected persons, for hepatitis or liver-related mortality, because of the
small numbers, we assumed subdistribution hazards of MSW and those with hemophilia to
be equal to MSM of the same sex and age, and not to depend on the calendar period. For the
other 3 CODs, we assumed the subdistribution hazard of MSW and those with hemophilia
to be different from MSM. However, the effect relative to HCV-positive MSM was assumed
to be equal, and the same in both calendar periods. For IDU we assumed effects, relative
to co-infected MSM of the same sex and age, to be the same for HIV and/or AIDS-related,
hepatitis or liver-related, and natural death causes, and not to differ by calendar period. It
is known that co-infected IDUs are at increased risk of non-natural mortality. Therefore, we
assumed that the relative effect had a different value, but again no interaction with calendar
period was assumed.
Supplementary reference
1.
86
Jarrin I, Geskus R, Bhaskaran K, et al. Gender differences in HIV progression to AIDS
and death in industrialized countries:
slower disease progression following HIV
seroconversion in women. Am J Epidemiol
2008;168:532–540.
Chapter 3.2
4
Chlamydia infections
in Suriname and
The Netherlands
87
88
Urogenital Chlamydia
trachomatis infections
among Ethnic Groups in
Paramaribo, Suriname; Determinants and
Ethnic Sexual Mixing Patterns
Jannie J. van der Helm1,2
Reinier J. M. Bom3
Antoon W. Grünberg4
Sylvia M. Bruisten3,5,6
Maarten F. Schim van der Loeff2,6
Leslie O. A. Sabajo7
Henry J. C. de Vries1,6,8,9
PLoS One. 2013 Jul 17;8(7):e68698
1
STI Outpatient Clinic, Public Health Service Amsterdam, Amsterdam, The Netherlands, 2Department of
Research, Public Health Service Amsterdam, Amsterdam, The Netherlands, 3Public Health Laboratory,
Public Health Service Amsterdam, Amsterdam, The Netherlands, 4 Lobi Foundation, Paramaribo,
Suriname, 5 Department of Experimental Virology, Academic Medical Center (AMC), University of
Amsterdam, Amsterdam, The Netherlands, 6Center for Infection and Immunity Amsterdam (CINIMA),
Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands, 7Dermatological
Service, Ministry of Health, Paramaribo, Suriname, 8Department of Dermatology, Academic Medical
Center, University of Amsterdam, Amsterdam, The Netherlands, 9Center for Infectious Disease Control,
National Institute of Public Health and the Environment, Bilthoven, The Netherlands.
Abstract
Background: Little is known about the epidemiology of urogenital Chlamydia trachomatis
infection (chlamydia) in Suriname. Suriname is a society composed of many ethnic groups,
such as Creoles, Maroons, Hindustani, Javanese, Chinese, Caucasians, and indigenous
Amerindians. We estimated determinants for chlamydia, including the role of ethnicity, and
identified transmission patterns and ethnic sexual networks among clients of two clinics in
Paramaribo, Suriname.
Methods: Participants were recruited at two sites a sexually transmitted infections (STI) clinic
and a family planning (FP) clinic in Paramaribo. Urine samples from men and nurse-collected
vaginal swabs were obtained for nucleic acid amplification testing. Logistic regression
analysis was used to identify determinants of chlamydia. Multilocus sequence typing (MLST)
was performed to genotype C. trachomatis. To identify transmission patterns and sexual
networks, a minimum spanning tree was created, using full MLST profiles. Clusters in the
minimum spanning tree were compared for ethnic composition.
Results: Between March 2008 and July 2010, 415 men and 274 women were included
at the STI clinic and 819 women at the FP clinic. Overall chlamydia prevalence was 15%
(224/1508). Age, ethnicity, and recruitment site were significantly associated with chlamydia
in multivariable analysis. Participants of Creole and Javanese ethnicity were more frequently
infected with urogenital chlamydia. Although sexual mixing with other ethnic groups did
differ significantly per ethnicity, this mixing was not independently significantly associated
with chlamydia. We typed 170 C. trachomatis-positive samples (76%) and identified three
large C. trachomatis clusters. Although the proportion from various ethnic groups differed
significantly between the clusters (P=0.003), all five major ethnic groups were represented
in all three clusters.
Conclusion: Chlamydia prevalence in Suriname is high and targeted prevention measures
are required. Although ethnic sexual mixing differed between ethnic groups, differences in
prevalence between ethnic groups could not be explained by sexual mixing.
90
Chapter 4.1
Introduction
U
rogenital Chlamydia trachomatis infection, or chlamydia, is the most prevalent bacterial
sexually transmitted infection (STI) worldwide.1 Left untreated, chlamydia can lead to
complications like pelvic inflammatory disease, ectopic pregnancy, and infertility. To reduce
complications and transmission of chlamydia, active case finding and early treatment are
critical strategies.2,3
Suriname is on the South American continent, but as a consequence of a shared
colonial past it is more socio-culturally connected to the Caribbean region. The prevalence of
chlamydia in the general population in many countries of the Caribbean is unknown because
testing facilities are lacking and routine screening is not available. A study in Guadeloupe
among patients who were referred for a genital infection, showed a prevalence of 17%
among men and 10% among women.4 A study in Barbados among the general population
showed a prevalence of 11%5 and a study in Trinidad and Tobago among pregnant women
showed a prevalence of 21%.6 We previously found a prevalence of 21% among high-risk
women and 9% among low-risk women in Suriname.7
The variety of ethnicities is distinctive for Surinamese society. The Surinamese
population consists of Creoles and Maroons (both descendants of African diaspora due to the
slave trade), Hindustani, Javanese, and Chinese (all descendants of labor immigrants from
the former British Indies, Dutch Indies, and China, respectively), Caucasians (descendants of
European colonialists), indigenous Amerindians, and people of mixed race. The five major
groups are Hindustani (27.4%), Creole (17.7%), Maroon (14.7%), Javanese (14.6%), and mixed
race (12.5%). These groups cannot be considered a ‘minority’ since they are comparable in
size and integrated parts of the total population.8 Previous Surinamese studies on sexuality,
however, have mainly focused on the Creoles, and rarely on other ethnicities.9,10
The structure of sexual networks is important for STI transmission, but elucidating
these transmission networks based on epidemiological and behavioral data alone is
challenging. Combining epidemiological and behavioral data with molecular microbial
genotyping techniques can provide more insight into the transmission patterns of
C. trachomatis. Molecular typing can reveal the relatedness of bacterial strains that
circulate among the population and may identify transmission networks at the pathogen
level. Because of the low genetic variability of C. trachomatis, a typing tool with a high
discriminatory resolution between strains is necessary to reveal network associations of
C. trachomatis. Whereas suitable molecular techniques for Neisseria gonorrhoeae have
been available for some time,11 high-resolution typing methods for C. trachomatis, such as
multilocus sequence typing (MLST), have only been developed recently.12,13 Studies using
high-resolution typing of C. trachomatis strains have examined the relation between clinical
91
symptoms14, geographic location15, and sexual risk group.16,17 The relation between ethnodemographic characteristics and C. trachomatis strains in sexual transmission networks
of heterosexual populations has not yet been analyzed using high-resolution molecular
pathogen typing.
Earlier we reported a high chlamydia prevalence among both low- and high-risk
women.7 Here we report on the chlamydia prevalence among women as well as men. The
aim of our study among men and women at two clinics in Paramaribo, Suriname was to
elucidate determinants for chlamydia, notably the role of ethnicity and ethnic sexual mixing,
and to identify transmission patterns and sexual networks using molecular epidemiological
network analyses.
Methods
Ethics statement
The study was approved by the ethics committee of the Ministry of Health of the Republic
of Suriname (VG010-2007) and the ethics committee of the Academic Medical Center,
University of Amsterdam, the Netherlands (MEC07/127). Patients participated anonymously
and gave written informed consent.
Recruitment sites and population
Participants were recruited at two sites in Paramaribo, Suriname:
1) The Dermatological Service, an integrated outpatient STI clinic, frequented by men
and women, that offers free-of-charge examination and treatment of STIs and infectious
skin diseases such as leprosy and leishmaniasis. All individuals who visited for an STI checkup were invited to participate in the study. These participants were considered to be a ‘highrisk’ population for chlamydia.
2) The Lobi Foundation, a family planning (FP) clinic frequented by women only. All
consecutive women visiting the clinic were invited to participate in the study. As women do
not primarily visit this clinic to be checked for STIs, these participants were considered to be
a ‘low-risk’ population for chlamydia.
Recruitment took place between March 2008 and July 2010. Exclusion criteria were:
age younger than 18 years and previous participation in the study. A nurse interviewed
participants about demographic characteristics (including self-reported ethnicity) and
sexual behavior.
Specimen collection and testing procedures
Urine samples from males and nurse-collected vaginal swabs from females were obtained for
92
Chapter 4.1
nucleic acid amplification test (NAAT) testing with the monospecific Aptima Chlamydia assay
for the detection of C. trachomatis rRNA (Hologic Gen-Probe Inc., San Diego, USA). Nurses
were trained to collect the swabs before routine speculum examination was performed, as
described before.7 The samples were collected according to the manufacturer’s instructions,
stored in a fridge (at temperature between 2° and 7°C) and packed according to IATA rules
for transport by plane to the Public Health Laboratory in Amsterdam for NAAT testing.
Technicians performing NAAT did not receive any information about the participant. NAAT
test results were forwarded to the two clinics in Suriname, where the chlamydia positive
participants were treated within 1 to 8 weeks after the clinic visit with doxycycline (100
mg bid for 7 days at the FP clinic and 100 mg bid for 10 days at the STI clinic) or, in case
of (probable) pregnancy, with a single 1000 mg oral dose of azithromycin. Participants
who tested positive for urogenital chlamydia also received treatment to be used by their
partner(s).
MLST
Multilocus sequence typing (MLST) was used to genotype C. trachomatis. Details of this
method were described previously.13 In brief, DNA was extracted at the Public Health
Laboratory Amsterdam from transport medium in which the swab or urine had been put,
using isopropanol precipitation. All DNA isolates were tested for the presence of chlamydial
DNA with the in-house pmpH qPCR as described previously.18,19 The DNA isolates were
amplified by a nested PCR and sequenced for the regions ompA, CT046 (hctB), CT058,
CT144, CT172 and CT682 (pbpB). The sequences were checked against an in-house library
and against the Chlamydia trachomatis MLST database (mlst.bmc.uu.se), and were given an
allele number for each region. Only samples of which all alleles were successfully amplified,
sequenced and identified, and therefore had obtained a full MLST profile (sequence type,
ST), were included in the analyses. As ompA is part of the MLST scheme, genovars could
be assigned for all included samples. A minimum spanning tree was generated using MLST
profiles. Cluster analysis was performed allowing single locus variance using BioNumerics
7 (Applied Maths, Sint-Martens-Latem, Belgium). A cluster was defined as a group of STs
differing by not more than one locus from another ST within that group, and had to include
at least 10% of the total number of samples (i.e. at least 17 samples). Typing data of the
study population are also reported in a paper comparing the distributions of C. trachomatis
strains among residents of Paramaribo and residents of Amsterdam (Bom et al., submitted).
The study population consisted of high-risk men and women recruited at the STI clinic
and low-risk women recruited at the FP clinic. To examine whether epidemiological
characteristics differed between these three study groups the χ2-test for independence was
93
used. Prevalence was calculated as the number of positive tests in the study period divided
by the total number of individuals tested in the study period.20 To assess determinants of
chlamydia, we performed univariable logistic regression analysis and examined the effect of
the following variables: age, education, ethnicity, different ethnic group of sexual partners
(i.e. ethnic sexual mixing), study group (including sex and recruitment site), condom use,
number of partners in the preceding month, number of partners in the preceding 12
months, having had sex in exchange for money or goods, and (for men) having had sex with
men (MSM). Age was divided into four categories. Because of small numbers we grouped
Caucasian, Chinese, and Indigenous Amerindian ethnicities together in univariable and
multivariable analyses. Ethnic sexual mixing was defined as having had sex with at least one
partner of another ethnicity in the preceding 12 months. Variables that were associated
with chlamydia at P≤0.1 in the univariable analysis were entered into a multivariable model.
Higher chlamydia prevalence at younger age and, with a higher number of sexual partners
has been established by various other studies21 and therefore these determinants were
forced into the multivariable model. Ethnicity and ethnic group of the partner(s) were
variables of specific interest and were also forced into the model. To avoid multicollinearity,
we only included the variable ‘number of partners in the preceding 12 months’ in the
model and not the variable ‘number of partners in the preceding month’. We considered
P<0.05 as statistically significant. We checked for interactions between study group and all
other variables in the final model and also checked for interactions between the number of
partners in the preceding 12 months and ethnic sexual mixing.
To examine whether ethnic group was a determinant for ethnic sexual mixing, we
performed a multivariable logistic regression analysis. Variables that were associated with
ethnic sexual mixing at P≤0.1 in univariable analysis were entered into a multivariable
model. The final model included number of partners in the preceding 12 months, sex in
exchange for money or goods, and study group.
We compared the observed frequency of people who had sexual partners from their
own ethnicity with the expected frequency (if partner selection from the population would
have occurred at random with respect to ethnic background) by using the χ2 goodness-offit test.22 The expected number of people with sexual partners from their own ethnicity
was calculated by multiplying the total number of reported partners of an ethnicity by the
proportion of individuals from each ethnicity in the study. In order to identify transmission
patterns and sexual networks, a minimum spanning tree was made with different colors
for different ethnicities and C. trachomatis clusters were compared in terms of ethnic
composition using χ2-tests for independence. Analyses were performed with SPSS package
version 19.0 (SPSS Inc., Chicago, IL).
94
Chapter 4.1
Results
Study population
Table 1. Epidemiological characteristics of the study population by study group in Paramaribo, Suriname, 2008–2010.
Men
recruited
at STI clinic
Women
recruited
at STI clinic
Women
recruited
atfamily
planning
clinic
n (% )
n (% )
n (% )
P value
Total study
population
n (% )
Demographic characteristics
Med ian ag e in years (IQR)
Age in years
Ed ucation
Ethnic group a
29 (25–38)
28 (23–33)
31 (25–37)
< 0.001
< 25
109 (26.3)
105 (38.3)
184 (22.5)
< 0.001
29 (25–37)
2 5 –2 9
116 (28.0)
67 (24.5)
198 (24.2)
381 (25.3)
3 0 –3 4
59 (14.2)
47 (17.2)
173 (21.2)
279 (18.5)
> = 35
131 (31.6)
55 (20.1)
264 (32.2)
L ow
235 (56.6)
99 (36.1)
277 (33.8)
Med ium
111 (26.7)
109 (39.8)
427 (52.1)
647 (42.9)
H ig h
40 (9.6)
46 (16.8)
111 (13.6)
197 (13.1)
Un k n o w n
29 (7.0)
20 (7.3)
4 (0.5)
C aucasian
2 (0.5)
11 (4.0)
6 (0.7)
C hinese
1 (0.2)
6 (2.2)
6 (0.7)
13 (0.9)
444 (29.4)
398 (26.4)
450 (29.8)
< 0.001
611 (40.5)
53 (3.5)
< 0.001
19 (1.3)
C reole
166 (40.0)
79 (28.8)
199 (24.3)
H ind ustani
33 (8.0)
30 (10.9)
226 (27.6)
289 (19.2)
Ind ig enous
6 (1.4)
9 (3.3)
10 (1.2)
25 (1.7)
J avanese
14 (3.4)
17 (6.2)
148 (17.9)
177 (11.7)
Maroon
120 (28.9)
53 (19.3)
85 (10.4)
258 (17.1)
Mixed
72 (17.3)
67 (24.5)
138 (16.8)
277 (18.4)
Had only sexual partners
from same ethnic group
162 (40.5)
120 (48.0)
508 (64.9)
Had at least one sexual partner
from another ethnic group
238 (59.5)
130 (52.0)
275 (35.1)
Sexual behavior
Ethnic sexual mixing
a
Condom use a
Number of partners preceding month
a
A lways
126 (30.7)
76 (28.0)
79 (9.8)
Never or inconsistent
285 (69.3)
195 (72.0)
731 (90.2)
0
22 (5.3)
16 (6.3)
34 (4.2)
1
228 (55.1)
185 (73.4)
741 (91.7)
>1
164 (39.6)
51 (20.2)
33 (4.1)
Median number of partners in the
preceding 12 months (IQR)
2 (1–4)
1 (1–2)
1 (1–1)
Mean number of partners in the
preceding 12 months
7
16
1
2 (0.5)
11 (4.0)
11 (1.3)
Number of partners in the
preceding 12 months
Sex in exchange for money or goods
Men having sex with men a
0
a
< 0.001
790 (55.1)
643 (44.9)
< 0.001
281 (18.8)
< 0.001
72 (4.9)
1211 (81.2)
1154 (78.3)
248 (16.8)
< 0.001
1 (1–2)
< 0.001
24 (1.6)
1
109 (26.3)
136 (49.6)
649 (79.2)
894 (59.3)
2
114 (27.5)
64 (23.4)
108 (13.2)
286 (19.0)
>2
190 (45.8)
63 (23.0)
51 (6.1)
11 (2.7)
45 (16.7)
6 (0.7)
7 (1.7)
NA
NA
95 (22.9)
51 (18.6)
78 (9.5)
304 (20.2)
< 0.001
62 (4.2)
7 (1.7)
Chlamydia prevalence
Chlamydia trachomatis infection
diagnosis by NAAT
< 0.001
224 (14.9)
aNumbers do not add up to the column total due to missing data, percentages do add up to 100%.
Missing data: ethnic group n = 6, ethnic sexual mixing n = 75, condom use n = 16, number of partners in the preceding month
n = 34, sex in exchange for money or goods n = 22, men having sex with men n = 3.
IQR, interquartile range; NA, not available; NAAT, nucleic acid amplification test; p-values based on men attending the STI clinic,
women attending the STI clinic and women attending the family planning clinic.
95
A total of, 415 men and 1093 women were included in the study. The response rate among
men was 78.3%, among women visiting the STI clinic 83.0% and among women visiting the
FP clinic 99.8%. The included and excluded men did not differ by age (P=0.303) and ethnicity
(P=0.329). The included and excluded women visiting the STI clinic had a comparable age
(P=0.238) but ethnicity did differ (P=0.020). Demographics and sexual behavior of study
participants are shown in Table 1. All epidemiological characteristics differed significantly
between the three study groups. The overall median age was 29 years (IQR, 25–37) and the
majority had a low (40.5%) or medium (42.9%) level of education. In total, 444 (29.4%) were
of Creole ethnicity, 289 (19.2%) of Hindustani ethnicity, 177 (11.7%) of Javanese ethnicity,
277 (18.4%) were mixed race, and 258 (17.1%) were of Maroon ethnicity. Women visiting
the STI clinic were younger compared with men from the same site and women visiting
the FP clinic (P<0.001). Women visiting the STI clinic reported higher risk behavior, such as
>2 partners in the previous year (23.0%), and more frequently reported sex in exchange
for money or goods (16.7%), compared with women visiting the FP clinic (6.1% and 0.7%,
respectively).
Prevalence and determinants of chlamydia
The prevalence of chlamydia was 18.6% (95% CI, 14.3–23.6%) among women visiting the
STI clinic, 9.5% (95% CI, 7.7–11.7%) among women visiting the FP clinic7 and 22.9% (95%
CI, 19.0–27.1%) among male STI clinic visitors. The highest prevalence of chlamydia was
found among Creole men visiting the STI clinic (30.1%) but this was not significantly higher
than the prevalence among men from other ethnic groups which ranged between 15.2%
and 21.4% (P=0.123). Hindustani women had a slightly lower prevalence (6.3%) compared
with women from other ethnic groups, which ranged between 10.9% and 15.3% (P=0.054).
Univariable associations between epidemiological characteristics and chlamydia are shown
in Table 2. Age, ethnic group, ethnic sexual mixing, study group and number of partners in the
preceding 12 months were significantly associated with chlamydia in univariable analysis. In
multivariable analysis, chlamydia was significantly associated with ethnic group (OR, 1.76;
95% CI, 1.03–3.00 for Creoles, OR, 2.05; 95% CI, 1.09–3.84 for Javanese, both compared
with Hindustani); age (OR, 3.01; 95% CI, 1.93–4.71 for those aged <25 years, compared
with those aged ≤35); and study group (OR, 2.30; 95% CI, 1.52–3.49 for men visiting the STI
clinic and OR, 1.91; 95% CI 1.24–2.94 for women visiting the STI clinic, both compared with
women visiting the FP clinic), but not with ethnic sexual mixing (OR, 1.33; 95% CI, 0.96–1.85)
and number of partners in the preceding 12 months (OR, 1.39; 95% CI, 0.92–2.11 for having
>2 partners compared with having ≤1 partner) (Table 2). The interactions between study
group and all other variables in the final model and the interaction between the number of
partners in the preceding 12 months and ethnic sexual mixing were not significant.
96
Chapter 4.1
Table 2. Univariable and multivariable logistic regression analyses of determinants associated with chlamydia among the study
population included attwo sites in Paramaribo, Suriname, 2008–2010.
NAAT
positive
Univariable
OR (95%CI)
P value
< 0.001
Multivariable
Adjusted OR
(95%CI)*
P value
1
< 0.001
224/1508 (14.9)
n/N (%)
Stud y g roup
Age in years
Ed ucation
Ethnic g roup
Ethnic sexual mixing
Fam ily p lanning clinic – wom en
78/819 (9.5)
1
STI clinic – w om en
51/274 (18.6)
2.17 (1.48–3.19)
STI clinic – m en
95/415 (22.9)
2.82 (2.03–3.91)
< 25
90/398 (22.6)
3.36 (2.22–5.08)
2 5 –2 9
71/381 (18.6)
2.63 (1.72–4.04)
2.60 (1.65–4.09)
3 0 –3 4
27/279 (9.7)
1.23 (0.73–2.08)
1.26 (0.73–2.18)
> = 35
36/450 (8.0)
1
L ow
96/611 (15.7)
1
preceding month
preceding 12 months
Sex in exchange for
money or goods
2.30 (1.52–3.49)
< 0.001
3.01 (1.93–4.71)
1
Med ium
93/647 (14.4)
0.90 (0.66–1.23)
27/197 (13.7)
0.85 (0.54–1.35)
Un k n o w n
8/53 (15.1)
0.95 (0.44–2.09)
C reole
87/444 (19.6)
3.11 (1.88–5.14)
H ind u stani
21/289 (7.3)
1
1
J avanese
28/177 (15.8)
2.40 (1.32–4.37)
2.05 (1.09–3.84)
Maroon
36/258 (14.0)
2.07 (1.17–3.65)
0.96 (0.52–1.78)
Mixed
44/277 (15.9)
2.41 (1.39–4.17)
1.33 (0.72–2.35)
Othera
7/57 (12.3)
1.79 (0.72–4.43)
88/790 (11.1)
1
125/643 (19.4)
1.93 (1.43–2.59)
Had only sexual partners
from same ethnic group
A lways
45/281 (16.0)
1
Never or inconsistent
176/1211 (14.5)
0.89 (0.62–1.27)
0
8/72 (11.1)
1
1
152/1154 (13.2)
1.21 (0.57–2.58)
>1
58/248 (23.4)
2.44 (1.11–5.39)
≤1
104/918 (11.3)
1
2
49/286 (17.1)
1.62 (1.12–2.34)
>2
71/304 (23.4)
2.39 (1.71–3.33)
No
207/1424 (14.5)
1
Y es
13/62 (21.0)
1.56 (0.83–2.93)
< 0.001
0.878
H ig h
Had at least one sexual partner
from another ethnic group
C o n d o m u se
1.91 (1.24–2.94)
0.001
1.76 (1.03–3.00)
0.027
1.01 (0.38–2.67)
< 0.001
1
0.090
1.33 (0.96–1.85)
0.529
< 0.001
< 0.001
1
0.225
1.33 (0.88–2.01)
1.39 (0.92–2.11)
0.166
*ORs in the multivariable model are adjusted for all factors for which adjusted ORs are shown.
a
Other: Caucasian, Chinese, Indigenous.
NAAT, nucleic acid amplification test; OR, odds ratio; 95%CI, 95% confidence interval.
Sexual mixing among ethnic groups
A total of 643 participants (43.6%) reported sexual mixing with other ethnic groups, and
790 (52.4%) did not report any sexual mixing. Ethnic sexual mixing differed between ethnic
groups. Of the Hindustani 65 (23.5%) reported sexual mixing. This was higher for individuals
with Creole (n=191; 44.3%), Javanese (n=85; 49.4%), Maroon (n=95; 38.6%), or mixed race
(n=170; 65.9%) ethnicity (P,0.001). In multivariable analysis, adjusting for number of partners
in the preceding 12 months, sex in exchange for money or goods, and study group, ethnic
sexual mixing was significantly associated with ethnic group (OR, 1.87; 95% CI, 1.30–2.70 for
Creoles; OR, 3.34; 95% CI, 2.18–5.11 for Javanese; OR, 1.15; 95% CI, 0.75–1.76 for Maroon;
97
OR, 4.88; 95% CI, 3.26–7.30 for mixed race; all compared with Hindustani).
Table 3 shows the ethnic groups of the participants included in the study and the
observed and expected ethnic background of their partners. Of the Creole, Hindustani,
Javanese and Maroon participants between 60.5% and 77.9% reported to have had sex with a
partner of their own ethnicity; for mixed race individuals this was 44.4%. Maroon individuals
were more likely to have a partner with a Creole ethnicity (29.8%) compared with a partner
with a Hindustani (3.1%) or Javanese ethnicity (3.9%). Likewise, only 1% of the Hindustani
and Javanese individuals reported sex with a Maroon partner. The observed frequencies of
only having sexual partners from participants’ own ethnicity were significantly higher than
expected frequencies if partners had been selected from the population at random with
respect to ethnicity (P<0.001 for all 5 major ethnic groups).
Table 3. Ethnic sexual mixing patterns of men and women, Paramaribo, Suriname, 2008 to 2010.
Ethnic group of sexual partner
Creole partner
O
E
Hindustani partner
Javanese partner
Maroon partner
Mixed race partner
O
E
O
E
O
E
O
225 (77.9)
68
107 (60.5)
24
1 (0.6)
32
E
Ethnic group of study
participants
Creole (n = 444)
43 (24.3)
40
25 (9.7)
58
338
338
Other (n = 63) a
Tota l
535
O/E
2.0
534
353
3.3
353
203
4.5
204
272
4.2
272
2.0
x 2 = 268, p < 0.001
x 2 = 472, p < 0.001
x 2 = 339, p < 0.001
x 2 = 585, p < 0.001
x 2 = 96, p < 0.001
Percentages in row totals can exceed 100% as participants may have partners from various ethnicities.
O = observed; E = expected. x² based on goodness offit.
The expected number of people with sexual partners from their own ethnicity was calculated by multiplying the total number of re
ported partners of an ethnicity (e.g.n = 353 for Hindustani) by the proportion ofindividuals from each ethnicity in the study (e.g. 19
% for Hindustani).
O/E is the ratio ofthe observed number of partners (e.g. n = 225 for Hindustani) divided by the expected number of partners
from that ethnic group (e.g. n = 68 for Hindustani).
aOther; Caucasian, Chinese, Indigenous (n = 57), unknown (n = 6).
Genovar typing and MLST
We were able to type 170 samples of the 224 C. trachomatis positive samples (75.9%). The
strains belonged to nine ompA genovars, predominantly E (32.4%), F (19.4%), D (18.2%)
and I (12.9%). Furthermore, J (5.9%), G (5.3%), K (2.9%), B (1.8%), and H (1.2%) were found.
Among the 170 fully typed samples, we identified 65 different MLST profiles of which 32
(49%) were novel when checked against the MLST database on January 8, 2013. These
novel MLST profiles were found in 52 (31%) of 170 samples. A minimum spanning tree
was generated using MLST profiles (Figure 1) in which three large distinct clusters of C.
trachomatis strains could be identified. Cluster 1 consisted of 27 samples (genovars I (81.5%)
98
Chapter 4.1
Figure 1. Minimum spanning tree of 170 Chlamydia trachomatis positive samples in Paramaribo, Suriname
2008–2010. Each circle represents one MLST type. Size of the circles is proportional to the number of identical MLST profiles. Bold lines connect types that differ by one single locus. Halos indicate the three large distinct
clusters ($27 samples). Colors indicate ethnicity; blue – Creole, brown – mixed race, green – Javanese, yellow –
Maroon, pink – Hindustani, white – Indigenous Amerindian, Caucasian and unknown.
Figure 2. Distribution of individuals in Chlamydia trachomatis clusters within ethnic groups in Paramaribo, Suriname, 2008–2010. Colors indicate cluster: Blue – cluster 1; Green – cluster 2; Yellow – cluster 3; Pink – residual
group.
and J (18.5%)), cluster 2 consisted of 34 samples (all genovar E) and cluster 3 consisted of
36 samples (genovars D (23.5%) and F (76.5%)). There were 13 smaller clusters (containing
2–10 samples) and 20 singletons.
Although all five major ethnic groups were represented in all three clusters, the
proportion from various ethnic groups differed significantly between the three clusters
99
(P=0.003). Figure 2 shows the distribution of individuals in each cluster for each ethnic
group. Individuals with Javanese ethnicity were mainly found in cluster 2 (53.8%). Of the
Hindustani, 35.1% belonged to cluster 1. Of the Creole and mixed race individuals 45.9% and
55.9%, respectively, were found outside the three main clusters of C. trachomatis strains.
Discussion
Prevalence of chlamydia in Suriname
This is the first report on epidemiology of chlamydia in Suriname in both a high-risk and a
low-risk population. Previously, we described the high prevalence of 9% and 21% respectively
among low-risk and high-risk Surinamese women;7 here we report a very high prevalence of
23% among high-risk Surinamese men. The high prevalence found in Suriname in our study
can partly be attributed to the current lack of screening facilities in Suriname. The prevalence
among women visiting the FP clinic was comparable to that reported by a recent study in
the Caribbean region among women in the general population.5 Another study in the region
among women who were referred for a genital infection, presumably a high-risk group for
chlamydia, reported a prevalence of 11%,4 and among pregnant women a prevalence of
21% was found.6 Studies among STI clinic visitors in the Caribbean region are scarce, but a
study in Jamaica from 1999, in which chlamydia was tested by direct fluorescence assay and
culture (which are now considered obsolete diagnostics), reported a prevalence of 55%.23
The high prevalence found in low- or middle-income countries indicates the urgent need for
reliable and affordable diagnostics, preferably a point-of-care test. The prevalence found
among the STI clinic visitors is likely to be higher than the prevalence in the Surinamese
general population. Furthermore, despite the high response rate, the included and excluded
women visiting the STI clinic differed by ethnicity and the reported prevalence should be
interpreted as the prevalence among those who were tested and might not reflect the
‘true’ prevalence. The response rate among the population attending the FP clinic was very
high and the prevalence may be a reasonable reflection of the sexually active Surinamese
population. The higher prevalence indicates that preventive measures focused on the
sexually active population in general are urgently necessary. Our study showed that the
younger age group was disproportionately affected by chlamydia, so targeting prevention
at this group seems most cost-effective, especially since safe sex messages probably will be
more effective at sexual debut.9
Prevalence of chlamydia among ethnic groups
The Creole and Javanese groups seemed more affected by chlamydia compared with the
100
Chapter 4.1
Hindustani. A study from Trinidad and Tobago performed in 2004 compared three ethnic
groups (African, East Indian and mixed race) using univariable analysis and found that
individuals of East Indian descent were less likely to be infected with chlamydia compared
with those of African descent.6 Compared with Trinidad and Tobago, a society characterized
by two dominant ethnic groups, Surinamese society is much more ethnically diverse. Since
the prevalence in all but one ethnic group was above 12%, testing and treatment of all
groups is required. The distribution of ethnic groups included in our study was approximating
a correct representation of the actual Surinamese population according to the 2004
population census,8 although our study included more Creole and mixed race individuals
and less people with Hindustani ethnicity.
Chlamydia and sexual mixing among ethnic groups
Previously it was found that sexual mixing patterns could be important for dynamics of
the spread of STI.24 Here we show that the frequency of having only sexual partners from
participants’ own ethnicity was higher than expected if partners would have been selected
regardless of ethnicity (i.e. assortative mixing). On the other hand, almost half of the study
population reported ethnic sexual mixing, which showed that bridges between the ethnic
groups do exist. Ethnic sexual mixing differed per ethnic group and was highest for mixed
race individuals followed by Javanese and Creoles. Nevertheless, this sexual mixing was not
associated with chlamydia, which is in line with a study among immigrants in the Netherlands
where ethnic sexual mixing was not associated with self-reported STI.25 One study on ethnic
mixing of Surinamese immigrants in the Netherlands showed that Hindu-Surinamese
individuals were more likely to mix than Afro-Surinamese individuals,26 which is in contrast
to our data derived from Suriname. In the Dutch study among Surinamese migrants,
eight times more Afro-Surinamese individuals were included than Hindu-Surinamese
individuals.26 Population size and the size of the ethnic group are of importance for the
likelihood of ethnic sexual mixing and might explain the difference between the studies.
Hindu-Surinamese migrants in the Netherlands might be more likely to meet individuals
from different ethnicities, and therefore more likely engage in ethnic sexual mixing.
Besides the epidemiological characterization of ethnic sexual mixing, we used MLST
typing to identify pathogen-associated networks among participants with chlamydia.
Previously ompA genovar typing has been used27 but MLST was found to be more
discriminative and provides more solid proof of independent circulation.27 Furthermore
MLST is less affected by intragenic recombination of C. trachomatis, than typing based on
only the ompA gene is.28 MLST revealed that all major ethnic groups were represented
in all three clusters of C. trachomatis strains, which suggests that these strains circulate
endemically among all ethnic groups. Although the distribution of clusters within each
group varied, clear separate networks for C. trachomatis transmission by ethnicity could
101
not be identified which can be explained by ethnic sexual mixing between the groups.
The typing results were in agreement with the epidemiological data. In contrast, studies
comparing non-mixing populations (heterosexuals and MSM) showed hardly any overlap
in chlamydial strains.16,17 In our study we could not distinguish separate networks between
MSM and heterosexuals as only 7 MSM were included of whom only one had chlamydia and
the provided sample could not be typed by MLST.
By checking the MLST profiles in the international C. trachomatis database, 32 (49%)
novel strains were found. This database has existed since 2007 and comprises 459 profiles
to date. It is most likely that many novel strains will be found. The database will expand and
include an increasingly wide variety of C. trachomatis strains from different parts of the
world. Combining the molecular data with epidemiological characteristics will provide more
insight into global C. trachomatis transmission networks.
Several potential limitations should be mentioned. In our study differences in
prevalence of chlamydia between ethnic groups were found, but we were not able to
elucidate why these differences exist between ethnic groups. Therefore, additional risk
behavior data are necessary. For example, concurrency is an important factor in the spread
of HIV/STI29 and is not uncommon among Surinamese individuals.26,30,31 Also, we did
not have information on other partner characteristics besides ethnic group such as age,
type of partner (regular or casual), or condom use with different partners. Mathematical
transmission models could be of added value to better identify sexual networks. Participants
were interviewed face to face by a research nurse. Therefore, they may have given socially
desirable answers and response bias may have occurred. Such bias might have occurred
for variables such as condom use and number of sexual partners and would probably have
resulted in an underestimation of risk behavior. Furthermore, ethnicity of the partner was
self-reported and misclassification cannot be excluded.
In conclusion, the prevalence of chlamydia in Suriname is very high, with 10% in a
low-risk population and up to 23% in a high-risk population. This prevalence is high overall
in all ethnic groups (>7%), but higher in the Creole and Javanese groups compared with
the Hindustani population. Although a high degree of sexual mixing occurs between the
ethnic groups, having sex with a partner of the same ethnic group was more common than
would be expected if partner selection occurred regardless of ethnic group. Nevertheless,
based on the MLST typing analysis there is no sound evidence for separate ethnic sexual
transmission networks and differences in prevalence of chlamydia between ethnic groups
could not be explained by ethnic sexual mixing patterns. Prevention activities must rather be
targeted at the whole community at risk, with a focus on the younger age groups. Adequate
testing facilities and subsequent treatment are needed to reduce the disease burden of
chlamydia in Suriname.
102
Chapter 4.1
Acknowledgments
The authors would like to thank all nurses and laboratory technicians of the Dermatological
Service and the Lobi Foundation for data collection; Ronald Geskus for critically reading the
manuscript, and Claire Buswell for editing the final manuscript.
Author contributions
Conceived and designed the experiments: JvdH LS SB HdV. Performed the experiments:
JvdH RB AG LS. Analyzed the data: JvdH RB MSvdL SB HdV. Contributed reagents/materials/
analysis tools: LS AG SB HdV. Wrote the paper: JvdH RB AG LS SB MSvdL HdV.
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105
106
The role of Surinamese migrants
in the transmission of
Chlamydia trachomatis
between Paramaribo, Suriname
and Amsterdam, the Netherlands
Reinier J. M. Bom1*
Jannie J. van der Helm2,3*
Sylvia M. Bruisten1,4
PLoS One. 2013 Nov 13;8(11):e77977
*
Both authors contributed equally to this work
1
Public Health Laboratory, Cluster Infectious Diseases, Public Health Service of Amsterdam, Amsterdam,
The Netherlands, 2 Department of Research, Cluster Infectious Diseases, Public Health Service of
Amsterdam, Amsterdam, The Netherlands, 3 STI Outpatient Clinic, Cluster Infectious Diseases, Public
Health Service of Amsterdam, Amsterdam, The Netherlands, 4Department of Experimental Virology,
Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands, 5Lobi Foundation,
Paramaribo, Suriname, 6Dermatological Service, Ministry of Health, Paramaribo, Suriname,
7
Department of Dermatology, Academic Medical Center, University of Amsterdam, Amsterdam, The
Netherlands, 8 Center for Infections and Immunity Amsterdam (CINIMA), Academic Medical Center,
University of Amsterdam, Amsterdam, The Netherlands, 9 Center for Infectious Disease Control,
National Institute of Public Health and the Environment, Bilthoven, The Netherlands
Abstract
Background: The large Surinamese migrant population in the Netherlands is a major risk
group for urogenital Chlamydia trachomatis infection. Suriname, a former Dutch colony, also
has a high prevalence of C. trachomatis. Surinamese migrants travel extensively between the
Netherlands and Suriname. Our objective was to assess whether the Surinamese migrants
in the Netherlands form a bridge population facilitating transmission of C. trachomatis
between Suriname and the Netherlands. If so, joint prevention campaigns involving both
countries might be required.
Methods: Between March 2008 and July 2010, participants were recruited at clinics in
Paramaribo, Suriname and in Amsterdam, the Netherlands. Participants were grouped
as native Surinamese, native Dutch, Surinamese migrant, Dutch migrant, or Other, based
on country of residence and country of birth of the participant and of their parents. Risk
behavior, such as sexual mixing between ethnic groups, was recorded and C. trachomatis
positive samples were typed through multilocus sequence typing (MLST).
Results: A minimum spanning tree of samples from 426 participants showed four MLST
clusters. The MLST strain distribution of Surinamese migrants differed significantly from
both the native Surinamese and Dutch populations, but was not an intermediate state
between these two populations. Sexual mixing between the Surinamese migrants and
the Dutch and Surinamese natives occurred frequently. Yet, the MLST cluster distribution
did not differ significantly between participants who mixed and those who did not. Sexual
mixing occurred between Surinamese migrants in Amsterdam and the native populations of
Suriname and the Netherlands. These migrants, however, did not seem to form an effective
bridge population for C. trachomatis transmission between the native populations.
Conclusion: Although our data do not seem to justify the need for joint campaigns to reduce
the transmission of C. trachomatis strains between both countries, intensified preventive
campaigns to decrease the C. trachomatis burden are required, both in Suriname and in the
Netherlands.
108
Chapter 4.2
Introduction
C
hlamydia trachomatis infections occur endemically among the general population of the
Netherlands, but most infections are found in defined risk groups, such as adolescents
and men who have sex with men (MSM).1 In addition, some ethnic minority groups are
affected disproportionally by C. trachomatis infections.2 Migrants from Suriname constitute
one of the largest ethnic minority groups in the Netherlands, and the highest prevalence
of C. trachomatis has been reported in this population. In 2011, the C. trachomatis
prevalence among clients of the Dutch sexually transmitted infection (STI) clinics was 18%
for heterosexual Surinamese migrants compared with 11% for native Dutch heterosexuals.3
Suriname is a former colony of the Netherlands in the Caribbean region. It is a multi-ethnic
society consisting of Creoles, Maroons, Hindustani, Javanese, Chinese, Caucasians, and
indigenous Amerindians, as well as a mixed race population. Although considered an upper
middle-income country by World Bank standards, Suriname is an emerging economy in
which reliable diagnostics to detect C. trachomatis infections and other STIs are still lacking
for the majority of its inhabitants.4 The prevalence of C. trachomatis infections is high; one
study demonstrated around 10% prevalence in a low-risk population (clients of a birth
control clinic) and 21% in a high-risk population (clients of an STI clinic).5
Since the independence of Suriname in 1975, a large proportion of the Surinamese
population migrated to the Netherlands and today almost as many people of Surinamese
origin live in the Netherlands as in Suriname itself. Amsterdam has the largest number of
Surinamese inhabitants outside of Suriname. As a result, traveling between the two countries
is common. A study in 2008 found that more than half of the population of Surinamese
descent living in the Netherlands had visited friends and relatives in Suriname during the
preceding five years.6 Of these travelers, 9% reported unprotected sexual contact in both
countries.2
Discordant sexual mixing is defined as sex between partners from two different
groups (e.g. with different age or ethnicity).7 A group characterized by a high degree of sexual
mixing can act as a bridge population for STI transmission between seemingly unrelated
groups. Surinamese migrants living in the Netherlands may thus be a bridge population for
STI transmission between the native populations in Suriname and the Netherlands.6 If this
is the case, it has implications for the design of effective preventive measures to reduce STI
transmission. Joint campaigns involving both countries and a focus on travelers might be
needed to reduce overall STI prevalence and to increase the impact of prevention.
We hypothesized that Surinamese migrants constitute a bridge population for the
transmission of C. trachomatis between Suriname and the Netherlands. If this were the
case, this would be reflected by:
109
1) A high degree of sexual mixing with native Surinamese and native Dutch partners, and
2) A distribution of C. trachomatis genotypes that is more similar to the native Surinamese
or native Dutch population among the Surinamese migrants who report sexual mixing with
the native Surinamese or native Dutch population respectively, compared with those that
do not report sexual mixing.
We collected C. trachomatis positive urogenital samples in the two capital
cities: Paramaribo, Suriname; and Amsterdam, the Netherlands, and genotyped the C.
trachomatis strains with a high-resolution multilocus sequence typing (MLST) method.8,9
This method was specifically designed to have a discriminatory power as required for
molecular epidemiological analyses. It was epidemiologically validated on clinical samples
to differentiate C. trachomatis strains on a population level in a previous study.8 These
MLST data were used to compose a minimum spanning tree and elucidate C. trachomatis
strain clusters. In a previous study, this approach successfully demonstrated the distinct
transmission of C. trachomatis strains in MSM and heterosexuals.9 In this study, the
distribution of clusters was related to predefined risk characteristics like sexual mixing
between native and migrant populations in the two countries.
Materials and Methods
Study sites and population
Participants were recruited at two sites in Paramaribo, Suriname and at one site in
Amsterdam, the Netherlands:
1) The Dermatological Service in Paramaribo, an integrated outpatient clinic that offers freeof-charge examination and treatment of STIs and infectious skin diseases such as leprosy
and leishmaniasis. Recruitment took place between March 2008 and July 2010.
2) The Lobi Foundation, a center for birth control and sexual health in Paramaribo.
Recruitment took place between July 2009 and April 2010.
3) The STI Outpatient Clinic of the Public Health Service of Amsterdam, which is a low
threshold clinic serving over 30,000 clients annually. Individuals were prioritized based on
a short questionnaire to estimate the risk of having an STI.10 Those considered at high-risk
of an STI were eligible to participate. Recruitment took place between November 2009 and
May 2010.
Exclusion criteria were: age younger than 18 years, antibiotic use in the previous 7
days, men having sex with men in the past 6 months, and previous participation in this
study. After written informed consent, participants were given a unique code to participate
anonymously. Participants were interviewed about demographic characteristics, including
110
Chapter 4.2
place of birth, place of birth of both parents, ethnicity of sexual partners, number of sexual
partners, and place of residence of their sexual partners. The ethics committees of the
Ministry of Health of the Republic of Suriname (VG010-2007) and the Academic Medical
Center, University of Amsterdam, the Netherlands (MEC07/127) approved the study. Part of
the data collected in the Netherlands has been described previously by Bom et al. (2013).9
Part of the data collected in Suriname has been described previously by Van der Helm et al.
(2012).5
Sample collection
In Paramaribo, urine samples from men and nurse-collected vaginal swabs were obtained,
shipped and tested with the Aptima Chlamydia assay for the detection of C. trachomatis
rRNA (Hologic Gen-Probe Inc., San Diego, USA) at the Public Health Laboratory in Amsterdam.
The urine samples were tested within 40 days, and the vaginal swabs within 50 days after
collection. A more detailed description has been reported in a previous study.5 In Amsterdam,
urine samples from men and nurse-collected vaginal or cervical swabs were tested with the
Aptima assay at the Public Health Laboratory in Amsterdam. For each individual, only one
C. trachomatis positive sample was selected. For female participants, vaginal samples were
preferred; if vaginal samples were not available, cervical samples were selected. A more
detailed description has been reported in a previous study.9
MLST
Nucleic acids from C. trachomatis-positive clinical samples were extracted and tested for
the presence of chlamydial DNA.11,12 DNA isolates were amplified by a nested PCR and
sequenced for the regions ompA, CT046 (hctB), CT058, CT144, CT172, and CT682 (pbpB).8,9
The sequences were checked against the Chlamydia trachomatis MLST database (mlstdb.
bmc.uu.se). Only samples of which all 6 loci were successfully amplified, sequenced, and
identified, and therefore had obtained a full sequence type (ST) or MLST profile, were
included in the analyses. As ompA is part of the MLST scheme, genovars could be assigned
for all included samples. A minimum spanning tree was generated using MLST profiles.
As the number of STs was too large to be used in statistical analyses, cluster analysis was
performed, allowing single locus variance using BioNumerics 7.0 (Applied Maths, SintMartens-Latem, Belgium). A cluster was defined as a group of STs differing by not more
than 1 locus from another ST within that group. Only clusters of at least 25 samples were
included in the cluster analysis as these clusters were large enough for statistical analyses.
The remaining samples were compiled in a residual group, which was used in the analyses
as an additional cluster.
111
Participants were classified into 5 groups based on country of residence of the participant,
and country of birth of the participant, and of his or her parents (Figure 1):
1) Native Surinamese group: Participants residing in Suriname; neither the participant, nor
the parents were born in the Netherlands, and at least one was born in Suriname;
2) Native Dutch group: Participants residing in the Netherlands; neither the participant, nor
the parents were born in Suriname, and at least one was born in the Netherlands;
3) Surinamese Migrant group: Participants residing in the Netherlands; the participant and/
or his or her parents (one or both) were born in Suriname;
4) Dutch Migrant group: Participants residing in Suriname; the participant and/or his or her
parents (one or both) were born in the Netherlands;
5) Other groups: A participant neither residing in Suriname nor in the Netherlands; or
neither the participant nor his or her parents were born in Suriname or the Netherlands.
Sexual partners in the past 12 months were classified into three groups based on
country of residence of the sexual partner, and the ethnicity of the sexual partner, as
perceived by the participant:
1) Native Surinamese partner: sexual partner residing in Suriname and of perceived
Surinamese ethnicity;
2) Native Dutch partner: sexual partner residing in the Netherlands and of perceived Dutch
ethnicity;
3) Surinamese Migrant partner: sexual partner residing in the Netherlands and of perceived
Surinamese ethnicity.
A partner of perceived Surinamese ethnicity was defined as a partner with a Creole,
Hindustani, Javanese, Chinese, Maroon, Amerindian, or mixed race ethnicity. A partner of
perceived Dutch ethnicity was defined as a partner with a Caucasian ethnicity. Differences
between clusters were tested using Pearson’s χ2 tests for categorical data. Fisher’s exact
tests were used when the expected cell count was less than one. For continuous data, MannWhitney U tests and Kruskal-Wallis tests were used. A p-value of <0.05 was considered
statistically significant. Analyses were performed with SPSS package version 19.0 (SPSS Inc.,
Chicago, IL). To test whether the distribution of C. trachomatis clusters found within the
Surinamese migrant population was an intermediate state between the distributions of
the native Surinamese and native Dutch populations, a range of hypothetical intermediate
cluster distributions was calculated. The proportion of every cluster within a hypothetical
intermediate state (Phyp_i) was calculated by:
Phyp- i =(100%—x)PSUR-i +xPNL - i
where pSUR_i is the proportion of cluster i in the native Surinamese population, pNL_i is
112
Chapter 4.2
the proportion of cluster i in the native Dutch population and x ranges from 0% to 100%
with a step size of 1%. With x=0%, the hypothetical distribution would be identical to the
distribution found in the native Surinamese population, whereas x=100% would result in
a distribution identical to the one found among the native Dutch. To test whether these
hypothetical intermediate distributions differed significantly from the distribution found
among the Surinamese migrants, the proportions of each cluster were multiplied by the
total number of Surinamese migrants and compared to the actual distribution of clusters
found among the Surinamese migrants using Pearson’s χ2 tests.
Results
Study population and specimens
A total of 415 men and 1093 women participated in Paramaribo and 449 men and 1051
women participated in Amsterdam. Of those, 95 (23%) men and 129 (12%) women in
Paramaribo and 100 (22%) men and 204 (19%) women in Amsterdam tested positive for
Figure 1. Algorithm for classification of participants into five groups (‘Native Surinamese,’ ‘Native Dutch,’ ‘Surinamese Migrant,’ ‘Dutch Migrant,’ and ‘Other’) based on country of residence of the participant and country
of birth of the participant and his or her parents. Data were missing for 6 of the 426 participants, therefore they
were not included in the analyses. The category ‘Other’ was derived from three different routes in the algorithm
(n = 33).
113
C. trachomatis. A total of 508 (96%) C. trachomatis positive samples were available for
further testing, of which 219 originated from Paramaribo and 289 from Amsterdam. In 450
samples (89%), the presence of genomic DNA could be demonstrated by qPCR. Of these
450 samples, 426 (95%) could be completely typed by MLST, of which 170 originated from
Paramaribo and 256 originated from Amsterdam.
Table 1 shows general characteristics of the 426 C. trachomatis positive participants,
with a complete MLST profile by city. The median age of the participants in Paramaribo
was higher (25 years; interquartile range (IQR): 22–30 years) compared with those from
Amsterdam (23 years; IQR: 21–26 years; p<0.001). In addition, participants from Paramaribo
usually had received less education (p<0.001) and reported fewer sexual partners (p=0.011).
Table 1. General characteristics of Chlamydia trachomatis -positive men and women included in Paramaribo, Suriname and
Amsterdam, the Netherlands, 2008–10.
Paramaribo (n = 170)
n (% )
Gender
Amsterdam (n = 256)
p
n (% )
Male
65 (38)
86 (34)
Fem ale
105 (62)
170 (66)
0.33
Age in years
Median (mean; IQR)
25 (27.0; 22–30)
23 (24.9; 21–26)
<0.001
Education a
L ow
68 (41)
2 (1)
<0.001
Med ium
76 (46)
120 (48)
H ig h
21 (13)
130 (52)
Native Surinam ese
155 (92)
-
Native D utch
-
166 (66)
D utch m ig rant
2 (1)
-
Surin am ese m ig rant
4 (2)
60 (24)
Other
7 (4)
26 (10)
Number of sexual partners in the past
12 months c
Median (mean; IQR)
1 (1.4; 1–2)
1 (2.0; 1–2)
0.011
ompA genovar
B
3 (2)
2 (1)
0.59
D
31 (18)
29 (11)
E
55 (32)
101 (39)
F
33 (19)
52 (20)
G
9 (5)
16 (6)
H
2 (1)
2 (1)
I
22 (13)
31 (12)
J
10 (6)
13 (5)
K
5 (3)
10 (4)
C luster 1
43 (25)
62 (24)
C luster 2
9 (5)
67 (26)
C luster 3
37 (22)
25 (10)
C luster 4
27 (16)
26 (10)
Resid ual g roup
54 (32)
76 (30)
Ethnic group b
MLST Cluster
<0.001
<0.001
aData were missing for 5 participants recruited in Paramaribo and 4 in Amsterdam.
bData were missing for 2 participants recruited in Paramaribo and 4 in Amsterdam.
cData were missing for 5 participants recruited in Paramaribo and 1 in Amsterdam.
IQR: interquartile range; MLST: multilocus sequence typing.
114
Chapter 4.2
Genovar distribution
As ompA is part of the MLST scheme, genovars could be assigned for all typed samples. In
both cities we found 9 different genovars, being B, and D through K. The genovar distribution
found in Paramaribo and Amsterdam was not significantly different (p=0.59) with genovars
D, E, F and I being most common (Table 1).
MLST results
Among the 170 MLST profiles from Paramaribo there were 65 different STs (Table S1). Of
these STs, 29 had multiple representatives (n=2–28) and 36 were found in only a single
isolate (singleton). Among the 256 Amsterdam samples, 124 different STs were found (Table
S1). Multiple representatives were seen for 34 STs (n=2–28) and 90 singletons were found.
In the total population of the 2 cities, we identified 166 STs (n=1–46) of which 106 were
singletons.
From the MLST profiles of these 426 samples, a minimum spanning tree was
generated (Figure 2, Figure 3). Within this minimum spanning tree, identical samples or
samples differing by one locus were grouped together. If these groups contained 25 or more
samples, they were considered a cluster and this is indicated in the minimum spanning tree
with a halo. A cluster supposedly represents one C. trachomatis strain type. In the minimum
spanning tree generated from the 426 samples, we could identify four clusters (n=53–105).
Cluster 1 included 105 individuals and consisted mainly of genovar F samples (77%), but also
of genovar D (19%) and J (4%). Cluster 2 (n=76) and cluster 3 (n=62) included solely genovar
E samples. Cluster 4 (n=53) consisted predominantly of genovar I (89%), but also of genovar
J (11%). Among the residual samples (n=130), all genovars were present, but genovars D
(31%), G (19%), E (14%), K (12%) and J (10%) were most common.
In contrast to the genovar distribution, the distribution of samples in the MLST clusters
was strongly associated with the city of sampling (p<0.001, Table 1; Figure 2). Overall, 60%
of samples were from Amsterdam, but 88% of samples in cluster 2 were from Amsterdam,
while 40% of samples in cluster 3 were from Amsterdam. No important deviations as
expected from the overall sample distribution were found for cluster 1 (with 59% of the
samples originating from Amsterdam), cluster 4 (with 49%), and the residual group (with
58%).
Demographic characteristics of the clusters
Demographic characteristics were compared for the four large clusters and the residual group.
Gender, age, and number of sexual partners in the past 12 months did not differ significantly
between the clusters. However, significant differences in education (p=0.003) and ethnic
groups (p<0.001) were observed between the clusters (Table S2). The participants in cluster
2 had received more education, whereas participants in clusters 3 and 4 had received less
115
Figure 2. Minimum spanning tree of 426 Chlamydia trachomatis-positive samples from Amsterdam and
Paramaribo, 2008–2010. Each circle represents one MLST type. Size of the circles is proportional to the number
of identical MLST profiles. Bold lines connect types that differ by one single locus. Halos indicate clusters. Colors
indicate city of sampling; green: samples from Paramaribo, Suriname (n = 170) and orange: samples from
Amsterdam, the Netherlands (n = 256).
Figure 3. Minimum spanning tree of 426 Chlamydia trachomatis-positive samples from Amsterdam and
Paramaribo, 2008–2010. Each circle represents one MLST type. Size of the circles is proportional to the number
of identical MLST profiles. Bold lines connect types that differ by one single locus. Halos indicate clusters. Colors
indicate ethnic group; green: native Surinamese participants (n = 155); orange: native Dutch participants (n = 166);
purple: Surinamese migrant participants (n = 64); and white: Dutch migrant participants (n = 2), other participants
(n = 33) and participants with missing data (n = 6).
116
Chapter 4.2
Figure 4. Venn diagrams of sexual mixing with native Surinamese partners (green circle), native Dutch partners
(orange circle) and Surinamese migrant partners (purple circle) in the past 12 months. A. Native Surinamese
participants (n = 153). B. Surinamese migrant participants (n = 60). C. Native Dutch participants (n = 150). Partner
data were missing for 2 native Surinamese participants, 4 Surinamese migrant participants, and 16 native Dutch
participants.
Figure 5. Distribution of the Chlamydia trachomatis clusters per ethnic group. Colors indicate the different
clusters; dark green: cluster 1; light green: cluster 2; yellow: cluster 3; red: cluster 4; and purple: the residual
group. These distribution of C. trachomatis strains differed significantly between the groups: native Surinamese
participants – Surinamese migrant participants: p = 0.002; and Surinamese migrant participants – native Dutch
participants: p<0.001.
education; these differences are largely due to the city of origin of the participants. Clusters
3 and 4 had more native Surinamese participants than the other clusters and cluster 2
had more native Dutch participants. Cluster 4 had more Surinamese migrant participants
compared with the other clusters.
Because the distribution of C. trachomatis strains differed between the participants
117
recruited in Amsterdam and Paramaribo, we also analyzed the data stratified by city of
sampling (Table S3). In the analysis for the samples from Paramaribo, no significant differences were found between the clusters and any of the variables tested (gender, age,
education, number of sexual partners, or ethnic group). For the Amsterdam samples, no
significant differences were found between the clusters and gender, age, education, or
number of sexual partners, but a very significant difference was found for ethnic group
(p<0.001): 73% of samples in cluster 4 were from migrant Surinamese participants, while
this group represented only 24% of the participants from Amsterdam (Figure 3, Table S3).
When we analyzed the data stratified for three main ethnic groups, no significant differences
were found between the clusters and any of the variables tested for the native Surinamese,
the native Dutch, or the Surinamese migrants (Table S4).
Sexual mixing between the ethnic groups
We hypothesized that Surinamese migrants constituted a bridge population for the
transmission of C. trachomatis between Suriname and the Netherlands. To investigate
whether this pattern of transmission of C. trachomatis strains occurred, we investigated
the degree of sexual mixing between the three main ethnic groups, i.e. native Surinamese
participants (n=155), Surinamese migrant participants (n=64), and native Dutch participants
(n=166; Figure 1). In this analysis, we excluded the Dutch migrant participants (n=2) and the
other participants (n=33), due to their low numbers and limited relevance in the model. In
addition, 2 native Surinamese participants, 4 Surinamese migrant participants, and 16 native
Dutch participants were excluded, as data regarding their sexual partners were missing or
incomplete.
Among the Surinamese migrant participants, we found that 13% (n=8/60) reported
having had sex with a native Surinamese partner in the past 12 months, and 13% (n=20/153)
of the native Surinamese participants reported having had sex with a Surinamese migrant
partner (Figure 4). Among Surinamese migrant participants, 30% (n=18/60) reported having
had sex with a native Dutch partner in the past 12 months, and 27% (n=40/150) of the native
Dutch participants reported having had sex with a Surinamese migrant partner. Among
the native Surinamese participants we found that 3% (n=4/153) reported having had sex
with a native Dutch partner in the past 12 months, and 1% (n=2/150) of the native Dutch
participants reported having had sex with a native Surinamese partner.
Clear differences were found in the distribution of the clusters, including the residual
group, between the three main ethnic groups: native Surinamese, Surinamese migrants and
native Dutch (Figure 5). Compared with the native Surinamese participants, samples from
the Surinamese migrant participants more often belonged to clusters 2 and 4, and less often
to cluster 3 and the residual group (p=0.002). Compared with the native Dutch participants,
samples from the Surinamese migrant participants more often belonged to cluster 4 and
118
Chapter 4.2
less often to cluster 2 and the residual group (p<0.001). In addition, the distribution of the
clusters found among the Surinamese migrants differed significantly from any intermediate
state between the distribution found among the native Surinamese and native Dutch (figure
S1).
The distribution of C. trachomatis strains found among the Surinamese migrant
participants did not differ significantly between those who reported sex with a native
Surinamese partner and those who did not (p=0.43; Table 2). In addition, no significant
differences were found in the distribution of C. trachomatis strains found among the native
Surinamese participants who reported sex with a Surinamese migrant partner and those
who did not (p=0.13). The same was observed for the Surinamese migrant participants: no
significant differences were found in C. trachomatis strain distribution between participants
who reported and those who did not report sex with native Dutch partners (p=0.66). Also
among native Dutch participants no significant differences were found in C. trachomatis
strain distribution between those who reported sex with Surinamese migrant partners and
those who did not (p=0.34).
Table 2. Sexual mixing with other ethnic groups among participants, by Chlamydia trachomatis cluster, Paramaribo, Suriname and
Amsterdam, the Netherlands, 2008–10.
Cluster 1
Cluster 2
Cluster 3
Cluster 4
n (%)
n (%)
n (%)
n (%)
Residual group
n (%)
p
Yes
5 (14)
0 (0)
3 (8)
7 (28)
5 (11)
0.13
No
32 (86)
9 (100)
33 (92)
18 (72)
41 (89)
Yes
1 (7)
0 (0)
1 (20)
3 (16)
3 (25)
No
13 (93)
10 (100)
4 (80)
16 (84)
9 (75)
Yes
4 (29)
5 (50)
1 (20)
5 (26)
3 (25)
No
10 (71)
5 (50)
4 (80)
14 (74)
9 (75)
Yes
10 (27)
10 (24)
7 (50)
1 (20)
12 (23)
No
27 (73)
31 (76)
7 (50)
4 (80)
41 (77)
Native Surinamese participants (n = 153)
Sex with Surinamese migrant partner:
Surinamese migrant participants (n = 60)
Sex with native Surinamese partner:
0.43
Surinamese migrant participants (n = 60)
Sex with native Dutch partner:
0.66
Native Dutch participants (n = 150)
Sex with Surinamese migrant partner:
0.34
Discussion
In this study, we showed differences in the distribution of C. trachomatis strains between
infected persons in Paramaribo and Amsterdam, and between Surinamese migrants and
native Dutch participants within Amsterdam using the high-resolution MLST genotyping
technique. These differences would have been largely obscured if conventional ompA typing
had been used. For example, cluster 2 infections were more prevalent in Amsterdam and
119
cluster 3 infections were more prevalent in Paramaribo, but both clusters were composed of
MLST sequence types with an identical ompA type, genovar E, which is the most prevalent
genovar type worldwide.13
We hypothesized that the Surinamese migrant population residing in the
Netherlands, who travel frequently between the two countries, acted as a bridge population
for the transmission of C. trachomatis strains between inhabitants in Suriname and the
Netherlands. We demonstrated that sexual mixing among Surinamese migrants occurred,
both with native Surinamese and with native Dutch partners (13% and 30%). Sexual mixing
between the native Dutch and native Surinamese groups occurred infrequently (1–3%).
This indicates, based on reported sexual mixing, that Surinamese migrants potentially
constituted a bridge population for STI between the Dutch and Surinamese populations.
However, the distribution of C. trachomatis strains found in the Surinamese migrant
population differed from both the native Surinamese and Dutch distributions, but was not
an intermediate state between the native groups. This is most strikingly illustrated by the
overrepresentation of Surinamese migrants in cluster 4, whereas cluster 4 strains are less
prevalent among the native Surinamese population and rare in the native Dutch population.
Therefore we conclude that limited transmission of C. trachomatis strains occurred between
the native Surinamese and Surinamese migrant populations, and between the native Dutch
and Surinamese migrant populations. In addition, when we examined the distribution of
C. trachomatis strains among the participants that reported sexual mixing and those who
did not, no significant differences could be found between the two in the distribution of C.
trachomatis clusters. Although the power to show differences between these groups was
limited, transmission patterns that could be expected were not observed. For example,
among native Dutch participants who mix with Surinamese migrants more cluster 4
strains were expected compared to those who do not mix, as these strains were highly
prevalent among the Surinamese migrant participants. However, just 5 Dutch participants
were diagnosed with a cluster 4 strain and only 1 of them reported sex with Surinamese
migrant partner past 12 months. Consequently, the high prevalence among the Surinamese
migrants compared with the native Dutch cannot be explained by sexual mixing with native
Surinamese.
In fact, the opposite may be true; both the high prevalence and the divergent
distribution of C. trachomatis strains among the Surinamese migrants might be explained by
the absence of effective sexual mixing with the native Dutch and Surinamese populations.
When subpopulations do not mix effectively, infections cannot spread to other risk
populations, and differences in prevalence are sustained.14,15 Similar patterns can be
found among African-Americans where a higher prevalence in C. trachomatis infections
is associated with socio-economic status and partnership structures.16,17 The differences
in distribution of C. trachomatis strains can be explained assuming that the chlamydial
120
Chapter 4.2
populations in communities that do not mix are more susceptible to stochastic effects.
We were able to include a large number of participants from Suriname and the
Netherlands, within a timespan of just over 2 years. Consequently we obtained an accurate
representation of C. trachomatis strains circulating in both countries. Participants completed
a questionnaire that was designed to study sexual networks, so detailed epidemiological
data were available and these could be linked to high-resolution typing results of the
pathogen. Together, these factors enabled us to study the determinants of the specific
groups for the transmission of C. trachomatis. Although the data of the participants’ ethnic
origin was precise (based on their own assessment), the data of their sexual partners was
limited to ‘perceived ethnicity’. Therefore the amount of sexual mixing between the groups
may be overreported, especially for native Dutch and Surinamese migrant partners. The
native Dutch partners were defined as a partner of a perceived Caucasian ethnicity living
in the Netherlands. Likely, this group encompasses more than only the native Dutch, as
Caucasian minorities also reside in Amsterdam. More biased are the Surinamese migrant
partners, as they were defined as a partner of a perceived Creole, Hindustani, Javanese,
Chinese, Maroon, Amerindian, or ‘mixed race’ ethnicity living in the Netherlands. Whereas
these ethnic groups are specific for native and migrant Suriname individuals, some of these
ethnicities are not distinguishable for native Dutch participants, especially the ‘mixed race’
ethnicity. In addition, native Dutch individuals might be unaware of Surinamese ethnic
groups and therefore underreport them.
Despite the limitations, these data provide a good view of the C. trachomatis strains
circulating in Suriname and the Netherlands, and the limited transmission of these strains
between the two countries. Although our data do not seem to justify the need for joint
campaigns to reduce the transmission of C. trachomatis strains between both countries,
intensified preventive campaigns to decrease the C. trachomatis burden are required,
both in Suriname and in the Netherlands. Moreover, informing travelers about the risks of
unprotected sex abroad is still relevant. In addition, the high prevalence of C. trachomatis
within the Surinamese migrant population justifies further studies into risk factors and
transmission networks of C. trachomatis within this group. This will enable more effective
tailored prevention programs to reduce the C. trachomatis burden.
Acknowledgments
We would like to thank Sahare GashiIlazi and Nadia Nassir Hajipour for their technical
assistance and expertise, Ronald Geskus for the statistical review, and Claire Buswell for
editing the manuscript.
121
Author Contributions
Conceived and designed the experiments: RJMB JJvdH SMB MFSvdL HJCdV. Performed
the experiments: RJMB JJvdH. Analyzed the data: RJMB JJvdH SMB MFSvdL. Contributed
reagents/materials/analysis tools: RJMB JJvdH SMB AWG LOAS MFSvdL HJCdV. Wrote the
paper: RJMB JJvdH SMB AWG LOAS MFSvdL HJCdV.
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123
Supporting information
Figure S1. Test for intermediacy. Depicted are the p-values of the C. trachomatis strain distribution found among the Surinamese
migrants compared with the distributions of the hypothetical intermediate states, using Pearson’s χ2 tests. These intermediate
states ranged from 100% identical to the native Surinamese distribution to 100% identical to the native Dutch distribution.
None of these intermediate states had a p-value of ≥0.05, therefore the distribution of C. trachomatis strains found among the
Surinamese migrants was not an intermediate state between the distributions found among the native Surinamese and native
Dutch populations.
Table S2. Characteristics of Chlamydia trachomatis-positive participants, by C. trachomatis cluster, from Paramaribo,
Suriname and Amsterdam, the Netherlands, 2008-10.
Gender
Male
Age in years
Female
Median (mean; IQR)
Low
a
Education
Ethnic group
b
Cluster 1
(n=105)
Cluster 2
(n=76)
Cluster 3
(n=62)
Cluster 4
(n=53)
n (%)
31 (30)
n (%)
31 (41)
n (%)
17 (27)
n (%)
26 (49)
n (%)
46 (35)
74 (70)
45 (59)
45 (73)
27 (51)
84 (65)
24 (24.6; 21-26) 24 (24.4; 21-26) 24 (26.8; 22-30) 24 (26.2; 21-29)
14 (14)
3 (4)
17 (28)
12 (23)
Residual group
(n=130)
24 (26.8; 21-29)
24 (19)
Medium
53 (51)
34 (45)
25 (41)
28 (54)
56 (45)
High
36 (35)
39 (51)
19 (31)
12 (23)
45 (36)
Native Surinamese
38 (37)
9 (12)
36 (59)
25 (47)
47 (37)
Native Dutch
40 (39)
48 (64)
16 (26)
6 (11)
56 (44)
1 (1)
0 (0)
0 (0)
0 (0)
1 (1)
15 (15)
11 (15)
5 (8)
20 (38)
13 (10)
Dutch Migrant
Surinamese Migrant
9 (9)
7 (9)
4 (7)
2 (4)
11 (9)
Other
Number of sexual partners in
Median
(mean;
IQR)
1
(1.5;
1-2)
1
(2.5;
1-2)
1
(1.3;
1-1)
1
(1.7;
1-2)
1
(1.8;
1-2)
c
the past 12 months
a
Data were missing for 2 participants in Cluster 1, 1 participant in Cluster 3, 1 participant in Cluster 4 and 5 participants in Residual group.
b
Data were missing for 2 participants in Cluster 1, 1 participant in Cluster 2, 1 participant in Cluster 3 and 2 participants in Residual group.
c
Data were missing for 1 participant in Cluster 2, 2 participants in Cluster 3 and 3 participants in Residual group.
IQR: interquartile range
124
p
0.07
0.27
0.003
<0.001
0.13
Chapter 4.2
Table S3A. Characteristics of Chlamydia trachomatis-positive participants, by C. trachomatis cluster, from Paramaribo,
Suriname, 2008-10.
Gender
a
Ethnic group
Cluster 2
(n=9)
Cluster 3
(n=37)
Cluster 4
(n=27)
Residual
group
(n=54)
n (%)
n (%)
n (%)
n (%)
n (%)
Male
15 (35)
2 (22)
10 (27)
16 (59)
22 (41)
Female
28 (65)
7 (78)
27 (73)
11 (41)
32 (59)
25 (26.7; 2231)
26 (30.1; 2530)
25 (27.5; 2331)
26 (27.5; 2133)
24 (26.2; 2128)
0.54
Low
14 (33)
2 (22)
17 (46)
12 (46)
23 (45)
0.19
27 (53)
Median (mean;
IQR)
Age in years
Education
Cluster 1
(n=43)
b
Medium
19 (45)
5 (56)
15 (41)
10 (38)
High
9 (21)
2 (22)
5 (14)
4 (15)
1 (2)
Native Surinamese
38 (90)
9 (100)
36 (97)
25 (93)
47 (89)
-
-
-
-
-
Dutch Migrant
Surinamese
Migrant
1 (2)
0 (0)
0 (0)
0 (0)
1 (2)
1 (2)
0 (0)
0 (0)
1 (4)
2 (4)
Other
Median (mean;
IQR)
2 (5)
0 (0)
1 (3)
1 (4)
3 (6)
1 (1.4; 1-1)
1 (1.4; 1-2)
1 (1.2; 1-1)
1 (1.3; 1-2)
1 (1.6; 1-2)
Native Dutch
Number of sexual partners in the past 12
months c
p
0.08
0.99
0.34
a
Data were missing for 1 participant in Cluster 1, 1 participant in Cluster 4 and 3 participants in Residual group.
b
Data were missing for 1 participant in Cluster 1 and 1 participant in Residual group.
c
Data were missing for 2 participants in Cluster 3 and 3 participants in Residual group.
Table S3B. Characteristics of Chlamydia trachomatis-positive participants, by C. trachomatis cluster, from Amsterdam,
the Netherlands, 2009-10.
Gender
Cluster 1
(n=62)
Cluster 2
(n=67)
Cluster 3
(n=25)
Cluster 4
(n=26)
Residual
group
(n=76)
n (%)
16 (26)
46 (74)
n (%)
29 (43)
38 (57)
n (%)
7 (28)
18 (72)
n (%)
10 (38)
16 (62)
n (%)
24 (32)
52 (68)
22 (23.2; 2025)
23 (23.6; 2125)
24 (25.8; 2128)
24 (24.7; 2126)
23 (27.2; 2031)
0.34
0 (0)
1 (1)
0 (0)
0 (0)
1 (1)
0.12
Medium
34 (56)
29 (43)
10 (42)
18 (69)
29 (39)
High
27 (44)
37 (55)
14 (58)
8 (31)
44 (59)
-
-
-
-
-
40 (66)
48 (73)
16 (67)
6 (23)
56 (75)
Male
Female
Age in years
Education
a
Ethnic group b
Median (mean;
IQR)
Low
Native Surinamese
Native Dutch
Dutch Migrant
Surinamese
Migrant
months c
Other
Median (mean;
IQR)
-
-
-
-
-
14 (23)
11 (17)
5 (21)
19 (73)
11 (15)
7 (11)
7 (11)
3 (13)
1 (4)
8 (11)
1 (1.5; 1-2)
1 (2.7; 1-2)
1 (1.4; 1-2)
1 (2.2; 1-2)
1 (2.0; 1-2)
p
0.26
<0.001
0.75
a
Data were missing for 1 participant in Cluster 1, 1 participant in Cluster 3 and 2 participants in Residual group.
b
Data were missing for 1 participant in Cluster 1, 1 participant in Cluster 2, 1 participant in Cluster 3 and 1 participant in Residual group.
c
Data were missing for 1 participant in Cluster 2.
125
Table S4A. Characteristics of trachomatis-positive native Surinamese participants, by C. trachomatis cluster, 2008-10.
Gender
Cluster 2
(n=9)
Cluster 3
(n=36)
Cluster 4
(n=25)
Residual
group
(n=47)
p
n (%)
13 (34)
n (%)
2 (22)
n (%)
10 (28)
n (%)
15 (60)
n (%)
19 (40)
0.09
25 (66)
7 (78)
26 (72)
10 (40)
28 (60)
26 (27.5; 2431)
26 (30.1; 2530)
26 (27.7; 2332)
26 (27.4; 2133)
24 (25.9; 2128)
0.36
Low
12 (32)
2 (22)
16 (44)
12 (50)
21 (47)
0.31
Medium
19 (50)
5 (56)
15 (42)
9 (38)
23 (51)
High
Median (mean;
IQR)
7 (18)
2 (22)
5 (14)
3 (13)
1 (2)
1 (1.4; 1-1)
1 (1.4; 1-2)
1 (1.2; 1-1)
1 (1.3; 1-2)
1 (1.6; 1-2)
Male
Age in years
Education
Cluster 1
(n=38)
a
months b
Female
Median (mean;
IQR)
0.50
a
Data were missing for 1 participant in Cluster 4 and 2 participants in Residual group.
b
Table S4B. Characteristics of trachomatis-positive native Dutch participants, by C. trachomatis cluster, 2009-10.
Cluster 1
(n=40)
Cluster 2
(n=48)
Cluster 3
(n=16)
Cluster 4
(n=6)
Residual
group
(n=56)
n (%)
9 (23)
31 (78)
n (%)
18 (38)
30 (63)
n (%)
4 (25)
12 (75)
n (%)
3 (50)
3 (50)
n (%)
18 (32)
38 (68)
22 (23.1; 2025)
-
22 (23.6; 2024)
-
24 (23.6; 2026)
-
20 (21.0; 1924)
-
24 (28.3; 2131)
-
Medium
17 (43)
18 (38)
5 (31)
5 (83)
17 (30)
High
Median (mean;
IQR)
23 (58)
30 (63)
11 (69)
1 (17)
39 (70)
1 (1.5; 1-2)
1 (2.0; 1-2)
1 (1.3; 1-2)
1 (1.8; 1-3)
1 (2.1; 1-2)
Gender
Male
Age in years
Female
Median (mean;
IQR)
Low
Education
months
p
0.47
0.07
0.12
0.47
Table S4C. Characteristics of trachomatis-positive Surinamese migrant participants, by C. trachomatis cluster, 2009-10.
Gender
Cluster 2
(n=11)
Cluster 3
(n=5)
Cluster 4
(n=20)
Residual
group
(n=13)
n (%)
6 (40)
9 (60)
n (%)
7 (64)
4 (36)
n (%)
2 (40)
3 (60)
n (%)
8 (40)
12 (60)
n (%)
7 (54)
6 (46)
21 (20.7; 1925)
23 (22.4; 2024)
25 (28.4; 2138)
25 (25.9; 2229)
23 (25.5; 1929)
0.11
0 (0)
0 (0)
0 (0)
0 (0)
2 (17)
0.38
Medium
12 (86)
7 (64)
4 (80)
13 (65)
8 (67)
High
2 (14)
4 (36)
1 (20)
7 (35)
2 (17)
1 (1.8; 1-2)
2 (1.7; 1-2)
1 (1.4; 1-2)
1 (2.3; 1-3)
1 (1.7; 1-2)
Male
Age in years
Education
Cluster 1
(n=15)
a
b
months
Female
Median (mean;
IQR)
Low
Median (mean;
IQR)
p
0.69
0.99
a
Data were missing for 1 participant in Cluster 1 and 1 participant in Residual group.
b
126
Chapter 4.2
Distinct transmission networks
of Chlamydia trachomatis
in men having sex with men
and heterosexual adults
in Amsterdam, the Netherlands
Reinier J. M. Bom1
Jannie J. van der Helm2,3
Martijn S. van Rooijen1,2,3
Titia Heijman2,3
Amy Matser2,5
Henry J. C. de Vries3,4,6
Sylvia M. Bruisten1,4
PLoS One. 2013;8(1):e53869
Public Health Laboratory, Public Health Service of Amsterdam (GGD Amsterdam), Amsterdam, The
Netherlands, 2Department of Research, Public Health Service of Amsterdam (GGD Amsterdam),
Amsterdam, The Netherlands, 3STI Outpatient Clinic, Public Health Service of Amsterdam (GGD
Amsterdam), Amsterdam, The Netherlands, 4Center for Infection and Immunology Amsterdam
(CINIMA), Academic Medical Center (AMC), University of Amsterdam, Amsterdam, The Netherlands,
5
Julius Centre for Health Sciences & Primary Care, University Medical Centre Utrecht (UMCU),
Utrecht, The Netherlands, 6Department of Dermatology, Academic Medical Center (AMC), University
of Amsterdam, Amsterdam, The Netherlands.
1
Abstract
Background: Genovar distributions of Chlamydia trachomatis based on ompA typing differ
between men who have sex with men (MSM) and heterosexuals. We investigated clonal
relationships using a high resolution typing method to characterize C. trachomatis types in
these two risk groups.
Methods: C. trachomatis positive samples were collected at the STI outpatient clinic
in Amsterdam between 2008 and 2010 and genotyped by multilocus sequence typing.
Clusters were assigned using minimum spanning trees and these were combined with
epidemiological data of the hosts.
Results: We typed 526 C. trachomatis positive samples: 270 from MSM and 256 from
heterosexuals. Eight clusters, containing 10–128 samples were identified of which 4
consisted of samples from MSM (90%–100%), with genovars D, G, J, and L2b. The other 4
clusters consisted mainly of samples from heterosexuals (87%–100%) with genovars D, E, F,
I, and J. Genetic diversity was much lower in the MSM clusters than in heterosexual clusters.
Significant differences in number of sexual partners and HIV-serostatus were observed for
MSM–associated clusters.
Conclusions: C. trachomatis transmission patterns among MSM and heterosexuals were
largely distinct. We hypothesize that these differences are due to sexual host behavior, but
bacterial factors may play a role as well.
128
Chapter 4.3
Introduction
Chlamydia trachomatis propagates as an obligate intracellular pathogen that is easily
transmitted sexually and often causes asymptomatic infections. C. trachomatis is endemic
in the general population, but the majority of infections occur within transmission networks
of specific risk groups, such as heterosexual adolescents, young adults, and men who have
sex with men (MSM).1 Low resolution typing methods, based on the ompA gene, showed
that multiple genovars circulate. Three genovars (D, E, and F) comprise about 70% of the
infections among heterosexuals, and the distribution of genovars appears to be stable over
time and independent of clinical symptoms and geography.2-6 The distribution among MSM
appears to be different; genovars D, G, and J comprise about 85% of C. trachomatis infections
among MSM according to a limited number of studies.5,7 Recently, a fourth dominant
genovar, L2b, was added to this distribution, because a lymphogranuloma venereum (LGV)
outbreak occurred among MSM in Europe, North America, and Australia.8-10
In this study, differences in circulating C. trachomatis strains between MSM and
heterosexuals were investigated using a high resolution typing method. A modified
multilocus sequence typing (MLST) technique was used, which was epidemiologically
validated on clinical samples to differentiate C. trachomatis strains on a population level.11
Using this technique, we previously found that there were differences in genetic diversity
among C. trachomatis strains from MSM and heterosexual women sampled in 3 different
countries.12 These hosts were separated in calendar time and geography however, making it
unlikely that direct exchange of Chlamydia strains had been possible. In the present study,
we focused on only one STI clinic in one city, Amsterdam, the Netherlands. Samples were
collected from both MSM and heterosexual men and women in a relatively short time frame
(2008–2010). We aimed to investigate the diversity of chlamydial genotypes, and analyzed
epidemiological characteristics of C. trachomatis MLST clusters between the risk groups.
Materials and Methods
Study site
The study was conducted among visitors of the STI outpatient clinic of the Public Health
Service of Amsterdam, the Netherlands. The low-threshold clinic offers free-of-charge
testing and treatment for STI to more than 30,000 visitors a year, of whom 29% are MSM.13
At entry, visitors are classified as high or low risk depending on reported sexual behavior.
Criteria for high-risk classification were: having STI-related physical complaints; being
notified of STI exposure by a sexual partner; having been paid for sexual contact in the
129
past 6 months; and for males, having had sex with men in the past 6 months. The highand low-risk groups are assigned to standard and short screening protocols, respectively.
An earlier study had shown that these criteria were able to identify groups with a high
prevalence of STI. Both protocols include diagnostic testing for C. trachomatis infections.13
Urine and swabs (taken from the vagina, cervix, urethra, proctum, or ulcer, depending on
sexual history and clinical symptoms) were tested for C. trachomatis upon collection, using
transcription-mediated amplification (TMA; Aptima Combo 2, Gen-Probe, San Diego, USA)
at the Public Health Laboratory.
Study population
For logistic reasons, recruitment for the 2 risk groups could not be conducted concurrently.
Therefore recruitment was done consecutively for each group with the collection periods
separated by two months. In addition, participants were only recruited from the standard
screening protocol. The first recruited group consisted of MSM at risk for STI. Inclusion
criteria were being at least 18 years old, understanding of written Dutch or English, and
having had sex with a man in the preceding 6 months. The recruitment period ran from July
2008 through August 2009. The second group consisted of male heterosexuals and females
at risk for STI. Male visitors were excluded if they had had sex with a male partner in the
preceding 6 months. Visitors had to understand written Dutch or English and be at least
18 years old. The recruitment period ran from November 2009 through May 2010. Visitors
could participate only once in this study, with one sample. For MSM, urine samples were
used or, if urine samples were not available, proctal samples were used. For heterosexual
men, only urine samples were used. For female participants, vaginal self-swab samples were
used or, if not available, cervical samples were used. Epidemiological data, such as diagnosis
at current visit and medical and sexual history, were obtained from the electronic patient
record. The study was approved by the medical ethics committee of the Academic Medical
Centre of Amsterdam, the Netherlands (MEC07/127, MEC07/181). Participants gave written
informed consent.
DNA extraction
DNA was extracted from clinical samples using 200 μL out of the 4 μL of transport medium
(Gen-Probe), containing swabs or urine that had previously been tested positive for Chlamydia
trachomatis by routine analysis (Aptima Combo 2, Gen-Probe, San Diego, USA). The medium
was added to 500 mL lysis buffer (bioMérieux, Boxtel, the Netherlands), 1 μL glycogen (20
mg/ml, Roche Diagnostics, Almere, the Netherlands). After mixing and incubation at 65�C
for 30 minutes, 700 μL ice-cold isopropanol was added. The precipitate was centrifuged for
20 minutes at 14000 rpm, washed twice with 70% ethanol, and dissolved in 50 μL 10 mM
Tris buffer (pH 8.0). DNA isolates were stored at —20�C until use. Per PCR reaction, 2 μL of
130
Chapter 4.3
DNA isolate was used.
DNA quantification
All DNA isolates were further tested with the in-house pmpH LGV qPCR for presence of
genomic DNA as described previously.7,14 For isolates that were negative or obtained a
cycling threshold (Ct) value higher than 35, DNA was re-extracted from the original samples
and requantified. For samples that were retested, the DNA isolate with the lowest cycling
threshold was selected for further typing analyses. Samples that tested repeatedly negative
or weakly positive (Ct>40) were excluded from typing analysis.
Nested PCR and sequencing of MLST regions
DNA isolates were amplified by a nested PCR for the regions ompA, CT046 (hctB), CT058,
CT144, CT172, and CT682 (pbpB) as described previously.11 There were some minor
adaptations to increase sensitivity: the primers CT1678R and pbpB2366R were replaced
by CT058IR (5’AAT CCT CCT TGG CCT CTC TT) and pbpB1OR (5’AAG AAC CTT CCA TCT CCT
GAA T). The inner PCR was performed with M13-tagged primers, identical to the standard
inner primers. This allowed sequencing using universal M13 primers for high throughput
purposes.
Data analysis
The obtained sequences were analyzed, assembled, and trimmed from their primer
sequences, using BioNumerics 6.6 (Applied Maths, Sint-Martens-Latem, Belgium). Samples
resulting in incomplete and low-quality sequences were reamplified and resequenced. The
cleaned primer-to-primer sequences were checked against an in-house library and against
the Chlamydia trachomatis MLST database (mlstdb.bmc.uu.se); each different sequence
from a region was given an allele number. Only samples of which all six alleles were
successfully amplified, sequenced, and identified, were included in the study and obtained
a full MLST profile. Samples with an incomplete MLST profile after repeated testing and
samples containing double infections were excluded from further analysis. A minimum
spanning tree was generated using MLST profiles. Cluster analysis was performed, allowing
single locus variance (SLV), using BioNumerics 6.6. Clusters containing 10 or more samples
were defined as large clusters. To investigate specific characteristics of small clusters (n≤9)
and singletons, we combined these samples into a residual group.
Participants were classified into 2 groups, MSM and heterosexuals, on the basis of their sexual
behavior. MSM were defined as those men who reported having sexual contact with men
in the preceding 6 months. The group of MSM was subdivided into men who have sex with
131
men only (MSMO) and men who have sex with both men and women (MSMW, bisexuals).
Men reporting sexual contact with women only (MSWO) in the preceding 6 months were
regarded as heterosexuals. In addition, all women were regarded as heterosexuals, as
male-to-female transmission is most likely for C. trachomatis infections among women.
Ethnicity was derived from the nationality, country of birth, and self-perceived ethnicity of
the participants. If all categories were answered Dutch/the Netherlands, participants were
classified as ‘Dutch’. If not, they were classified as ‘Other’. Differences between the 2 groups
and between clusters were tested univariately using the Pearson’s χ2 test, Fisher’s exact test,
Mann-Whitney U test, and Kruskal-Wallis test, when appropriate. A ρ-value of ≤0.05 was
considered statistically significant. Analyses were performed with SPSS package version 19.0
(SPSS Inc., Chicago, IL, USA).
The diversity within each clusters was calculated using Simpson’s index of diversity
(D). The formula used to define this index is:
D = 1—
1
N(N— 1)
s
∑ x j (x j —1)
j=1
where N is the total number of samples, and xj the number of samples belonging to the
jth sequence type and s is the number of different sequence types. Confidence intervals
(95%CI) were estimated using:
95% CI = D ± 1.96
σ2
where the standard deviation σ is given by:
4
σ =
N
2
s
∑
j=1
xj
N
3
s
∑
j=1
xj
N
2
2
Results
Study populations and samples
We enrolled 3992 participants of the STI outpatient clinic in Amsterdam. Of these, 2492
were MSM and 1500 were heterosexuals. In total, 669 participants were positive for C.
trachomatis by routine TMA testing (365 MSM and 304 hetero-sexuals). From these 669
participants, 658 C. trachomatis positive samples were available. In 566 samples (86%),
132
Chapter 4.3
Table 1. Demographic and clinical characteristics of MSM and heterosexuals with Chlamydia trachomatis infection, STI outpatient
clinic, Amsterdam, July 2008–May 2010.
Sex group
MSM (n = 270)
Heterosexuals (n = 256)
p
<0.001
MSMO
262
(97)
–
–
MSMW
8
(3)
–
–
MSWO
–
–
86
(34)
Female
–
–
170
(66)
Age in years
Median (IQR)
39
(31–45)
23
(21–27)
<0.001
Ethnicity a
Dutch
191
(72)
183
(71)
0.935
Other
75
(28)
73
(29)
Residence b
Amsterdam
210
(80)
186
(75)
Outside Amsterdam
51
(20)
61
(25)
Number of sexual partners in past 6 months c
Median (IQR)
8
(4–18)
2
(1–4)
<0.001
Notified for STI
No
221
(82)
163
(64)
<0.001
Yes
49
(18)
93
(36)
Urethra (male)
89
(33)
86
(34)
Proctum (male)
181
(67)
–
–
(66)
Source of sample
STI-related complaints
HIV d
0.161
<0.001
Cervix/Vagina
–
–
170
No
121
(45)
131
(51)
Yes
149
(55)
125
(49)
(100)
<0.001
<0.001
Negative
144
(55)
254
Positive
116
(45)
0
Negative
218
(81)
242
(95)
Positive
52
(19)
14
(5)
0.145
MSM: men who have sex with men; MSMO: men who have sex with men only; MSMW: men who have sex with men and
women; MSWO: men who have sex with women only; STI: sexually transmitted infections; IQR: interquartile range.
aData were missing for 4 MSM.
bData were missing for 9 MSM and 9 heterosexuals.
cData were missing for 6 MSM.
dData were missing for 10 MSM and 2 heterosexuals.
the genomic DNA load was sufficiently high for genotyping (for 43 samples, the second
extraction was selected). Of these samples, 526 (93%) could be completely typed by MLST
(of which 30 samples came from the second extraction).
Among the 526 participants with a full MLST profile were 270 MSM and 256
heterosexuals (Table 1). Notable differences between the 2 groups were the higher age
among MSM (p<0.001), higher reported number of sexual partners among MSM (p<0.001),
and MSM being less often notified for an STI by sexual partners (p<0.001). Almost half of the
MSM were HIV positive, versus none of the heterosexuals (p<0.001, Table 1). Coinfections
with Neisseria gonorrhoeae were significantly more common among MSM (p<0.001, Table
1).
Genovar distributions
As ompA is part of the MLST scheme, genovars could be assigned to all typed samples.
Among MSM, we found 7 different genovars: D (32%), E (4%), F (3%), G (32%), J (16%),
K (0.4%), and L2b (13%). Among heterosexuals, we found 9 different genovars: B (1%), D
133
(11%), E (39%), F (20%), G (6%), H (1%), I (12%), J (5%), and K (4%). Notable was the high
prevalence of LGV genovar L2b among MSM and genovar I among heterosexuals.
High resolution typing results
Among the 526 fully typed samples, 164 unique sequence types were found (Table S1).
Using the MLST profiles, a minimum spanning tree was generated, in which 8 large clusters
could be identified (Figure 1). These clusters ranged from 10 to 128 samples and comprised
86% of all samples. The remaining 75 samples were distributed over 28 singletons and 16
small clusters, ranging from 2 to 8 samples.
A clear separation in the minimum spanning tree was seen between samples from MSM
and heterosexuals (Figure 2). Four large clusters (clusters I to IV) consisted predominantly of
samples from MSM (90% to 100%) and were therefore named MSM-associated clusters. The
other 4 large clusters (clusters V to VIII) consisted primarily of samples from heterosexuals
(87% to 100%) and were named heterosexual-associated clusters. Of the samples from 75
participants outside the large clusters, only 2 were from MSM.
Within the 4 MSM-associated clusters we identified genovars D, G, J, L2 and L2b
(Table 2). Two clusters fully consisted of samples with an identical genovar: clusters II and
III contained only genovar D samples. Cluster IV contained genovar L2b (91%) and L2 (9%)
samples. Cluster I however consisted of genovar G samples (67%) as well as genovar J
samples (33%). The same phenomenon was seen for the heterosexual-associated clusters
(Table 2). Cluster V contained genovars F (82%), D (14%), and J (4%), while clusters VI and VII
consisted of genovar E samples and cluster VIII of genovar I samples. The remaining small
clusters and singletons contained a wide variety of genovars, with genovars G, D, J, and K
being the most prominent.
Diversity within MSM-associated clusters was low. The majority of samples in clusters
II, III, and IV belonged to a single sequence type, while most other sequence types differed
only in 1 locus from the central sequence type (D=0.38, 0.38 and 0.22, respectively; Table
2; Figure 2). Cluster I showed more variation (D=0.77), as it contained 3 dominant sequence
types; however, all but 1 of the remaining samples differed no more than 1 locus from
these sequence types. Among heterosexuals, diversity was much higher: numerous small
clusters and singletons were observed and also more variation was seen within the large
heterosexual-associated clusters (D=0.82, 0.86, 0.71 and 0.87, respectively for clusters V, VI,
VII and VIII). Although the majority of samples belonged to 1 or 2 dominant sequence types,
many more sequence type variants were present among heterosexuals and these variants
could vary in up to 3 loci from the central sequence types.
Clinical and epidemiological analysis
Only MSM-associated clusters II and III included some heterosexuals. Interestingly, men
134
Chapter 4.3
Figure 1. Minimum spanning
tree showing ompA genovar
type
of
526
Chlamydia
trachomatis-positive
samples
from MSM and heterosexuals
in Amsterdam between July
2008 and May 2010. Sizes of
the node discs are proportional
to the number of samples of
each sequence type; branches
show single locus variants (SLV);
halos indicate clusters based on
SLV; and letters indicate ompA
genovar type. The color coding
is: red, genovar D (n=115);
yellow, genovar E (n=112);
black, genovar G (n=102); green,
genovar F (n=61); blue, genovar
J (n=56); pink, genovar I (n=31);
gray, genovar L2b (n=31); brown,
genovar K (n=11); cyan, genovar
L2 (n=3); purple, genovar B
(n=2); and orange, genovar H
(n=2).
Figure 2. Minimum spanning tree
showing the sexual orientation
of the host of 526 Chlamydia
trachomatis-positive
samples
from MSM and heterosexuals
in Amsterdam between July
2008 and May 2010. Sizes of
the node discs are proportional
to the number of samples of
each sequence type; branches
show single locus variants (SLV);
halos indicate clusters based on
SLV; and letters indicate ompA
genovar type. The color coding
is: pink, men who have sex
with men only (n=262); green,
men who have sex with men
and women (n=8); and blue,
heterosexual men and women
(n=256).
135
136
Chapter 4.3
No
Notified for STI
27 (21)
Outside
Amsterdam
103 (80)
7 (3–18)
99 (79)
Amsterdam
Median (IQR)
b
Number of sexual partners in
past 6 months c
Residence
37 (29)
Other
Ethnicity a
39 (31–45)
90 (71)
Median (IQR)
Dutch
Age in years
0
0
L2b
0
0
L2
Female
0
K
MSWO
42 (33)
J
2 (2)
0
I
126 (98)
0
H
MSMW
86 (67)
G
MSMO
0
F
Sex group
0
E
0.77
(0.72–0.82)
0
D
D (95% CI)
0
B
Simpson’s diversity index
ompA genovar
61 (76)
6 (3–10)
11 (15)
64 (85)
23 (29)
57 (71)
39 (29–45)
0
3 (4)
1 (1)
76 (95)
0. 38
(0. 24–0. 52)
0
0
0
0
0
0
0
0
0
80 (100)
0
9 (90)
5 (3–15)
1 (10)
9 (90)
1 (11)
8 (89)
33 (24–42)
1 (10)
0
0
9 (90)
0.38
(0.03–0.72)
0
0
0
0
0
0
0
0
0
10 (100)
0
28 (82)
15 (10–21)
8 (25)
24 (75)
7 (21)
26 (79)
40 (35–45)
0
0
0
34 (100)
0.22
(0.04–0.39)
31 (91)
3 (9)
0
0
0
0
0
0
0
0
0
Cluster IV
(n = 34)
41 (58)
2 (2–5)
13 (19)
56 (81)
22 (31)
49 (69)
24 (21–27)
46 (65)
16 (23)
3 (4)
6 (8)
0.82
(0.74–0.91)
0
0
0
3 (4)
0
0
0
58 (82)
0
10 (14)
0
58 (75)
3 (2–5)
23 (31)
14 (54)
2 (1–3)
8 (31)
18 (69)
9 (35)
18 (24)
51 (69)
17 (65)
25 (22–28)
18 (69)
7 (27)
1 (4)
0
0.71
(0.53–0.90)
0
0
0
0
0
0
0
0
26 (100)
0
0
Cluster VII
(n = 26)
58 (76)
24 (21–28)
38 (49)
29 (38)
0
10 (13)
0.86
(0.81–0.92)
0
0
0
0
0
0
0
0
77 (100)
0
0
Cluster VI
(n = 77)
Cluster V
(n = 71)
Cluster III
(n = 10)
Cluster I
(n = 128)
Cluster II
(n = 80)
H e te r o s e x u a l -a s s o c ia te d c lu s te r s
MS M-a s s o c ia te d c lu s te r s
15 (60)
2 (1–5)
8 (33)
16 (67)
13 (52)
12 (48)
24 (21–27)
16 (64)
9 (36)
0
0
0.87
(0.80–0.94)
0
0
0
0
25 (100)
0
0
0
0
0
0
Cluster VIII
(n = 25)
55 (73)
3 (2–4)
13 (18)
59 (82)
18 (24)
57 (76)
23 (21–32)
51 (68)
22 (29)
1 (1)
1 (1)
–
0
0
11 (15)
11 (15)
6 (8)
2 (3)
16 (21)
3 (4)
9 (12)
15 (20)
2 (3)
Residual
Group
(n = 75)
–
–
pI
to IV
0.494
0.627
0.005
0.782
< 0.001 0.001
0.212
0.228
< 0.001 0.126
< 0.001 0.062
–
–
p total
to VIII+R
0.059
0.656
0.192
0.065
0.708
0.022
–
–
pV
Table 2. Demographic and clinical characteristics of participants by cluster based on MLST of Chlamydia trachomatis, STI outpatient clinic, Amsterdam, July 2008–May 2010.
137
106 (83)
22 (17)
Positive
50 (41)
Negative
73 (59)
Positive
66 (52)
Yes
Negative
62 (48)
25 (20)
No
Yes
Cluster IV
(n = 34)
14 (18)
66 (83)
28 (36)
50 (64)
37 (46)
43 (54)
19 (24)
2 (20)
8 (80)
2 (20)
8 (80)
7 (70)
3 (30)
1 (10)
6 (18)
28 (82)
28 (88)
4 (13)
24 (71)
10 (29)
6 (18)
30 (42)
8 (11)
63 (89)
2 (3)
69 (97)
29 (41)
42 (59)
6 (8)
71 (92)
5 (7)
70 (93)
41 (53)
36 (47)
19 (25)
Cluster VI
(n = 77)
1 (4)
25 (96)
0
25 (100)
11 (42)
15 (58)
12 (46)
Cluster VII
(n = 26)
Cluster V
(n = 71)
Cluster III
(n = 10)
Cluster I
(n = 128)
Cluster II
(n = 80)
H e te r o s e x u a l -a s s o c ia te d c lu s te r s
MS M-a s s o c ia te d c lu s te r s
6 (24)
19 (76)
0
25 (100)
16 (64)
9 (36)
10 (40)
Cluster VIII
(n = 25)
1 (1)
74 (99)
1 (1)
74 (99)
43 (57)
32 (43)
20 (27)
Residual
Group
(n = 75)
to IV
0.073
pI
to VIII+R
0.149
pV
0.002
0.991
0.005
< 0.001 < 0.001 0.342
0.085
p total
MLST: multilocus sequence typing; MSM: men who have sex with men; MSMO: men who have sex with men only; MSMW: men who have sex with men and women; MSWO:
men who have sex with women only; STI: sexually transmitted infections; IQR: interquartile range.
p total represents the p-value for the analyses over all clusters and the residual group; p I to IV over MSM-associated clusters, i.e. clusters I–IV and pV to VIII+R over heterosexual-associated clusters, i.e. clusters V–VIII and the residual group.
aData were missing for 1 sample from cluster I, 1 from cluster III, 1 from cluster IV and 1 from cluster VI.
bData were missing for 2 samples from cluster I, 5 from cluster II, 2 from cluster IV, 2 from cluster V, 3 from cluster VI, 1 from cluster VIII and 3 from the residual group.
cData were missing for 3 samples from cluster I and 3 from cluster II.
dData were missing for 5 samples from cluster I, 2 from cluster II, 2 from cluster IV, 2 from cluster VI and 1 from cluster VII.
HIV d
STI-related complaints
Table 2. Cont.
having sex with both men and women (MSMW) were more likely to be infected with strains
from the heterosexual-associated clusters compared to men who only had sex with women
(MSWO, p=0.001, Figure 2).
Comparing the MSM-associated clusters, significant differences were observed
in number of sexual partners (p=0.001) and HIV serostatus (p<0.001, Table 2). When we
excluded the LGV cluster (IV) from the analyses, no significant differences were found for
the 3 other MSM-associated clusters.
Comparing heterosexual-associated clusters, we observed differences for ethnicity
and being notified for STI by a sexual partner, but these were not significant. (Table 2).
Participants infected with C. trachomatis types from cluster VIII were more likely to be of
non-Dutch origin, whereas participants infected with C. trachomatis types from cluster VI
were less often notified for STI by a sexual partner. We found that participants with samples
in small clusters or with an infection that did not cluster were less likely to be coinfected
with N. gonorrhoeae.
Discussion
Using high resolution multilocus sequence typing, we identified clusters of C. trachomatis
strains representing but not coinciding with all prevailing genovars in Amsterdam. As
in previous studies, we found differences in C. trachomatis genovar distributions among
infected MSM and heterosexuals.5,15 MSM were mainly infected by genovars D, G, J, and
L2b, whereas heterosexuals were mainly infected by genovars D, E, F, and I. On a cluster
level however, we found very distinct circulating strains for the 2 sexual risk groups. Thus
MLST provided more solid proof of independent transmission and circulation, since it was
genetically more discriminating than using ompA typing alone.11,16,17 For example, 2 clusters
of MSM-associated samples were identified, all of which had a genovar D ompA type, but
these differed clearly from the heterosexual genovar D infections. The same was true for
genovar G and J, showing separate clusters for MSM and heterosexuals. Differences in
genovar distributions between the 2 sexual risk groups were described previously.2-7 This
is also in concordance with the findings of Christerson et al. (2012), describing differences
in the distribution of C. trachomatis strains between MSM and women in both Sweden and
the Netherlands.12 Therefore, we think that distinct transmission of C. trachomatis strains is
not unique for Amsterdam.
Recent full genome studies revealed that ompA is more mobile, due to recombination,
than previously thought.18 Using 5 extra genomic targets next to ompA, we were able to
show that samples with identical ompA types can belong to different clusters, even if these
138
Chapter 4.3
clusters are associated with the same risk groups, such as the genovar D clusters among
MSM and the genovar E clusters among heterosexuals (Figure 1, Figure 2, Table 2, Table
S1). The opposite also occurs as different genovars can clearly belong to the same cluster.
Among MSM, a cluster was indentified, showing a probable recombination event between
a genovar G and a genovar J type. Among heterosexuals, we identified a cluster being
largely of a genovar F type, but which recombined with a genovar J type ompA and two
distinct genovar D types. High resolution MLST is able to discern close relationships in spite
of recombination events, while ompA typing does not. Therefore it is a very useful tool
for epidemiological studies. Previously described MLST schemes use housekeeping genes
and canonical SNPs since they seek to answer evolutionary questions, such as establishing
Chlamydia relationships at the genus level.19,20 Our modified MLST scheme however, makes
use of genes that are under immune pressure or have variable repeat regions. This enables
to demonstrate detailed genetic differences between C. trachomatis strains that are involved
in transmission chains in human hosts in a short time frame of only a few years.
The thus identified genetic diversity of the MSM-associated chlamydial population
was very low, compared to that of the heterosexual-associated strains. Nearly all samples
from MSM were found in just 4 homogeneous clusters, pointing to clonal outbreaks. The
variation in types found among heterosexuals was much larger. Not only were the large
heterosexual-associated clusters more heterogeneous, there were also numerous small
clusters and singletons. These differences might be explained by host-related factors, such
as differences in transmission networks and population size, as well as by pathogen-related
factors, such as differences in tissue tropism.
Clear epidemiological differences between C. trachomatis-infected MSM and
heterosexuals were observed already at intake in Amsterdam. Infected MSM were often in
their late thirties and reported a median of 8 sexual partners in the past 6 months, whereas
infected heterosexuals were mostly in their early twenties and reported just 1 or 2 partners.
We found that exchange of strains between MSM and heterosexuals was rare, which was
supported by the inclusion of only 8 bisexual men in our study. The statistical analyses of
MSM-associated clusters revealed that a subpopulation existed, consisting primarily of
HIV-infected men with higher sexual risk behavior, in which LGV circulated.10 Men in the
3 non-LGV MSM-associated clusters however did not differ in their demographic or sexual
behavior characteristics. This suggests that the non-LGV C. trachomatis strains were not
circulating in separate subpopulations of MSM in Amsterdam. The existence of a broad
behavioral transmission network may well explain the lower diversity within chlamydial
strains found among MSM. Differences in being notified for STI and in ethnicity between
clusters associated with heterosexuals suggest the existence of subpopulations among
heterosexuals. Together with the lower number of partners for heterosexuals, this may have
led to the higher genetic diversity of the chlamydial strains. Also for other infections a clear
139
separation of pathogen types has been reported for MSM versus heterosexuals, notably for
all hepatitis viruses (HAV, HBV, and HCV) and N. gonorrhoeae.21,25
Recently, an alternative explanation for the different distributions of genotypes has
been put forward. Jeffrey et al. (2010) suggested that this difference could be explained by
pathogen- related factors, such as tissue tropism.26 For LGV, we found a clear preference for
proctal tissue, as LGV was detected in only one urine sample in this study and all other LGVinfections were found in proctal samples. Strains from the other MSM-associated clusters
clearly showed the ability to infect urethral tissue, but these strains may have adapted to
favor infection of proctal tissue over cervical tissue. This could explain why only one sample
coming from a woman was infected with an MSM-associated strain. We do not know
whether MSM-associated strains can be found in proctal samples from women, as no such
samples were available for the present study.
A weakness in our study is that the participants of this study were recruited in 2
consecutive time periods, MSM in the first and heterosexuals in the second period, but
together a rather short period of less than 24 months. This might have influenced cluster
formation, but previous studies demonstrated that the mutation rate of the C. trachomatis
genome is very low.26 In addition, sampling among MSM might have been biased towards
urethral types. As only 11 proctal samples were excluded due to the presence of a concurrent
urine sample, we assume this effect is minimal.
Another limitation is that all participants were recruited at the STI outpatient clinic,
which may have introduced bias towards higher risk behavior and may not be representative
for the general C. trachomatis-infected population. This applies to MSM in Amsterdam and
even more to heterosexuals. In addition, many patients with asymptomatic infections and
those who visited their general practitioner were obviously not included in the present
study.
Despite these limitations, we are confident that the distinct C. trachomatis
transmission patterns among MSM and heterosexuals in Amsterdam are true and reliable.
Our typing data show a more clonal character for strains circulating among MSM and
ongoing diversifying transmission of strains circulating among heterosexuals. We do not
know presently whether this is a global or a local phenomenon, although similar findings
have been found for sets of samples from Sweden, the Netherlands and the United States.12
These findings on C. trachomatis distribution and transmission patterns therefore need
to be confirmed in a more global setting by MLST typing and cluster analysis of samples
from both MSM and heterosexuals in countries where C. trachomatis infection is highly
prevalent. This would contribute to a large worldwide database (mlstdb.bmc.uu.se), and
would improve insight into the global variation found within and between C. trachomatis
strains. Finally, the effect of mixing patterns of the hosts versus pathogen-related factors on
the distribution of chlamydial strains needs to be clarified. This knowledge will contribute
140
Chapter 4.3
to a better understanding of chlamydial transmission and help to improve screening and
prevention programs.
Supporting Information
Table S1 MLST-data of the 526 samples collected at the STI outpatient clinic, Amsterdam,
July 2008–May 2010. Coding is according to the Chlamydia trachomatis MLST database
(mlstdb.bmc.uu.se). The samples are sorted by cluster and sequence type. Suplementary
Table 1 can be viewed and downloaded from www.plosone.org
Acknowledgments
We would like to thank Nadia Nassir Hajipour and Sahare Gashi-Ilazi for their technical
assistance and expertise, and Susan Landry for editing the manuscript.
Collected the data: RJMB JJvdH TH AM. Wrote the first draft of the manuscript: RJMB
MFSvdL SMB. Contributed to the writing of the manuscript: RJMB JJvdH MFSvdL MSvR TH
AM HJCdV SMB. Conceived and designed the experiments: MFSvdL HJCdV SMB. Performed
the experiments: RJMB JJvdH TH AM. Analyzed the data: RJMB JJvdH MSvR AM.
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144
5
STI test evaluations
145
146
Point-of-care test
for detection of urogenital chlamydia in women
shows low sensitivity.
A performance evaluation study
in two clinics in Suriname.
Servaas A. Morré4,5
Arjen G. C. L.Speksnijder6
PLoS One. 2012;7(2):e32122
1
STI Outpatient Clinic, Cluster Infectious Diseases, Public Health Service Amsterdam, Amsterdam, The
Netherlands, 2Dermatological Service, Ministry of Health, Paramaribo, Suriname, 3Lobi Foundation,
Paramaribo, Suriname, 4VU University Medical Center, Amsterdam, The Netherlands, 5Institute
of Public Health Genomics, Department of Genetics and Cell Biology, Research Institutes CAPHRI
and GROW, Faculty of Health, Medicine & Life Sciences, University of Maastricht, Maastricht, The
Netherlands, 6Public Health Laboratory, Cluster Infectious Diseases, Public Health Service Amsterdam,
Amsterdam, The Netherlands, 7Department of Dermatology, Academic Medical Center, University
of Amsterdam, Amsterdam, The Netherlands, 8Centre for Infections and Immunity Amsterdam,
Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands, 9Centre for
Infectious Disease Control, National Institute of Public Health and the Environment, Bilthoven, The
Netherlands.
Abstract
Background: In general, point-of-care (POC) tests for Chlamydia trachomatis (Ct) show
disappointing test performance, especially disappointing sensitivity results. However, one
study sponsored by the manufacturer (Diagnostics for the Real World) reported over 80%
sensitivity with their Chlamydia Rapid Test (CRT). We evaluated the performance of this CRT
in a non-manufacturer-sponsored trial.
Methods: Between July 2009 and February 2010, we included samples from 912 women
in both high- and low-risk clinics for sexually transmitted infections (STIs) in Paramaribo,
Suriname. Sensitivity, specificity, positive- and negative predictive values (PPV and NPV) for
CRT compared to NAAT (Aptima, Gen-Probe) were determined. Quantitative Ct load and
human cell load were determined in all CRT and/or NAAT positive samples.
Results: CRT compared to NAAT showed a sensitivity and specificity of 41.2% (95% CI,
31.9%–50.9%) and 96.4% (95% CI, 95.0%–97.5%), respectively. PPV and NPV were 59.2%
(95% CI, 47.5%–70.1%) and 92.9% (95% CI, 91.0%–94.5%), respectively. Quantitative Ct
bacterial load was 73 times higher in NAAT-positive/CRT-positive samples compared to
NAAT-positive/CRT-negative samples (p<0.001). Human cell load did not differ between
true-positive and false-negative CRT results (p=0.835). Sensitivity of CRT in samples with
low Ct load was 12.5% (95% CI, 5.2%–24.2%) and in samples with high Ct load 73.5% (95%
CI, 59.9%–84.4%).
Conclusions: The sensitivity of CRT for detecting urogenital Ct in this non-manufacturersponsored study did not meet the expectations as described previously. The CRT missed
samples with a low Ct load. Improved POC are needed as meaningful diagnostic to reduce
the disease burden of Ct.
148
Chapter 5.1
Introduction
U
rogenital chlamydia is the most prevalent, curable bacterial sexually transmitted infection
(STI) worldwide,1 with a significant public health burden, especially in young women.2
The causative bacterium, Chlamydia trachomatis (Ct) causes a high rate of asymptomatic
infections3 and is associated with adverse outcomes like infertility, ectopic pregnancy
and pelvic inflammatory disease (PID).4 To reduce transmission and late complications,
active case finding and early treatment are critical strategies. The standard diagnostics are
Nucleic Acid Amplification Tests (NAAT), but they are expensive and require sophisticated
laboratory conditions.5 This makes NAAT unsuitable for the detection of Ct for most lowresource settings.6 Therefore the World Health organization (WHO) has launched a priority
program that is designated to develop affordable and reliable point-of-care (POC) tests for
STIs that are predominant in low resource countries [http://www.who.int/ std_diagnostics].
In this program, WHO has formulated the ASSURED criteria that POC tests have to meet:
Affordable, Sensitive, Specific, User-friendly, Robust and rapid, Equipment-free, Deliverable
to those who need them.7 The POC test result should be readily available, while the patient
waits, to ensure prompt treatment. This is especially important where patient return for
treatment is low. It is estimated that a POC test of moderate sensitivity (63%) combined
with immediate treatment on-site may lead to the treatment of more infected individuals
than an ultra-sensitive and specific NAAT alone when patient return is low.8 Moreover,
counselling messages are most efficient when a diagnosis can be communicated during the
same consultation.9 These advantages are relevant for industrialized countries as well, even
if POC tests have a lower sensitivity than standard NAAT.
To date, POC tests for urogenital chlamydia show disappointing test characteristics,
especially low sensitivity. In a recent evaluation, three POC tests for urogenital chlamydia,
currently on the market, showed poor sensitivity between 12% and 17% in a non–
manufacturer-sponsored clinical study.10 In contrast, one POC test for urogenital chlamydia
(Diagnostics for the Real World, Cambridge, UK) especially developed for low-resource
countries has an asserted sensitivity of over 80%.11 A manufacturer-sponsored diagnostic
field study in the Philippines revealed sensitivities of 71% and 87% among women at high
risk and low risk for STI, respectively.12 Suriname, South America, is a low-resource country
and affordable and reliable diagnostics to detect Ct are urgently needed. Therefore, we
aimed to evaluate the performance of this promising POC test in two outpatient clinics in
Suriname, with the objective to use this test for intervention of the chlamydia epidemic.
149
Methods
Study sites and population
The study was approved by the ethical committee of the Ministry of Health of the Republic
of Suriname (VG010-2007) and the ethical committee of the Academic Medical Centre,
University of Amsterdam, the Netherlands (MEC07/127). Patients were recruited at two
sites in Paramaribo, Suriname:
1) The Dermatological Service, an integrated outpatient clinic that offers freeof-charge examination and treatment of STIs and infectious skin diseases like leprosy
and leishmaniasis. All consecutive women who visited for an STI check-up were asked to
participate in the study and were considered to be at high-risk for STI.
2) The Lobi Foundation is a center for birth control and sexual health. As women
who visit this clinic do not attend primarily to be checked for STI, these participants were
considered to be at low risk for STI.
Recruitment took place between July 2009 and February 2010. Exclusion criteria
were: use of antibiotics in the past 7 days, age younger than 18 years and previous
participation. After written informed consent, patients were given a unique code to
participate anonymously. Participants were interviewed about demographic characteristics,
including self-reported ethnicity as Suriname is a multiethnic society, with many ethnic
groups such as Creoles and Maroons (both descendants from the African diaspora due to
slave trade), Hindustani, Javanese, and Chinese (all descendants from labor immigrants),
Caucasians (descendants from Dutch farmers), indigenous Amerindian people and Mixed
race persons. Moreover, participants were asked about willingness to wait for POC test
results, although in our study participants did not receive the results from POC, and if they
used any products for vaginal hygiene like douches, herbs, or other home products, and if
so, in what frequency. Data were entered into an MS Access database.
Specimen collection and testing procedures
Nurse-collected vaginal swabs were obtained blindly for the Chlamydia Rapid Test (CRT)
(Diagnostics for the Real World (Europe), Cambridge, UK) and NAAT (Aptima, Gen-Probe,
San Diego, USA) testing using a cross-over model. This means that in the first half of the
included women the swab for the CRT was taken first and the second of the included women
NAAT was taken first. Nurses were trained to collect the swabs before routine speculum
examination was performed. A minimum period of 10 times for CRT and 10 seconds for
NAAT of contact between the tip of the swab and the vaginal wall in a rotating motion was
ensured. CRT was immediately performed according to the manufacturer’s instructions onsite in the laboratory. All technicians that performed the CRT were trained with proficiency
150
Chapter 5.1
panels as provided and instructed by the manufacturer. Technicians did not receive
information about the participant. The test results were interpreted and recorded by two
laboratory technicians separately. CRT results were defined as indeterminate when the
laboratory technicians reported discordant results or when CRT failed (i.e. control line did
not appear). The samples for NAAT testing were collected according to the manufacturer’s
instructions, and shipped to the Public Health Laboratory in Amsterdam where they were
tested within 50 days after collection. NAAT test results were communicated with the two
recruitment sites in Suriname and participants with a positive-Ct NAAT were treated with
doxycycline 100 mg bid for 7 days at Lobi Foundation and 10 days bid at the Dermatological
Service or, in case of (possible) pregnancy, with a single 1000 mg oral dose of azithromycin.
Chlamydia Rapid Test
The CRT was performed as described previously.13 Version 6.1 of the Chlamydia Rapid Test
(Professional use) (P/N 1200-20) instructions for use (C03-0008) was used. Shortly, each
swab was subjected to extraction by sequential addition of 400 ml of reagent 1, 300 ml of
reagent 2, and 100 ml of reagent 3 to the swab in a tapered sample preparation tube, with
gentle mixing between additions. The sample preparation reagents were administered with
unit dose pipettes. The extraction tube was then capped and used as a dropper to deliver 5
drops (approximately 100 ml) of the extracted sample to a tube containing the lyophilized
amplification and detection reagents. The resulting mixture was agitated gently until a clear
pink solution was obtained, after which the test strip, coated with a monoclonal antibody
to chlamydial lipopolysaccharide (LPS) and including a procedural control, was added to
the solution and allowed to stand for 25 minutes before the result was read. Each swab
was subjected to one extraction. The test strip was used in the interpretation of the result;
a clearly visible test line indicated a positive result, provided that the control line was also
visible on the test strip.
NAAT testing
For NAAT testing, the monospecific Aptima chlamydia assay for the detection of Chlamydia
trachomatis rRNA (Gen-Probe Inc., San Diego, USA) was used with the accompanying
vaginal swab specimen collection kit. The protocols described in the package inserts were
followed. Technicians performing NAAT were blinded to the results of the POC-Ct and did
not receive clinical information. This NAAT is an FDA-approved commercial test and was
used to estimate the Ct prevalence at both study sites.
Quantitation of Ct load and HLA
Quantitative Ct load was determined for samples with a discrepant test result between CRT
and NAAT, and for samples that tested positive for CRT as well as for NAAT using a real-time
151
PCR targeting the cryptic plasmid.14 Ct load was expressed as inclusion forming units (IFU)
based on defined serial dilutions of Ct cultured in human cells with over >90% infected
HeLa cells of 100 IFU to 0.001 IFU taking into account also DNA from non-viable Ct particles.
The human cell load was assessed by determination of human HLA copies in combination
with a defined serial dilution of quantified human DNA using the following primer probe
combination: HLA-F 5’-TTG-TAC-CAG-TTT-TAC-GGT-CCC-3’ HLA-R 5’- TGG-TAG-CAG-CGGTAG-AGT-TG,-3 and HLA-Probe 5’-FAM- TTC TAC GTG GAC CTG GAG AGG AAG GAG -BHQ1-3’.
By using a chlamydial and a human target, the average chlamydial/human cell ratio, and
IFU/swab were calculated.10
To evaluate the performance of CRT compared to NAAT sensitivity, specificity, positive
predictive value (PPV) and negative predictive value (NPV) were calculated using standard
methods. Specimens with indeterminate results by CRT were excluded. An independent
t-test was used to compare log-transformed Ct loads between true-positive and falsenegative CRT results. Analyses were performed with SPSS package version 19.0 (SPSS Inc.,
Chicago, IL).
The study has been reported according to the STARD checklist for the reporting of
studies of diagnostic accuracy.
Results
Study population and specimens
In total, 1019 women were asked to participate in the study, of whom 917 were included
and 102 did not meet the inclusion criteria or declined to participate (Figure 1). Five women
wereexcluded from the CRT performance evaluation due to either discrepancy in CRT result
between two lab technicians (n=3) or failure of CRT (n=2).
General characteristics of the 912 women included in the CRT performance
evaluation are shown in Table 1. Their median age was 30 years (IQR 25–36), 336 (36.9%)
were of Creole/Maroon ethnicity and 229 (25.1%) were of Hindustani ethnicity. Twenty-one
(2.3%) women reported having had sex for money or goods. Almost all women 900 (98.7%)
would wait for the CRT test result if the test were a standard offering in their clinic. Of these
women, 660 (73.3%) would be willing to wait for a maximum of half an hour to receive the
results, the other 240 (26.7%) would be willing to wait for at least an hour.
152
Chapter 5.1
1,019 women were asked to
participate in the study
Site 1
Dermatological Service
N=229
Site 2
Lobi Foundation
N=790
70 women were ineligeble of whom
9 had used antibiotics <7 days
13 were <18 years of age
48 declined
32 women were ineligeble of whom
21 had used antibiotics <7 days
9 were <18 years of age
2 declined
From 159 women swabs were
taken for CRT and NAAT
measurement
From 758 women swabs were
taken for CRT and NAAT
measurement
5 samples were excluded of which
3 due to a discrepancy in CRT
result between two laboratory
technicians
2 due to failure of CRT
159 included in
performance analysis
753 included in
performance analysis
Figure 1. Flow chart of specimen collection for the evaluation of a Chlamydia Rapid Test test as diagnostic for
urogenital chlamydia in women at two study sites in Paramaribo, Suriname, from July 2009 to February 2010.
NAAT; Aptima chlamydia single test, Genprobe (control test) CRT; Chlamydia Rapid Test, Diagnostics for the Real
World (evaluated test).
Ct prevalence and CRT performance results
Ct prevalence was 20.8% in the high-risk population (visiting the Dermatological Service)
and 9.2% in the low-risk population (visiting Lobi Foundation). Combining the results of
the two sites, the sensitivity and specificity of the CRT in identifying Ct compared to NAAT
were 41.2% (95% CI, 31.9%–50.9%) and 96.4% (95% CI, 95.0%–97.5%), respectively. PPV
of the CRT was 59.2% (95% CI, 47.5%–70.1%) and NPV was 92.9% (95% CI, 91.0%–94.5%).
Sensitivity and specificity of CRT compared to NAAT were comparable for the high-risk
population (39.4% and 94.4%) and the low-risk population (42.0% and 96.8%) (Table 2).
Quantitative load measurements
Quantitative Ct bacterial load and human HLA were assessed for the samples that showed
discrepant results for CRT and NAAT (n=89) and for samples that were CRT and NAAT positive
(n=42). Ct bacterial load could be detected in 99/131 samples and human HLA in 126/131
samples. Of the 42 samples that tested positive for CRT and NAAT, quantitative Ct bacterial
load was detected in all 42 samples and human HLA in 39 samples. Of the 60 samples that
tested CRT negative and NAAT positive, quantitative Ct bacterial load was detected in 55
samples and human HLA in all 60 samples. Of the 29 samples that tested CRT positive and
NAAT negative, quantitative Ct bacterial load was detected in 2 samples and human HLA in
27 samples (Table 3).
153
Table 1. General characteristics of the 912 women included in the evaluation of a Chlamydia Rapid Test as diagnostic for
urogenital chlamydia in women attwo study sites in Paramaribo, Suriname, from July 2009 to February 2010.
Dermatological Service
(n = 159)
Lobi Foundation
(n = 753)
Total population
(n = 912)
N (% )
N (% )
N (% )
27 (22–34)
30 (25–37)
30 (25–36)
Caucasian
5 (3.1)
6 (0.8)
11 (1.2)
Chinese
1 (0.6)
5 (0.7)
6 (0.7)
Creole/Maroon
81 (51.0)
255 (33.9)
336 (36.9)
Hindustani
17 (10.7)
212 (28.2)
229 (25.1)
Indigenous Amerindian
5 (3.1)
9 (1.2)
14 (1.5)
Javanese
10 (6.3)
137 (18.2)
147 (16.1)
Mixed race
39 (24.5)
127 (16.9)
166 (18.2)
Yes
17 (10.7)
4 (0.5)
21 (2.3)
No
140 (88.1)
735 (96.7)
875 (95.9)
Unknown
2 (1.3)
14 (1.9)
16 (1.7)
159 (100)
741 (98.4)
900 (98.7)
Half an hour
84 (52.8)
576 (77.7)
660 (73.3)
At least an hour
75 (47.2)
165 (22.3)
240 (26.7)
Dysuria
56 (35.2)
173 (23.0)
229 (25.1)
Irregular menstruation
53 (33.0)
194 (25.8)
247 (27.1)
Lower abdominal pain
72 (45.3)
302 (40.1)
374 (41.0)
Pain during intercourse
40 (25.2)
192 (25.5)
232 (25.4)
Vaginal discharge
110 (69.2)
369 (49.0)
479 (52.5)
Median age in years (IQR)
Ethnic Group
Sex for money or goods
Willing to waitfor POC-Cttest result
Maximum time these women are willing to wait
Symptoms
Use of any vaginal cleansing
Yes
80 (50.3)
228 (30.3)
308 (33.8)
No
74 (46.5)
512 (68.0)
586 (64.3)
Unknown
5 (3.1)
13 (1.7)
18 (2.0)
Frequency of cleansing among those who practice vaginal cleansing
At least once a week
43 (53.8)
110 (48.2)
153 (49.7)
Less than once a week
18 (22.5)
56 (24.6)
74 (24.0)
Unknown
19 (23.8)
62 (27.2)
81 (26.3)
IQR; interquartile range.
Table 2. Performance results of the Diagnostics for the Real World Chlamydia Rapid Test (CRT) compared to NAAT (Aptima
chlamydia single test).
Sensitivity (%), 95% CI
Specificity (%), 95% CI
PPV (%), 95% CI
NPV (%), 95% CI
41.2% (42/102), 31.9%–50.9%
96.4% (781/810),
95.0%–97.5%
59.2% (42/71),
47.5%–70.1%
92.9% (781/841),
91.0%–94.5%
Dermatological Service (n = 159)
39.4% (13/33), 24.0%–56.6%
94.4 (119/126), 89.3–97.5
65.0 (13/20), 42.7–83.2
85.6 (119/139), 79.0–90.7
Lobi Foundation (n = 753)
42.0 (29/69), 30.8–53.9
96.8 (662/684), 95.3–97.9
56.9 (29/51), 43.1–69.9
94.3 (662/702), 92.4–95.8
Total population (n = 912)
Evaluation of a CRT as diagnostic for urogenital chlamydia in women attwo study sites in Paramaribo, Suriname, from July
2009 to February 2010. PPV; positive predictive value. NPV; negative predictive value. 95% CI; 95% confidence interval.
Quantitative Ct bacterial load was 73 times higher in NAAT-positive/CRT-positive samples
(geometric mean 120 IFU) compared to NAAT-positive/CRT-negative samples (geometric
mean 1.64 IFU, p<0.001). Human DNA concentration did not differ between the true154
Chapter 5.1
positive and false-negative CRT results (p=0.835). The average chlamydial/human cell load
ratio (Ct concentration) was 60 times higher in NAAT-positive samples where CRT detected
Ct infection (geometric mean 0.32 IFU/ human cell) compared to loads that CRT did not
detect (geometric mean 0.0053 IFU/human cell, p<0.001). Quantitative HLA load was
comparable for NAAT-positive/CRT-positive samples (geometric mean 344 cells) compared
to NAAT-negative/CRT-positive samples (geometric mean 451 cells, p=0.424).
Quantitative Ct loads were comparable for women reporting symptoms like vaginal
discharge, irregular menstruation, pain during intercourse, lower abdominal pain or dysuria
and women without the specific symptom (data not shown). Women visiting the highrisk STI clinic had comparable quantitative Ct loads with those visiting the low-risk clinic
(p=0.525). Sensitivity of the CRT was comparable for those who practiced any vaginal
hygienic measures, 37.5% (95% CI, 23.6%–53.1%), compared to those who did not practice
vaginal cleansing, 43.3% (95% CI, 31.3%–56.0%). When comparing women who practice
vaginal cleansing frequently, at least once a week, with those who cleanse less than once
weekly, sensitivity of CRT yields comparable results, 39.1% (95% CI, 21.1%–59.8%) and
27.3% (95% CI, 7.5%–57.8%), respectively.
Based on the overall median Ct load, NAAT-positive samples were divided in two
groups with either a low- (range 0.006–12.5 IFU) or high-grade quantitative bacterial Ct load
(range 13.5–6470 IFU). In the low-grade bacterial load group, the CRT sensitivity was 12.5%
(95% CI, 5.2%–24.2%), whereas in the high-grade Ct load group the sensitivity was 73.5%
(95% CI, 59.9%–84.4%).
Table 3. C. trachomatis quantitative bacterial load and human cell load measurements in concordant and discordant samples with
NAAT (Aptima chlamydia single test) and the Diagnostics for the Real World Chlamydia Rapid Test (CRT).
NAAT+/CRT+(n = 42)
NAAT+/CRT-(n = 60)
Quantitative Ct load assessed
42
55
Geometric mean Ct load (IFU)
119.6
1.6
P-value
NAAT-/CRT+(n = 29)
2
< 0.001
Range (IFU)
5.57–6470
0.0061–519
0.00261 and 62.9
Quantitative human cell load
39
60
27
Geom etric m ean hum an cell load (H L A cop y)
344.0
326.7
Rang e hum an cell load (H L A cop y)
5.27–1460
7.99–1930
C oncentration C t load p er hum an cell assessed (IF U/H L A cop y)
39
55
Geom etric m ean of concentration (IF U/H L A cop y)
0.32
0.0053
Range (IFU/HLA copy)
0.0079–107.2
3.9*10-6 – 1.87
0.835
451.43
8.01–7800
2
0.001
1.5*10 -6 and 0.15
Evaluation of a CRT as diagnostic for urogenital chlamydia in women at two study sites in Paramaribo, Suriname, from July
2009 to February 2010. IFU; inclusion forming units. HLA; human leucocyte antigen gene.
Discussion
We found a disappointingly low clinical sensitivity of 42.0% and 39.4% of the CRT in lowrisk and high-risk Surinamese women, respectively, compared to the sensitivity of 86.8% in
155
low-risk women and 71% in high-risk women in the Philippines, reported earlier in a study
supported by the manufacturer.12 The discrepancy might partly be explained by the use of
a different reference test. Where we used Gen-Probe’s Aptima platform as a reference test,
in the Philippines study the Roche Amplicor (Roche Molecular Systems, Branchburg, NJ)
was used. Although current generation NAATs have comparable sensitivities, NAAT could
be more sensitive than Roche Amplicor.15 A somewhat lower sensitivity of CRT in our study
could be expected with a more sensitive control test, but this does not explain the large
difference in sensitivity found in the Philippine study and our results.
Another explanation for the lower sensitivity we found could be attributed to a
different wash-out period for antibiotic use between the two studies. We excluded women
who used antibiotics in the last 7 days, while in the Philippines study women who used
antibiotics in the previous month were excluded. Time to clearance of LPS antigen, which
is targeted by the CRT, might be shorter after antibiotic use than time to clearance of Ct
rRNA, which is targeted by NAAT.16 This could have caused the occurrence of false-positive
NAAT samples, and consequently more false-negative CRT samples could be expected. Low
sensitivity of the CRT due to inadequate collection resulting in a low sample yield could be
ruled out since the human cell load in samples with true-positive and false-negative CRT
results was comparable. The CRT had a 96.4% specificity. False-positive CRT results could
have been caused by cross reactivity with C. ptsittaci or C. pneumoniae as described in the
manufacturers manual. Yet infections with these organisms in the urogenital tract in humans
are uncommon.17,18 As a false positive chlamydia diagnosis can have serious adverse social
consequences a specificity of 96,4% is undesirable, especially in low prevalent settings. The
CRT in our study had a few modifications compared to the study in the Philippines. We
used unit dose pipettes instead of unit dose vials. Also, the nitrocellulose membrane was
changed by the manufacturer and according to the manual, only one dipstick had to be
used to interpret the results. However, when a test is renewed one might expect at least
comparable diagnostic characteristics compared to the previous test.
In the CRT evaluation study performed in the Philippines, the Ct prevalence was
6.3% in the low-risk group (women visiting an obstetrics-gynaecology clinic) and 17.9 to
32% in the high-risk group (female sex workers), which compares well with the prevalences
found in our study, 9.2% and 20.8% respectively. The sensitivity figures found in our study
were comparable for low-risk and high-risk women, 42.0% and 39.4% respectively. Quite
surprisingly, in the Philippines study a much lower sensitivity was found in the high-risk
group compared to the low-risk group. The authors explain this finding as a result of the use
of vaginal creams and other feminine hygiene products, which can interfere with the CRT.
In our study, the sensitivity of CRT was comparable for women who practiced any vaginal
cleansing and those who did not.
Although we consider the population recruited at Lobi Foundation a low risk group,
156
Chapter 5.1
with a prevalence of 9.2% this population would be considered high risk in many settings.
Yet, with a prevalence of 20.8% as found at the Dermatological Service, the difference in
prevalence between the two study sites is substantial.
The sensitivity of CRT is higher in samples with a high bacterial load. The clinical
relevance of organism load is still debated, but it is suggested that infections with high
organism loads are more likely to lead to cervicitis or PID and are associated with multiple
patient-reported symptoms.19 However, the association with patient-reported symptoms
was only found with first-void urine and endocervical samples and not with self-collected
vaginal samples. In our study, where nurse-collected vaginal swabs were used, quantitative
Ct loads were not significantly different for asymptomatic women and women reporting one
or multiple symptoms such as vaginal discharge or dysuria.
The NAAT platform is a latest generation highly sensitive commercial diagnostic
test for Ct.20 However no test is 100% accurate and a positive bacterial Ct load signal was
detected in two samples that were NAAT negative and CRT positive. One sample had a Ct
load of 62.9 IFU which might be explained by inhibition of high target load.21 The other
sample had a very low load of 0.00261 IFU. Since the frequency of these discrepancies was
extremely low, we do not consider that this finding significantly affects our test evaluation.
A recent field study of the same CRT test but to detect ocular chlamydia infection
(trachoma) found similar disappointingly low sensitivity (33.3%–67.9%) and specificity
(92.4%–99.0%).21 Most commercially available and clinically evaluated POC tests for
urogenital chlamydia show poor sensitivity results.10 Compared with the results found in
our evaluation, the CRT of Diagnostics for the Real World outperforms some of the other
commercially available products.10 Still, with a sensitivity of only 41.7%, this test performs
under the minimally required sensitivity of 63% required for a POC test to treat more
infected individuals than the standard NAAT in a setting with low patient return (65%).8 On
the other hand, in situations where transmission during treatment delay and low return for
treatment are considerable, even a POC test with a sensitivity below 63% could be beneficial
in the prevention of ongoing STI transmission.23 A recent economic evaluation analysis using
the same CRT as we evaluated in this study, showed that in the UK using NAAT is more costeffective.24 In that evaluation, a sensitivity between 73% and 85% for the CRT was assumed.
POC tests available for systemic infections like HIV and syphilis are highly sensitive since
they are based on the detection of serum antibodies.25-26 Infections caused by organisms
like Ct (but also N. gonorrhoeae) are confined to mucosal tissue and normally invoke little to
no production of antibodies. Therefore, the development of POC tests to diagnose mucosal
Ct infections based on the detection of serum antibodies is, at least for now, not an option.
Improved POC tests for Ct need to detect bacterial antigens or nucleic acids, even in cases
with a low bacterial load. Promising steps have been made in the field of POC HIV-load
NAAT using nanotechnology.27 Along the same lines, a POC test for urogenital chlamydia
157
with sufficient sensitivity could be developed. Until reliable and affordable diagnostics are
available, algorithms for syndromic management can be used for low-resource settings,
although the success of algorithms for vaginal discharge varies between populations.28
In conclusion, the evaluated CRT of Diagnostics for the Real World has no added value
in the management of Ct infections due to its low test performance. There is an urgent need
for POC diagnostics for the detection of urogenital chlamydia meeting the ASSURED criteria,
including adequate sensitivity.
Acknowledgments
The authors would like to express their gratitude to all nurses and laboratory technicians of
the Dermatological Service and the Lobi Foundation for data collection, and Susan T. Landry
for editing the final manuscript.
Conceived and designed the experiments: JvdH LS SM AS HdV. Performed the experiments:
JvdH AG SM AS. Analyzed the data: JvdH SM HdV. Contributed reagents/materials/analysis
tools: LS AG SM AS HdV. Wrote the paper: JvdH LS AG SM HdV.
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Chapter 5.1
High performance and acceptibility
of self-collected rectal swabs for diagnosis
of Chlamydia trachomatis and Neisseria gonorrhoeae
in men who have sex with
men and women
Christian J. P. A. Hoebe2,3
Martijn S. van Rooijen1
Elfi E. H. G. Brouwers2,3
Han S. A. Fennema4
Harold F. J. Thiesbrummel1
Nicole H. T. M. Dukers-Muijrers1,2,3
Sex Transm Dis. 2009 Aug;36(8):493-7
1
Cluster Infectious Diseases, Sexually Transmitted Infection Outpatient Clinic, Amsterdam Public
Health Service, Amsterdam, The Netherlands; 2Department of Infectious Diseases, South Limburg
Public Health Service, Geleen, The Netherlands; 3Department of Medical Microbiology, Maastricht Infection Center, Maastricht University Medical Centre, Maastricht, The Netherlands; 4Cluster Infectious
Diseases, Amsterdam Public Health Service, Amsterdam, The Netherlands
161
Abstract
Background: Identification of sexually transmitted infections (STI) is limited by the infrequent
assessment of rectal STI. This study assesses usability of self-collected rectal swabs (SRS) in
diagnosing rectal Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG).
Methods: In 2006 to 2007, clients of the Amsterdam and South Limburg STI outpatient clinics
reporting receptive anal intercourse were asked to fill out a questionnaire and provide SRS.
A standard provider-collected rectal swab (PRS) was also taken, and both were tested for CT
and NG by a nucleic acid amplification tests. SRS performance was compared with PRS as to
agreement, sensitivity, and specificity.
Results: Prevalence of rectal CT was 11% among the 1458 MSM and 9% among the 936
women. Rectal NG prevalence was 7% and 2%. In 98% of both MSM and women, SRS and
PRS yielded concordant CT test results, for NG agreement was 98% for MSM and 99.4%
for women. SRS performance for CT and NG diagnosis was good in both groups and was
comparable for both study regions. Slightly more (57% of MSM, 62% of women) preferred
SRS to PRS or had no preference; 97% would visit the STI clinic again if SRS was standard
practice.
Conclusions: Because anal sex is a common practice for MSM and women, and anal STI are
frequently present, rectal screening should be an essential part of an STI consultation. SRS is
a feasible, valid, and acceptable alternative for MSM and women attending STI clinics, and
hence should be considered for other settings as well.
162
Chapter 5.2
Introduction
C
hlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) both cause widespread
sexually transmitted infections (STI) with major public health consequences. Active case
finding and early treatment of CT and NG are critical strategies for preventing sequelae and
reducing transmission.1-3
Although STI are commonly tested at endocervical, vaginal, and urethral sites, testing
is not standard at rectal and oropharyngeal sites. Exclusion of these body locations can leave
many infections unnoticed.4,5 In women, the risk for rectal STI is often overlooked. Data from
our Amsterdam and South Limburg STI clinics show that in 37% to 66% of women who have
rectal CT or NG, the same STI was not present genitally (unpublished data). Heterosexual
anal intercourse is often reported, while condom use is limited. In the United States, 40% of
men and 35% of women aged 15 to 44 years old reported heterosexual anal intercourse in
2002.6 In the Netherlands, anal intercourse has doubled over the past decade, reaching 15%
and 14% in women and men aged 12 to 25 years, respectively.7-9 In 2007, a national Dutch
STI clinic registration system (registering 78,062 consultations) showed the proportion of
rectal infections in the total number of CT and NG infections has increased from 11% and
22% in 2005 to 12% and 30% in 2007.10
Considering that anal sex and rectal STI are not uncommon in both men who have
sex with men (MSM) and women, there is a clear need for multisite testing for CT and NG
when anal sex is reported.11-13 Testing strategies based on the reporting of rectal complaints
would probably not suffice to reduce the number of unnoticed rectal infections. Symptoms
are partly nonspecific and often silent, with about 85% of rectal CT and NG infections being
asymptomatic in MSM.4 Diagnostic means are needed that are minimally invasive, acceptable
for clients, and easy to implement in both clinical and nonclinical settings. Because nucleic
acid amplification tests (NAATs) are highly sensitive and specific for the detection of CT or
NG in endocervical, vaginal and urethral swabs (patient- or provider-collected), and firstcatch urine samples, the self-collection of rectal swabs may be an excellent alternative
to those taken by providers.14,15 This private and simple noninvasive procedure initiates
an opportunity to enhance active case finding and case recognition in both clinical and
nonclinical settings. Studies have shown that rectal swab specimens were valid for detection
of CT and NG (although still not officially included in manufacturers’ protocols).16-18 The aim
of the current study is to evaluate the validity, feasibility, and acceptability of self-collected
rectal swabs (SRS) compared with health care provider-collected rectal swabs (PRS) for the
diagnosis of anal CT and NG in both MSM and women who report receptive anal intercourse.
163
Study setting and population
The STI outpatient clinics of the Public Health Services of Amsterdam (approximately 26,000
new consultations per year) and South Limburg (approximately 5000 new consultations
per year) both offer free-of-charge examination and treatment for STI. All visitors reporting
receptive anal intercourse within the past 6 months are routinely screened for rectal CT
and NG, for which swabs are taken by a specialized STI nurse. At the Amsterdam STI clinic,
proctoscopic examination is performed as well and swabs are taken during this examination.
For the current study, we asked participation and verbal or written consent, of MSM and
women who attended the clinics in 2006 (South Limburg) and 2007 (Amsterdam) and
reported receptive anal intercourse in the past 6 months. The study was permitted by the
Medical Ethical Committees of the University of Maastricht and of Academic Medical Center,
Amsterdam, The Netherlands.
Specimen collection, diagnostic tests, and treatment
Participants provided a SRS in addition to the PRS. STI nurses gave them a diagram and oral
instructions about how to take a SRS, i.e., to insert the swab 2.5 cm into the rectum, rotate
for 5 to 10 seconds, and place the swab in a capped tube.
All matching swabs were tested for CT and NG by the same NAAT (Cobas Amplicor,
Hoffman–La Roche, Basel, Switzerland, or SDA, Becton and Dickinson Diagnostics, NY).
Because positive NG results by Cobas Amplicor may often include false-positives, we
confirmed all positive NG results by a real-time PCR developed in-house.19-22 For SDA
confirmation, all negative results around the cut-off (for CT), and all positive results (for
NG) were retested in the next test round on the original sample and internal controls were
used. Specimen were tested within 36 hours. For Amsterdam testing occurred by Cobas
Amplicor at the Public Health Laboratory, situated in the same building as the STI clinic.
For South Limburg, testing occurred by Cobas Amplicor at the microbiologic laboratory of
Atrium, Heerlen and testing by SDA at the microbiologic laboratory of the academic hospital,
Maastricht. In South Limburg, none of the samples were inhibited. In Amsterdam, for the
purpose of the study, when inhibition occurred, further diagnostic dilution procedures were
not carried out to completion. Individual patients test results were communicated based
on the standard method of material collection (PRS and culture). Participants who tested
positive for rectal CT or NG were treated according to the standard treatment protocol of
the STI clinic. Sexual partners of the last 6 months were treated as well, if partner notification
was successful.
164
Chapter 5.2
Questionnaire
To evaluate acceptability, all participants were asked to fill out a questionnaire concerning
demographic data (e.g., sex, age, nationality), how they experienced use of both swab
methods, and their preferred method. For non-Dutch participants in Amsterdam, the
questionnaire was available in English.
To evaluate validity, agreement, к (>0.8 considered good test agreement), sensitivity, and
specificity of SRS compared with PRS were calculated. Positive and negative predictive values
(NPV) were calculated for SRS. Additionally, to examine the performance of SRS in a virtual
situation in which both PRS and SRS were used, we constructed a virtual gold standard.
Here, a result was considered positive when at least one of the NAAT tests was positive.
Prevalences, including confidence intervals, were assessed for both PRS and SRS results.
Questionnaires were analyzed by using Pearson χ2 test for independence and, in case of
small numbers with Fisher exact test. A P<0.05 was considered statistically significant.
Analyses were performed with the SPSS package version 15.0 (SPSS Inc., Chicago, IL).
Results
Study population
Of 2432 MSM and 1939 women who were eligible for this study, 1458 (60.0%) MSM and
936 (48.3%) women participated (study population: N=2394). Compared with those who did
not participate, those who did were more often of Dutch nationality and, if women, more
often had a current HIV test (P<0.05). We asked a small group of clients who were asked
to participate but refused (N=66), their reasons for not participating. Of those recorded,
the most common was fear of taking the swab incorrectly by 56% (N=37). Finding instructions unclear was mentioned by 9% (N=6) and other reasons included current complaints
of pain (N=4), no time for the extra procedure (N=3), and dislike for self-collection (N=7).
Characteristics of the study population are presented in Table 1.
Because of PCR inhibition at the first diagnostic step (N=47 for CT MSM, N=35 for
CT women and N=31 for NG MSM, N=33 for NG women), and later start of NG PCR in
Amsterdam, not all participants of the study had complete results for CT PCR and NG PCR.
Therefore, for comparison of SRS and PRS, 1411 MSM and 901 women were included for CT,
and 929 MSM and 697 women for NG.
165
Table 1. Characteristics of the Study Population (N=2394)
Amsterdam
N
Age; median (IQR)
Dutch
; N(%)
C SW ; N ( % )
HIV test at current visit; N(%)
South Limburg
MSM
Women
MSM
Women
1355
37 (30–44)
1136 (83.8)
22 ( 1.6)
902 (66.6)
866
26 (22–31)
756 (87.3)
49 (5.7)
847 (97.8)
103
36 (26–44)
92 (89.3)
4 (4.0)
93 (92.1)
70
27 (23–35)
66 (94.3)
3 (4.3)
66 (94.3)
CSW indicates commercial sex worker; IQR, interquartile range.
Prevalence of rectal CT and NG
Prevalence of CT and NG showed no statistical difference when assessed with PRS or SRS. CT
prevalence among MSM was 10.8% (95% CI: 9.3–12.6) and 10.5% (95% CI: 9.0–12.2) for PRS
and SRS, respectively. Among women, CT prevalence was 9.4% (95% CI: 7.7–11.5) and 9.3%
(95% CI: 7.6–11.4), respectively.
For NG, the overall prevalence among MSM was 7.1% (95% CI: 5.6–8.9) for PRS and
7.9% (95% CI: 6.3–9.8) for SRS; among women, it was 1.9% (95% CI: 1.1–3.2) for both PRS
and SRS.
SRS test performance and validity
Agreement between PRS and SRS was very good for both NG and CT, being higher than 97%
and showing few discrepant results (Table 2). In addition, other measures of agreement,
such as к, revealed good agreement between PRS and SRS (all к>0.8). To obtain more insight
into test performance, we calculated sensitivity, specificity, NPV, and positive predictive
value (PPV) for SRS compared with PRS (Table 2). Results show that, compared with the
standard practice of care (PRS as gold standard), PPV is in all cases above 80%.
Table 2. Performance of Self-Collected Rectal Swabs in Detection of CT and NG in MSM and Women
MSM SRS
Women SRS
MSM SRS
Women SRS
166
PRS
PRS
134
19
14
1244
75
10
y (CI 95%)
Specificity (CI 95%)
PPV
NPV
Agreement
Kappa
88% (81–91)
99% (98–99)
91%
98%
98%
0.88
9
807
88% (80–93)
99% (98–99)
89%
99%
98%
0.88
58
8
15
848
88% (78–94)
98% (97–99)
79%
99%
98%
0.82
11
2
2
682
85% (58–96)
100% (99–100)
85%
100%
99%
0.84
Chapter 5.2
Additionally, to examine the performance of SRS in a virtual situation where SRS and PRS are
combined for diagnostics, the constructed virtual gold standard was used. Com- pared with
this standard, SRS picked up 89% of all positive CT results in both MSM and women, whereas
PRS picked up 92% and 90% of all positive CT results. For NG, SRS was positive in 90% and
87% of positive samples and PRS was positive in 81% and 87% samples among MSM and
women, respectively. Of note, performance results were comparable for both study regions.
Almost all samples (98%) were tested by Cobas Amplicor, only 36 complete sets (28
MSM, 8 women) of PRS and SRS were tested by SDA. When only considering results of Cobas
Amplicor, the findings in Table 2 did not change except for NPV in MSM tested for CT, which
increased from 98% to 99% and PPV in MSM tested for NG, increased from 79% to 80%.
When comparing the data obtained from sets that were tested with SDA, SRS, and PRS test
agreement ranged from 93% to 100% for CT and NG testing in women and MSM (data not
shown).
Questionnaire on acceptability
Of all participants, 1151 MSM (80%) and 694 (74%) women responded to questions on
SRS feasibility and acceptability. Questionnaire responders did not substantially differ from
nonresponders, except that MSM who filled out the questionnaires were older (P<0.01)
than MSM who did not.
Of the total, 94% of MSM and 95% of women would use SRS again, and 97% of both
MSM and women would visit the STI clinic again if SRS were the standard test. The SRS
procedure seemed easy to 94% of MSM and 95% of women, and comfortable to 91% of
MSM and 87% of women (P=0.03); 97% of both groups found test instructions clear.
If given a choice between SRS and PRS, 50% of MSM and 57% of women would prefer
SRS, whereas 44% of MSM and 38% of women would prefer PRS (P<0.01). Of all respondents,
7% of MSM and 5% of women had no preference. Preference for either collection method
did not differ by nationality or age. Those who preferred SRS cited it is being more private
and physically comfortable (44% of MSM and 48% of women) or cited SRS is easier/quicker
(52% of MSM and 49% of women). Those who preferred PRS mainly cited the feeling that
a nurse or other healthcare provider would be more expert in taking samples (the reason
cited by 74% of MSM and 76% of women).
Discussion
This study demonstrated that self-collection of rectal specimens (SRS) is an effective method
for the detection of rectal CT and NG in MSM and women. This is in accordance with a
167
recent study among MSM, were the Gen-Probe Aptima Combo 2 is used for detecting
rectal CT and NG.23 We showed that SRS is an appropriate alternative to the standard
approach of provider-collection of specimen (PRS) in terms of test per formance, traced
infections, feasibility, and acceptability. Agreement between SRS and PRS is excellent (>97%
and all к>0.8), although some constraints must be taken into account when interpreting
test results from either approach. The absence of a gold standard impedes any definite
conclusion on the performance of either test versus reality. This is a well known problem
for studies comparing performance of different tests to reality, especially in the area of CT
diagnosis.18,24 However, absence of a gold standard is only a small obstacle in this study
because we sought an alternative to the PRS procedure that is currently in use at our clinic.
We compared 2 different methods of sample collection using otherwise exactly similar
diagnostic procedures.
Our creation of a virtual gold standard, in which at least one positive test result in SRS
or PRS indicated infection, allowed us to obtain more insight into the performance of both
collection methods. Again, since both methods may be slightly imperfect, using the virtual
gold standard has the limitation of reducing all false-positives to zero; no conclusions can
be drawn on specificity, and sensitivity may be overestimated.24 Therefore, we compared
the results of SRS and PRS only between each other in this virtual setting, where SRS picked
up ≤3% CT positives in both risk groups, a similar number of NG positives in women, and
9% more NG positives in MSM. None of the differences were statistically significant, again
suggesting that both collection methods perform equally.
Nevertheless, current procedures using NAATs are superior to those using culture,
and NAATs can improve our ability to diagnose rectal infection with CT or NG, although
not yet licensed for such use.16,18 A problem with NAATs for detection of rectal NG is crossreaction with related Neisseria species resulting in false-positive results.25 Because we confirmed all positive Cobas Amplicor NG results by a real-time PCR developed in-house, this is
of limited importance in our study. Furthermore, if there still is cross-reaction, presumably it
would be equal for SRS and PRS and not influence the comparison between the 2 methods.
Our study regions differed in level of urbanization, risk group composition, and CT
prevalence (according to PRS: 11% and 9% in Amsterdam and 8% and 6% in Limburg among
MSM and women, respectively). Results indicated that self-collection can be used in both
higher and lower prevalence settings, since SRS was in all settings feasible, well accepted,
and test performance was similar in the 2 study regions (data not shown).
This study and others show that test instructions, especially when illustrated, can
be made sufficiently clear for patients.26 However, patients need to be clearly informed
that SRS is an approved method in STI examination, since some of our study participants
preferred PRS due to feeling that provider-collection would be more expert. Doubt of their
own capability was also an important reason among those who refused to take part in the
168
Chapter 5.2
study. Still, was found that such doubt would not deter the majority of clients to come to
the clinic if SRS were to become the standard of care. It should be noticed that the median
age of the female population is 26 years old and may not reflect the young adolescent’s
perception of SRS. However, we have no reason to assume that acceptance in this young
group is lower because we did not find an age-effect and other methods of self-collection
are very well accepted by adolescents.27
The study population can be considered representative of all participants who
reported receptive anal sex at the STI clinics in the last 6 months, except that women of
non-Dutch nationality were more inclined not to participate. Of note, no determinants were
found to be related to nonacceptance of SRS in questionnaire respondents. The relatively
low participation rate of the study (60% MSM, 50% women) and doubts mentioned earlier
might suggest a general unease with rectal STI examination which underlines the need for
alternative noninvasive diagnostics. However, the participation rate may largely be explained
by time-pressure at the STI clinic that prevented all visitors from being invited to take part.
Unfortunately, we have no data on the number of eligible participants who were actually
asked to participate.
SRS can play an important role in controlling CT and NG transmission, considering
that anal sex and rectal STI are not uncommon in both MSM and women and considering, as
well, the often asymptomatic nature of these infections.18 Of course, self-sampling cannot
always replace nurse evaluation and proctoscopic examination. For specific risk groups, it
is important to inspect for anal warts or inspect the anal mucosa for lesions, discharge,
or abscesses.28,29 However, application of self-collection methods is especially valuable in
settings that include risk groups for rectal STI but do not routinely offer rectal screening for
CT and NG (e.g., the general practitioner’s office; outreach activities).30 The noninvasive
character of SRS can overcome the reluctance of at-risk populations to seek appropriate
care. Besides, SRS can be performed at home and might be a good addition to the novel STI
prevention strategies that use the internet.31,32
Conclusions
The SRS is a valid, feasible, and acceptable approach in sample collection. In a clinical
setting, it can be an additional alternative for patients who would otherwise be reluctant
to undergo rectal examination. In a nonclinical setting, it can be an important public health
tool to enhance active case finding and case recognition where it can be used for routine
screening.
169
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171
172
Clinical value of
Treponema pallidum real-time PCR
for diagnosis of syphilis
R. Heymans1*
J. J. van der Helm3,4*
H. J. C. de Vries2,3,6
H. S. A. Fennema2,4
R. A. Coutinho6,7
S. M. Bruisten1,5
J Clin Microbiol. 2010 Feb;48(2):497-502
*Both authors contributed equally to this work
Public Health Laboratory, 3STI Outpatient Clinic, 4Department of Research, 2Cluster of Infectious
Diseases, Amsterdam Public Health Service, Amsterdam, The Netherlands; Department of
Dermatology, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands;
5
Department of Experimental Virology, Academic Medical Centre, University of Amsterdam,
Amsterdam, The Netherlands; 6Department of Internal Medicine, CINIMA, Academic Medical Centre,
University of Amsterdam, Amsterdam, The Netherlands; 7National Institute for Public Health and
Environment (RIVM), Bilthoven, The Netherlands
1
Abstract
Background: The diagnosis of syphilis can be complicated when it is based on diverse clinical
manifestations, dark-field microscopy, and serology. In the present study, therefore, we
examined the additional clinical value of a Treponema pallidum real-time TaqMan PCR for
the detection of primary and secondary syphilis.
Methods: The additional value of the T. pallidum real-time PCR for the diagnosis of primary
syphilis was evaluated by the use of three different algorithms: (i) a head-to-head comparison
of the dark-field microscopy result and the T. pallidum real-time PCR result, (ii) comparison
of the clinical diagnosis made in a sexually transmitted infection clinic (STI) (including by
dark-field microscopy) and the T. pallidum real-time PCR result, and (iii) comparison of the
clinical diagnosis made in a general practitioner’s office (without dark-field microscopy)
and the T. pallidum real-time PCR result. A fourth algorithm was used to determine the
performance of the T. pallidum real-time PCR regarding the detection of secondary syphilis.
Results: From December 2006 to April 2008, 716 patients with suspected cases of primary
syphilis and 133 patients with suspected cases of secondary syphilis were included in the
study. A kappa value of 0.601 was found for the agreement between dark-field microscopy
and the T. pallidum real-time PCR. Good agreement was found between the T. pallidum realtime PCR and both the diagnosis of the general practitioner (kappa =0.745) and the diagnosis
of the STI clinic (kappa = 0.769). The sensitivity with respect to the STI clinic diagnosis was
72.8%, the specificity was 95.5%, the positive predictive value was 89.2%, and the negative
predictive value was 95.0%.
Conclusions: The T. pallidum real-time PCR is a fast, efficient, and reliable test for the
diagnosis of primary syphilis in an STI outpatient clinic and a general practitioner setting,
but it has no added diagnostic value for the diagnosis of secondary syphilis.
174
Chapter 5.3
Introduction
T
he etiologic agent of syphilis, Treponema pallidum subsp. pallidum, causes a multistage
sexually transmitted infection (STI). During the last decade, there has been an increase
in the reported incidence of syphilis in industrialized countries, emphasizing the need for
reliable diagnostics for syphilis.
The slow generation time and the inability to survive and multiply outside the
mammalian body make T. pallidum unsuitable for in vitro culturing.11 The reliable and
fast diagnosis of syphilis and early treatment could improve public health. Until recently,
the laboratory diagnosis of syphilis was based on dark-field microscopy and/or syphilis
serology. Dark-field microscopy is mainly used for the diagnosis of primary syphilis. For
optimal interpretation of the test result, dark-field microscopy requires the laboratory
technician performing the microscopy to have a great deal of experience and expertise. In
many settings in which patients with (ano)genital ulceration are seen, such as the office of
a general practitioner (GP), dark-field microscopy is not available and a definite diagnosis of
syphilis depends solely on the clinical picture in combination with the syphilis serology. In
the case of primary syphilis, false-negative serological results might specifically occur due
to the window period. Consequently, follow-up visits with repeated serological testing are
required for a period of 3 months. This might, however, result in a treatment delay, causing
disease progression that results in potentially serious health complications and continued
transmission. On the other hand, false-positive serological results may occur due to the
persistence of antibodies from infections in the past.
A fast and reliable PCR is therefore of great potential value for the diagnosis of primary
syphilis, specifically in settings in which it is not possible to perform dark-field microscopy.3
The advantages of a real-time PCR are the ability to detect the pathogen directly, the short
turnaround time, and the ease of performance. We previously developed a real-time
PCR that targets the polA gene and that is performed with swabs from the (ano)genital
ulceration(s).10
In the present study, we investigated the clinical value of this T. pallidum real-time
PCR with regard to both primary and secondary syphilitic lesions. The sensitivity, specificity,
positive predictive value (PPV), and negative predictive value (NPV) of the T. pallidum realtime PCR were determined in a clinical setting of a very large, low-threshold outpatient STI
clinic in Amsterdam, The Netherlands.
175
Study population
The STI outpatient clinic of the Amsterdam Public Health Service in Amsterdam, The
Netherlands, is a low-threshold clinic serving approximately 27,000 clients annually. Clients
can visit the STI clinic anonymously, free of charge, and without a referral by a medical
doctor. All high-risk clients are routinely screened for Treponema pallidum, Chlamydia
trachomatis, and Neisseria gonorrhoeae. Diagnostics for other STIs, such as (ano)genital
herpes simplex virus (HSV) infection, are based also on clinical symptoms. A considerable
number of clients make multiple visits per year; some of these clients are diagnosed with
one or more STIs at a time.
Clients were included consecutively in the study as having suspected cases of primary
syphilis if they presented with an (ano)genital ulcer or were included as having suspected
cases of secondary syphilis if they presented with a skin manifestation possibly related
to secondary syphilis, like macular or papular rashes, condyloma latum lesions, roseolas,
mucous patches, or alopecia.
Diagnostic tests. (i) Dark-field microscopy
Dark-field microscopy was performed for all clients who presented with an (ano)genital ulcer.
A microscope equipped with a reflecting dark-field condenser and a ×40 objective was used.
Depending on the quality of the ulcer sample collected (no epithelial cells, small amount
of erythrocytes), a minimum of two slides and a maximum of four slides were prepared for
examination. A trained dermatologist or a trained resident in dermatology examined the
dark-field slides, and the result for those found to be positive for T. pallidum were confirmed
by another examiner.
(ii) Syphilis serology
The sera of all clients were tested at the Public Health Laboratory of the Amsterdam Health
Service. The syphilis serology included a quantitative T. pallidum particle agglutination
(TPPA) test (Serodia-TP.PA; Fujirebio Europe BV) as a primary screening test and both a
quantitative rapid plasma reagin (RPR) flocculation test (RPR-Nosticon II; bioMérieux,
Boxtel, The Netherlands) and a fluorescent treponemal antibody (FTA) test (Trepo-Spot
IF; bio-Mérieux) as confirmation tests. The FTA and RPR tests were performed with TPPA
test-positive sera. To rule out false-positive results, TPPA test titers of <1:1,000 were also
confirmed by a supplementary line immunoassay (INNO-LIA syphilis score). All diagnostic
tests for treponemal and nontreponemal syphilis were performed according to the
manufacturer’s instructions.
176
Chapter 5.3
(iii) T. pallidum real-time PCR
For testing by the T. pallidum real-time PCR, two dry swab specimens were obtained from
the (ano)genital ulcer or skin scraping. Within 24 h, these swabs were transported to the
Public Health Laboratory at room temperature. All ulcerations were also examined for HSV
infections by real-time PCR (see below). The swabs were combined and eluted in a 600µl phosphate-buffered salt solution. Part of the T. pallidum eluate (100 µl) was lysed by
adding 600 µl of a 5 M guanidine thiocyanate buffer (L6; bioMérieux) containing 0.04 mg/
ml glycogen (Roche, Almere, The Netherlands) and was incubated at 65°C for 30 min. T.
pallidum chromosomal DNA was precipitated by adding 700 µl isopropanol (—20°C; Merck,
Darmstadt, Germany), and the pellet was subsequently washed twice with 500 µl 70%
ethanol. The precipitated total DNA was dissolved in 50 µl 10 mM Tris-HCl (pH 8.0) and
directly amplified.10
A real-time PCR assay targeting the polA gene of T. pallidum was performed.10 The
forward primer sequence was 5'-GGTAGAAGGGAGGGCTAGTA, and the reverse primer
sequence was 5'-CTAAGATCTCTATTTTCTATAGGTATGG. The TaqMan probe sequence was
5'-FAM-ACACAGCACTCGTCTTCAACTCC-BHQ1 (where FAM is 6-carboxyfluorescein and
BHQ1 is Black Hole Quencher). After a denaturation cycle of 5 min at 93°C, the amplification
profile consisted of 50 cycles of 30 s at 95°C, 30 s at 55°C, and 30 s at 72°C. The cutoff
positive cycle threshold (CT) was <36. CT values of 36 to 40 were considered to be in the gray
zone. These samples were retested and were considered positive if the CT value was <40.
The amplification was performed in a Rotor-Gene3000 apparatus (Corbett, Westburg, The
Netherlands).
The T. pallidum real-time PCR was shown to be specific, as no cross-reactivity with
nontreponemal pathogens occurred.10 DNA samples from T. pertenue and T. endemicum,
however, could successfully be amplified by the T. pallidum real-time PCR.
HSV-1 and HSV-2 real-time PCR
The two eluted dry swab specimens of an (ano)genital ulcer or skin scraping obtained for the
T. pallidum real-time PCR were also used for an HSV real-time PCR. HSV DNA was released by
heat extraction: a 30-µl swab eluate was incubated at 95°C for 15 min.
A real-time PCR assay targeting the gG gene of HSV-1 and the gD gene of HSV-2 was
performed.20 For HSV-1, the forward primer sequence was 5'-GGTTCCGACGCCTCAACATAC
and the reverse primer sequence was 5'-GGTGTGGATGACGGTGCTG. The TaqMan
probe sequence was 5'-HEX-CCGCTGTTCTCGTTCCTCACTGCCTC-TAMRA (where HEX is
4,4,7,2',4',5',7'-hexachloro-6-carboxyfluorescein and TAMRA is 6-carboxytetramethylrhoda
mine). For HSV-2, the forward primer sequence was 5'-CGCCAAATACGCCTTAGCA, the reverse
primer sequence was 5'-GAAGTTCTTCCCGCGAAAT, and the TaqMan probe sequence was
5'-FAM-CTCGCTTAAGATGGCCGAT CCCAATC-TAMRA.20 After a denaturation cycle of 2 min at
177
95°C, the amplification profile consisted of 45 cycles of 15 s at 95°C and 60 s at 45°C. The
cutoff positive CT value was <36. The amplification was performed in a Rotor-Gene3000
apparatus (Corbett).
Diagnostic criteria
To evaluate the clinical value of the T. pallidum real-time PCR for the diagnosis of primary
syphilis, we used three different diagnostic algorithms. The first was a head-to-head
comparison of the results of dark-field microscopy and those of the T. pallidum real-time
PCR (irrespective of previous syphilis episodes or syphilis serology test results), since both
are direct treponemal tests.
The second algorithm, which we refer to as an STI clinic-based clinical diagnosis, is
based on an algorithm conceivable for use in an equipped STI outpatient clinic and includes
comparison of the results of dark-field microscopy of the ulcer sample, previous syphilis
episodes, and the syphilis serology results with the results of the T. pallidum real-time PCR
(Fig. 1).
Since the T. pallidum real-time PCR also has great potential for GP, the third algorithm,
which we refer to as the clinical diagnosis in a GP setting, simulates a GP setting without the
Fig. 1. Representation of the procedure used to
diagnose primary syphilis in the STI outpatient
setting.
178
Fig. 2. Representation of the procedure used
to diagnose primary syphilis in a simulated GP
setting.
Chapter 5.3
availability of dark-field microscopy and is based only on comparison of the presence of an
(ano)genital ulcer, previous syphilis episodes, and syphilis serology results with the results
of the T. pallidum real-time PCR (Fig. 2).
To evaluate the clinical value of the T. pallidum real-time PCR with respect to
the diagnosis of secondary syphilis, the following diagnostic criteria were used: a skin
manifestation possibly related to secondary syphilis, as stated in the inclusion criteria above
under “Study population,” and a reactive quantitative RPR test (titer ≥1:8).
Evaluation of the clinical accuracy of the T. pallidum real-time PCR was performed by
determining the sensitivity, specificity, PPV, NPV, and kappa value (a measurement of
agreement). The Wilcoxon signed-rank test was used to describe differences in age between
T. pallidum real-time PCR-positive and -negative cases. The Pearson χ2 test was used to
examine the differences in the proportion of cases with an HSV-1 and/or HSV-2 infection
between groups. Analyses were performed by using SPSS (version 15.0) software (SPSS Inc.,
Chicago, IL).
Results
During the period from December 2006 to April 2008, a total of 716 suspected cases of
primary syphilis and another 133 suspected cases of secondary syphilis were consecutively
included. For primary and secondary syphilis, we included 40% and 87% men who have sex
with men (MSM), respectively; 30% and 9% men who have sex with women, respectively;
and 30% and 4% of women who have sex with men, respectively (Table 1). We identified
Table 1. Characteristics of suspected cases of primary and secondary syphilis and T. pallidum real-time PCR results
Characteristic
U l cus epi sodes ( pr i mar y syphi l i s)
All cases
T. pallidum PCR-positive cases
Ski n mani festati ons ( secondar y syphi l i s)
All cases
T. pallidum PCR-positive cases
Total no. (%) of cases
716 (100)
93 (100)
133 (100)
34 (100)
Age (yr)
M edi an
Inter quar ti l e r ange
32
25–41
42
36–47
37
32–45
39
32–47
Sexual orientation (no. % of cases)
Men who have sex with men
Men who have sex with women
Women who have sex with men
289 (40)
212 (30)
215 (30)
85 (91)
6 (7)
2 (2)
116 (87)
12 (9)
5 (4)
34 (100)
0 (0)
0 (0)
Infections (no. % of cases)
HSV-1 a
H SV -2
122 (17)
197 ( 28)
28 (4)
53 (7)
1 (1)
0 ( 0)
4 (4)
8 (9)
3 (2)
0 ( 0)
13 (10)
15 (11)
1 (3)
0 ( 0)
5 (15)
8 (24)
a
One patient was infected with both HSV-1 and HSV-2.
179
93 T. pallidum real-time PCR-positive cases of primary syphilis, and the median age was 42
years (interquartile ratio [IQR], 36 to 47 years) (Table 1). Infections with herpes simplex virus
type 1 (17%) or type 2 (28%) and infections with Chlamydia trachomatis (7%) and Neisseria
go-norrhoeae (4%) occurred frequently, reflecting the high risk for STIs in this population.
The T. pallidum real-time PCR-positive cases were 91% MSM, 7% heterosexual men, and
2% women. Patients with a positive T. pallidum real-time PCR result were significantly older
(P<0.001) than those who tested T. pallidum real-time PCR negative.
For secondary syphilis, 34 cases were found to be positive by the T. pallidum real-time
PCR. All of the cases were MSM, and their median age was 39 years (IQR, 32 to 47 years).
The characteristics of all patients are summarized in Table 1.
Evaluation of T. pallidum real-time PCR
for primary syphilis
In the comparison of dark-field
microscopy and the T. pallidum realtime PCR results, 47 cases tested
positive for primary syphilis by both
dark-field microscopy and the T.
pallidum real-time PCR (Table 2). We
found 53 discrepant results between
dark-field microscopy and the T.
pallidum real-time PCR; 7 cases tested
dark-field microscopy positive and T.
pallidum real-time PCR negative, while
46 cases tested dark-field microscopy
negative and T. pallidum real-time PCR
positive. The kappa value was 0.601,
indicating fair agreement in the headto-head comparison between darkfield microscopy and the T. pallidum
real-time PCR.
On the basis of the diagnosis
made by use of the clinical criteria for
primary syphilis used in an STI clinic
setting, we found the results for 83
cases to be concordantly positive with
those of the T. pallidum real-time PCR,
while the results for 41 cases were
180
Table 2. Diagnosis of primary syphilis obtained by dark-field
a
microscopy versus that obtained by the T. pallidum real-time PCR
T. pallidum real-time
PCR result
No. of cases with the following
dark-field microscopy result:
47
7
46
616
a
The data are for a total of 716 cases. The sensitivity of the T.
pallidum real-time PCR was 87.0%, and its specificity was 93.1%. The
kappa value was 0.601, which indicates fair agreement between the
results of the two tests.
Table 3. Clinical diagnosis of primary syphilis made in an STI
outpatient clinic versus that made by the T. pallidum real-time
a
PCR
PCR result
No. of cases with the following
clinical diagnosis at STI clinic b :
83
31
10
592
a The data are for a total of 716 cases. The sensitivity of the T. pallidum realtime PCR was 72.8%, the specificity was 95.5%, the PPV was 89.2%, and the NP was
95.0%. The kappa value was 0.769, which indicates good agreement between
the results of the two tests.
b The diagnostic criteria for primary syphilis in the STI outpatient clinic setting were
dark-field microscopy positive, syphilis serology, and patient history.
Table 4. Clinical diagnosis of primary syphilis made by using
syphilis serology and patient history as a model for a general
practitioner setting versus the result of the T. pallidum real-time
a
PCR
No. of samples with the
following result for clinical
diagnosis in GP setting b :
PCR result
76
26
17
597
a
The data are for a total of 716 cases. The sensitivity of the T. pallidum realtime PCR was 75%, the specificity was 97%. The kappa value was 0.745, which
indicates good agreement between the results of the two tests.
b
Primary syphilis was diagnosed either in patients with a positive TPPA result
(irrespective of the RPR test result) without a history of syphilis or in patients
with an RPR titer of 1:8 and a history of syphilis (Fig. 2).
Chapter 5.3
found to be discordant (Table 3). Of
these, 31 cases were positive on the
basis of the clinical criteria but T.
pallidum real-time PCR negative, while
No. of samples with positive HSV result/total no. of samples
in the group (%)
10 cases were negative on the basis of
T. pallidum
real-time
Clinical diagnosis of primary
Dark-field microscopy
the clinical criteria but T. pallidum realPCR result
syphilis in STI clinic setting
Positive
Negative
Positive
Negative
time PCR positive. The kappa value
1/47 (2)
0/46 (0)
1/83 (1)
0/10 (0)
was 0.769, indicating good agreement
3/7 (43)
314/616 (51)
11/31 (36)
306/592 (52)
between the diagnosis made by use
The data are for a total of 716 cases.
of the STI clinic algorithm and the
Table 6. Diagnosis of secondary syphilis made on the basis of
suspected skin or mucosal findings plus an RPR titer of 1:8
result of the T. pallidum real-time PCR.
versus the result of the T. pallidum real-time PCRa
The positive and negative predictive
No. of samples with the
values of 89.2% and 95%, respectively,
following
result
for
secondary syphilis:
PCR result
indicate the clinical usability of the
T. pallidum real-time PCR for the
33
1
44
55
diagnosis of primary syphilis.
The data are for a total of 133 cases. The sensitivity of the T. pallidum realtime PCR was 43.0%, and the specificity was 98.0%. The kappa value was 0.372,
On the basis of the diagnosis
which indicates slight agreement between the results of the two tests.
made by use of the clinical criteria for
primary syphilis used in a GP setting, we found the findings for 76 cases to be concordantly
positive with those of the T. pallidum real-time PCR (Table 4). Of the 43 discrepant results,
26 cases were positive on the basis of the clinical diagnosis in the GP setting and T. pallidum
real-time PCR negative, while 17 cases were negative on the basis of the clinical diagnosis in
the simulated GP setting and T. pallidum real-time PCR positive. The kappa value between
the results found by use of the criteria in a simulated GP setting and those of T. pallidum
real-time PCR was 0.745, which is good agreement.
Genital and anogenital ulcers can be caused by infection with T. pallidum, but in most
cases they are caused by an HSV infection; therefore, all swab samples were also examined
for both HSV-1 and HSV-2 by a herpes simplex virus type-specific PCR. Among the 716 cases,
122 (17%) were HSV-1 positive and 197 (28%) were HSV-2 positive (Table 1). In one case, an
infection with both HSV-1 and HSV-2 was found. We subtabulated the results of both darkfield microscopy and the diagnosis made in the STI clinic setting in relation to the results
for HSV and those of the T. pallidum real-time PCR (Table 5). Among the cases confirmed
to be positive by both dark-field microscopy and the T. pallidum real-time PCR, only one
case was found to be positive by the HSV-1 PCR. Among the dark-field microscopy-negative
and the T. pallidum real-time PCR-negative cases, we found 314/616 (51%) HSV-1 and -2
infections (Table 5). Of importance, no HSV-1 and -2 infections were found in the darkfield microscopy-negative and T. pallidum real-time PCR-positive group (0/46). Similarly,
when the STI clinic algorithm was used, only 1 (of 83; 1%) HSV-positive case was noted in
Table 5. Distribution of HSV-1 and/or HSV-2 infections within
the analysis of the results of dark-field microscopy versus those
of the T. pallidum real-time PCR and the analysis of the clinical
diagnosis by the STI clinic versus the results of the T. pallidum
real-time PCR a
a
a
181
the T. pallidum real-time PCR-positive group, whereas 306 (of 592; 52%) HSV-1 and HSV-2
infections were found in the STI clinic algorithm-negative and the T. pallidum real-time PCRnegative group. Notably, again, not a single HSV infection (0/10) was found in the STI clinic
algorithm-negative and the T. pallidum real-time PCR-positive group. Therefore, for both
the dark-field microscopy and the STI clinic algorithms, we found HSV infections significantly
more often (P<0.001) among the T. pallidum real-time PCR-negative cases than among the
T. pallidum real-time PCR-positive cases. This shows that most of the time ulcers either are
of herpetic origin or are caused by a syphilitic infection and not by double infections with
herpes simplex virus and Treponema pallidum.
Evaluation of T. pallidum real-time PCR for diagnosis of secondary syphilis
To evaluate the performance of the T. pallidum real-time PCR for the diagnosis of secondary
syphilis, 133 cases were included in the study. A total of 33 cases were positive both for
a diagnosis of secondary syphilis and by the T. pallidum real-time PCR. Of the 45 cases
with discordant results, 44 were T. pallidum real-time PCR negative and secondary syphilis
positive, while only 1 case was possibly missed by use of a diagnosis of secondary syphilis.
The kappa value was 0.372, indicating that there was only slight agreement between a
diagnosis of secondary syphilis and the T. pallidum real-time PCR result (Table 6).
Discussion
Syphilis is also known as “the great imitator,” and the diagnosis of syphilis is complicated
since its clinical manifestations are diverse or may be totally absent.6,7 Although genital
ulcerations can be caused by Treponema pallidum infection, in The Netherlands they
are mainly caused by herpes simplex virus types 2 and 1.1,3,14,15,18 A proper diagnosis of
syphilis therefore requires the interpretation of both the clinical picture with reference to
the laboratory results (the findings of syphilis serology and dark-field microscopy) and the
patient’s history (previous episodes of syphilis and previous syphilis serology).17
The T. pallidum real-time PCR is easy to perform in most present-day microbiological
laboratory settings.16 Two dry sterile swab specimens are used for ulcer sampling and can
be sent, at room temperature, to the laboratory for testing, making this a fast and efficient
process. Moreover, when the T. pallidum real-time PCR is available, there is no further need
to consider the syphilis serological window period, which can be up to 3 months.8 Our
analysis shows that, in addition to practical advantages, there is a good agreement between
a clinical diagnosis of primary syphilis in the STI outpatient setting and a clinical diagnosis
of primary syphilis in the simulated general practitioner setting (without the availability of
182
Chapter 5.3
dark-field microscopy).
Both T. pallidum real-time PCR and dark-field microscopy identify the spirochete
directly without the use of an indirect parameter, such as antibody production (syphilis
serology), or possibly biased information, such as the patient’s history. Therefore, we first
compared the T. pallidum real-time PCR and dark-field microscopy results and found only
fair agreement of the results of the two tests for patients with suspected primary syphilis.
If the bacterial load is low or if the viability of the treponemes is reduced, such as may
occur in older lesions, the sensitivity of dark-field microscopy may be severely reduced
to less than 80%. In combination with the usually high sensitivity of the PCR, this lack of
agreement can be envisaged.12,13,16 The second and third diagnostic algorithms were better
approaches for the clinical diagnosis of primary syphilis. Comparison of the result of the T.
pallidum real-time PCR to the diagnoses made by use of both of these diagnostic algorithms
for primary syphilis showed good agreement, as discussed by Byrt.5 Looking in more detail
at the general practitioner setting, we found that 7 of 17 discrepant cases were positive by
the T. pallidum real-time PCR and by dark-field microscopy, indicating that the T. pallidum
real-time PCR result was truly positive. In these seven cases, an early primary T. pallidum
infection within the window of the serological response may have occurred. In the general
practitioner setting, performance of the T. pallidum real-time PCR, in addition to syphilis
serology, may thus prevent a false-negative diagnosis of syphilis.
On the basis of experience, a considerable number of visitors to the STI outpatient
clinic did not return after the initial visit for their test results and could not be traced
because they were tested anonymously. Therefore, as standard practice, all patients with a
suspected syphilitic lesion and a positive dark-field microscopy result received presumptive
treatment, the consequence being that seroconversion to syphilis antibodies or a rise in titer
at the end of the window period cannot be registered, even though this would prove with
more certainty that the individual had primary syphilis.
Since no laboratory test is perfect, there are several explanations for the falsenegative T. pallidum PCR results that we found in our comparisons. There is always the
possibility of sampling errors, but dark-field microscopy may also give false-positive results,
for example, because commensal spirochetes in a perianal ulceration are falsely classified
as Treponema pallidum. False-positive serological results are also known to occur, even if
the patient’s history is known in some detail. In our study, additional information on the
patient’s history and follow-up data indicated that 21 of 26 discordant cases, in which the
individual was positive by use of the algorithm for the GP setting and T. pallidum real-time
PCR negative, had a suspected case of secondary or latent syphilis or had a serology result
that corresponded with previous syphilis treatment. Of these 21 cases, 12 cases had a
herpes simplex virus infection and 2 cases had lymphogranuloma venereum, which were the
more probable causes of ulceration. In four other cases, the serology and history data were
183
inconclusive and in only one case the dark-field microscopy result was positive, supporting
the notion that a case was missed by the T. pallidum real-time PCR.
Using the dark-field microscopy and clinical diagnosis algorithms, we observed a
significantly higher number of HSV-1 and -2 infections in the T. pallidum real-time PCRnegative group (>50%) than in the T. pallidum real-time PCR-positive group (<1%) (Table
5). Thus, for the cases in which the T. pallidum real-time PCR result was negative, it is
reasonable to assume that the (ano)genital ulceration was caused by HSV-1 and/or HSV-2.3,9
In Amsterdam, it is standard practice to perform both a T. pallidum and a herpes simplex
virus type-specific PCR with the same swab samples from ulcers. In the present study, 44%
of the cases suspected of having primary syphilis included were found to have an HSV-1 or
an HSV-2 infection.
For a considerable number of individuals with genital ulcers, no causative agent could
be isolated, and in our study this was the case for 40% of the individuals, which is highly
comparable to the findings of other studies.3,19
Secondary syphilis is often missed because of the wide diversity of clinical
presentations.2 In contrast, laboratory confirmation of secondary syphilis is not complicated,
since it is almost always accompanied by a highly reactive anticardiolipin antibody titer.
Consequently, we evaluated our T. pallidum real-time PCR with samples from patients with
skin or mucosal lesions suspected of being secondary syphilis. A diagnosis of secondary
syphilis was confirmed by an RPR test titer of ≥1:8. Although we found that the T. pallidum
real-time PCR had a high specificity (98.0%) for the detection of secondary syphilis, the
sensitivity was disappointingly low (43.0%). This might be explained by the low bacterial
load present in most secondary syphilitic lesions and/or by the method used to obtain
material for PCR (skin scrapings of abraded lesions). In contrast to our data, a study in which
directly frozen skin biopsy specimens and a PCR that used the tp47 gene as a target were
used to diagnose secondary syphilis reported a sensitivity of 75%.4 On the basis of the low
level of agreement, we conclude that the T. pallidum real-time PCR has no added value for
the clinical diagnosis of secondary syphilis cases.
In summary, the T. pallidum real-time PCR is a fast and reliable test for the detection
of primary syphilis in the STI outpatient clinic setting, as well as in the general practitioner
setting. Its added value for the diagnosis of secondary syphilis seems to be limited, however.
The earlier diagnosis of primary syphilis enabled by a fast PCR result will lead to timely
treatment and the prevention of disease progression, as well as a reduction in the length of
exposure of the patient’s sexual partners.
184
Chapter 5.3
Acknowledgments
We thank the public health nurses from the STI clinic (Cluster of Infectious Diseases,
Amsterdam Health Service) for collecting samples and the laboratory technicians of the
Public Health Laboratory (Cluster of Infectious Diseases, Amsterdam Health Service) for
analyzing them. We also thank T. Heijman for assistance with data interpretation and I.
Evertse for editing the final manuscript.
We hereby state that we do not have a commercial or other association that might
pose a conflict of interest regarding the study presented in this paper.
This study was supported by the RIVM Centre for Infectious Diseases.
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Microbiol. 45:93–96.
Mackay, I. M., G. Harnett, N. Jeoffreys,
I. Bastian, K. S. Sriprakash, D. Siebert,
and T. P. Sloots. 2006. Detection and
discrimination of herpes simplex viruses,
Haemophilus ducreyi, Treponema pallidum,
and Calymmatobacterium (Klebsiella)
granulomatis from genital ulcers. Clin.
185
Infect. Dis. 42:1431–1438.
15. Morre, S. A., J. Spaargaren, J. S. Fennema,
and H. J. de Vries. 2005. Molecular diagnosis
of lymphogranuloma venereum: PCR-based
restriction fragment length polymorphism
and real-time PCR. J. Clin. Microbiol. 43:
5412–5413.
16. Orle, K. A., C. A. Gates, D. H. Martin, B. A.
Body, and J. B. Weiss. 1996. Simultaneous
PCR detection of Haemophilus ducreyi,
Treponema pallidum, and herpes simplex
virus types 1 and 2 from genital ulcers. J.
Clin. Microbiol. 34:49–54.
17. Ratnam, S. 2005. The laboratory diagnosis of
syphilis. Can. J. Infect. Dis. Med. Microbiol.
16:45–51.
18. Sethi, G., E. Allason-Jones, J. Richens, N. T.
Annan, D. Hawkins, A. Ekbote, S. Alexander,
and J. White. 2009. Lymphogranuloma
186
venereum presenting as genital ulceration
and inguinal syndrome in men who have sex
with men in London, United Kingdom. Sex
Transm. Infect. 85:165–170.
19. Suntoke, T. R., A. Hardick, A. A. Tobian, B.
Mpoza, O. Laeyendecker, D. Serwadda,
P. Opendi, C. A. Gaydos, R. H. Gray, M. J.
Wawer, T. C. Quinn, and S. J. Reynolds.
2009. Evaluation of multiplex real-time
PCR for detection of Haemophilus ducreyi,
Treponema pallidum, herpes simplex virus
type 1 and 2 in the diagnosis of genital ulcer
disease in the Rakai District, Uganda. Sex
Transm. Infect. 85:97–101.
20. van Doornum, G. J., J. Guldemeester, A.
D. Osterhaus, and H. G. Niesters. 2003.
Diagnosing herpesvirus infections by realtime amplification and rapid culture. J. Clin.
Microbiol. 41:576–580.
Chapter 5.3
6
General discussion
187
188
Chapter 6
“K
now your epidemic, know your response” is a saying often used in the fight against
HIV.1 To know an epidemic is a main principle of infectious diseases control; not to
just generate knowledge, but to make subsequent steps to control and ultimately eradicate
the infection or disease. All studies described in this thesis have contributed to a better
understanding of the epidemiology and detection of the infections studied, and report on
HIV (non-)progression and the impact of HCV co-infection, the HCV epidemic among HIVpositive MSM, urogenital chlamydia infections in Suriname and the Netherlands, and the
evaluation of STI diagnostic procedures for urogenital chlamydia, gonorrhoea, and syphilis.
This Chapter summarises the main findings and describes future opportunities to reduce
spread and disease burden.
Chapter 2: HIV disease progression
What this Chapter adds
Most studies have estimated the prevalence of (long-term) non-progression (LTNP).2-4 Our study
is the first study with a longitudinal approach to report on the median time to progression:
2.07 years (95%CI, 1.96-2.17) after HIV seroconversion. Only two smaller studies have
reported on the loss of LTNP status among HIV seroconverters and their estimate only
differed slightly from our estimate of 12.5 years (95%CI, 12.1-12.9).5,6 Those identified
with LTNP at 10 years were heterogeneous regarding their demographic characteristics
and viral load, as were those who remained free of progression for ≥20 years. Our data
support previous suggestions that individuals with LTNP are more likely at the tail end
of a distribution than a distinct subpopulation. However, we cannot exclude that some
individuals will never experience disease progression.
Prevention and future research
Identifying the few unique individuals with durable immunological and clinical control
may yield important information on the correlates of control of infection and might help
in the development of prophylactic and therapeutic vaccines.7 However, identifying people
with LTNP may become challenging in the future if the trend towards earlier initiation of
combination ART continues. Moreover, to identify underlying mechanisms of LTNP, stringent
and uniform definition criteria, derived from epidemiological studies are important, as
a small change in definition might have a major impact on the apparent outcome.3,8 In
addition to other prevention efforts, a vaccine might be required to end the global HIV
epidemic,9 but major challenges in vaccine development remain such as the genetic
diversity of HIV, the rapid integration of HIV into the host genome, and the establishment
189
of latent reservoirs.10 Since the discovery of HIV, only four HIV vaccine concepts have been
evaluated in clinical trials, but none have proved effective.10 Novel HIV vaccine candidates
are needed in the near future. Also, although cART changed HIV from an imminent deadly
disease into a chronic disease, a cure for HIV infection is not yet feasible. Of the millions
of persons infected, to date only one adult is alive and free of the virus following a bone
marrow transplantation with CCR5Δ32 variant CD4 cells.11 Furthermore, cART cessation did
not lead to rebound viremia in a child who received cART very early after birth.12 Long-term
follow-up is required, to gain certainty as to whether the child has really been cured. To be
relevant for society at large an HIV cure needs to be simple and inexpensive.
Other interventions to reduce new infections and to curb the HIV epidemic
When broadly implemented, HIV screening of donated blood, cART use among HIV-infected
pregnant and breastfeeding women, and comprehensive harm-reduction strategies
including opiate substitution and needle exchange programmes for injecting drug users
have been successful interventions. Furthermore, male circumcision is an important
one-time intervention that reduce the risk of a man acquiring HIV during heterosexual
intercourse by 50%-60%.13 Still, challenges remain such as limited access to services, stigma,
discrimination, and the definition of drug dependence as a law enforcement rather than
public health issue.14 Currently, biomedical interventions to prevent HIV transmission are
emerging and might be an effective addition to the present behavioural interventions. The
biomedical interventions include post-exposure profylaxis (PEP), treatment as prevention
(TasP), and pre-exposure profylaxis (PrEP). PEP reduces the likelihood of HIV infection
by use of short-term ART very soon after potential exposure.15 It has been available for
individuals who were occupationally exposed to HIV since the introduction of ART.16 Since
the late 1990s, PEP became available for individuals with any type of exposure.17 TasP
was shown to be an effective intervention in the HPTN 052 study where early ART (at CD4
cell counts 350-550 cells/mm³) reduces the sexual transmission of HIV in serodiscordant
couples by 96% compared with delayed ART (at CD4 cell counts ≤250 cells/mm³).18 Several
treatment guidelines now recognise the public health benefits and have adopted TasP as a
prevention strategy. Nonetheless, the individual benefits of earlier start with cART remain
an issue of debate. PrEP is an intervention method in which HIV-negative individuals
use oral or topical ART daily to protect against HIV aquisition.19,20 When adherent to the
intervention, up to a 92% reduction in the risk of HIV acquisition has been reported.19 Many
questions remain to be elucidated in the coming years regarding the impact, cost-benefit
ratio, access, adherence, and acceptability of each intervention alone or in combination.
Therefore, observational studies, clinical trials, and modelling studies will be required. At
the same time, individual interventions will be improved to increase their effect and should
be evaluated. For example, PrEP with daily regimens requires adherence to be effective.
190
Chapter 6
New technologies such as a single injection with a long-acting ART might protect against HIV
for up to three months,21 and antiretroviral drug-infused vaginal rings designed for monthly
use are under development.22
Furthermore, timely identification of HIV-infected individuals remains important. In
the Netherlands it is estimated that 27% of individuals with HIV do not know their status
and 43% are diagnosed late in their infection.23 These individuals form an ongoing infective
reservoir propagating the epidemic, as it is estimated that 90% of new HIV transmissions
among MSM take place before diagnosis of the index case.24 Novel strategies improving
timely testing need to be developed and evaluated.25
Chapter 3: HIV disease progression
and HCV coinfection
The Hepatitis C epidemic among MSM: incidence estimates from 1990-2007 (Chapter 3.1)
Outbreaks of acute hepatitis C virus (HCV) infection among HIV-infected men having sex with
men (MSM) were described since 2000.26 Phylogenetic analysis suggested that the spread
of HCV started earlier, around 1996.27 We estimated HCV incidence among HIV-positive
MSM using three methods to capture the data structure of HCV infection, as individuals
in our study population were not all routinely and frequently screened. Our study showed
that, regardless of the estimation method applied, HCV incidence had already increased
among HIV-infected MSM in the period before 2000 (from 0.9 to 2.2/1000 person-years (PY)
in 1990 to 5.5 and 8.1/1000 PY in 1995). The increase was substantial from 2002 onwards to
values between 16.8 and 30.0/1000 PY in 2005 and between 23.4 and 51.1/1000 PY in 2007.
Effect of Hepatitis C co-infection on cause-specific mortality following HIV seroconversion
(Chapter 3.2)
Conflicting evidence existed as to whether HCV co-infection affected HIV disease progression.
In contrast to most studies, in our large study all individuals had a known date of HIV
seroconversion. Our study clearly showed that in the cART era, HCV co-infection increased
the risk of HIV- and/or AIDS-related mortality among all risk groups, compared with HIV
mono-infected individuals from the same risk group. Other clinically-relevant findings
from our study were that, all-cause mortality became significantly higher for co-infected
individuals compared with mono-infected individuals in the cART era. Moreover, among coinfected individuals, we found that their risk of hepatitis or liver-related mortality decreased
in the cART era compared with the pre-cART era. In addition, despite the reduction in
191
hepatitis or liver-related mortality in the cART era, co-infected individuals still experienced a
higher rate of death from these causes compared with mono-infected individuals.
Recent reports from the US, Japan, and Switzerland studying HCV incidence among HIVpositive MSM showed an ongoing increase in new HCV infections from 2008-2011, with
incidence estimates between 2.57 and 40.9 per 1000 person-years (PY).28-30 In contrast, a
study from Amsterdam estimating HCV incidence until 2011 reported stabilisation around
12/1000 PY after 2005 among HIV-infected MSM from the Amsterdam cohort.31 The
authors suggested that the levelling off might be explained by an increase in HCV testing
and treatment uptake, risk reduction, and a saturation-effect among MSM at highest risk
for HCV infection.31 HCV incidence among HIV-negative MSM remains low.32 However, a
high incidence of reinfection has been observed among MSM successfully treated for HCV
with possible consequences such as the development of resistant strains and treatment
costs.33,34 HCV infection in MSM is associated with non-injecting recreational drug use and
high-risk sexual behaviour that might result in mucosal trauma such as fisting, use of sex toys
and group sex. Furthermore, biological factors related to HIV infection and ulcerative STI
play a role as well. For example, HIV/HCV co-infected individuals are more likely to shed HCV
RNA in semen and have higher HCV RNA serum levels compared with HCV mono-infected
individuals. However, the role of host immunity remains to be elucidated.28 Phylogenetic
HIV analysis found clustering of HCV cases on the HIV phylogeny and showed that the
location of an HIV-positive individual on the HIV phylogeny can serve as an indicator for the
risk of HCV co-infection.35 The generalisability of these findings should be validated by other
studies and it might be of interest to determine the HCV sequences. However, this principle
might have the potential to offer targeted HCV testing to HIV-positive men whose HIV strain
coincides with HCV co-infected individuals.
Our findings in Chapter 3.2 support the current recommendation to begin ART early
in the course of HIV infection in order to limit progression of liver disease in co-infected
patients.36 As HCV treatment of co-infected individuals is changing rapidly, future studies
describing the role of HCV therapy on HIV disease progression are needed. Furthermore, the
effect of the moment of HCV infection relative to HIV infection on HIV disease progression
is unknown. Also, the new and more effective HCV treatment combinations might limit the
HCV epidemic among MSM in high-income countries. As observed with the introduction of
cART for HIV37, risk behaviour might increase and should be monitored.
To achieve successful HCV prevention among HIV co-infected individuals, multiple
approaches for different risk groups will be necessary. Raising awareness, routine testing
of risk groups, and high uptake of effective HCV treatment are needed to minimise
further spread of HCV, particularly among HIV-infected MSM when considering high192
Chapter 6
income countries. For IDU, harm reduction programmes have the potential to decrease
both incidence and prevalence of HCV but these interventions are not, or incompletely,
implemented in many countries.38-40 Moreover, an HCV vaccine will be beneficial for all risk
groups, and prospects for a HCV vaccine have improved greatly in the last decade.41,42 The
promising results of treatment-as-prevention studies for HIV may drive interest in pursuing
this strategy with DAAs to combat HCV transmission in the future.32,43 However, as HCV
treatment is still costly, preventing initial exposure to HCV remains a high priority. Continued
follow-up and incidence estimates obtained from cohort studies are required to observe the
development of the HCV epidemic and disease burden.
Chapter 4: Chlamydia infections in Suriname
and the Netherlands
Chlamydia infections among ethnic groups in Paramaribo, Suriname (Chapter 4.1)
We estimated determinants for chlamydia, including the role of ethnicity, and identified
transmission patterns and ethnic sexual networks among clients of two clinics in Paramaribo,
Suriname. The overall chlamydia prevalence was 15%. Younger participants and participants
of Creole and Javanese ethnicity were more frequently infected with urogenital chlamydia.
Although sexual mixing with other ethnic groups did differ significantly per ethnicity,
this mixing was not independently significantly associated with chlamydia. We typed C.
trachomatis-positive samples using multi-locus sequence typing (MLST) and identified three
large C. trachomatis clusters. Although the proportion from various ethnic groups differed
significantly between the clusters, all five major ethnic groups were represented in all three
clusters.
The role of Surinamese migrants in the transmission of Chlamydia trachomatis between
Suriname and the Netherlands (Chapter 4.2)
Surinamese migrants travel extensively between the Netherlands and Suriname. Therefore,
we assessed whether the Surinamese migrants in the Netherlands form a bridge population
facilitating transmission of C. trachomatis between Suriname and the Netherlands. The
MLST strain distribution of Surinamese migrants differed significantly from both the native
Surinamese and Dutch populations, but was not an intermediate state between these two
populations. Based on data from the questionnaires, sexual mixing occurred frequently
between Surinamese migrants in Amsterdam and the native populations of Suriname and
the Netherlands. Yet, the MLST cluster distribution did not differ significantly between
193
participants who mixed and those who did not. We concluded that migrants did not seem
to form an effective bridge population for C. trachomatis transmission between the native
populations.
Distinct transmission networks of Chlamydia trachomatis among MSM and heterosexual
adults (Chapter 4.3)
Genovar distributions of Chlamydia trachomatis based on ompA typing differ between MSM
and heterosexuals. We investigated clonal relationships using MLST, a high resolution typing
method. When MLST was applied, differences in C. trachomatis strain distribution proved
to be much more apparent compared with ompA genovar typing. We identified 8 clusters of
which 4 consisted of samples from MSM (90%–100%). The other 4 clusters consisted mainly
of samples from heterosexuals (87%–100%). Genetic diversity was much lower in the MSM
clusters than in heterosexual clusters. C. trachomatis transmission patterns among MSM
and heterosexuals were largely distinct.
To map the role of sexual mixing across ethnic subpopulations in relation to the spread of STI,
using molecular epidemiology alone has its limitations. For example, the role of concurrency
and partnership factors cannot be included sufficiently. Mathematical transmission models
could be of added value to better identify sexual networks and elucidate why differences
exist between ethnic groups as has been demonstrated for HIV.44 The study showed that if
migrants had more partners, the HIV prevalence would increase in their own community,
and that decreasing condom use or increasing frequency of sexual intercourse would
not affect HIV prevalence. Also, studies have shown that sexual behaviour determinants
do not solely account for ethnic disparities in STI rates at the population level, but that
social determinants such as poverty contribute as well.45,46 Therefore, to eliminate ethnic
disparities in the prevalence and incidence of STI, focus on social determinants should not
be neglected.
For Suriname, we recommend targeting prevention activities at the community at
risk, with a focus on the younger age groups. Furthermore, adequate testing facilities and
subsequent treatment are needed to reduce the disease burden of chlamydia in Suriname.
Our data do not seem to justify the need for joint-preventive campaigns between Suriname
and the Netherlands, as Surinamese migrants did not seem to form an effective bridge
population for C. trachomatis transmission. However, in the Netherlands, chlamydia
prevalence is high among specific ethnic groups and therefore attention to these groups is
warranted.47
We found almost completely distinct C. trachomatis strains between MSM and
heterosexuals. This might be explained by the absence of sexual mixing between the groups.
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Chapter 6
On the other hand, tissue tropism might play a role. As the pathogens reside in different
niches within the human body (male urethral, cervical, and rectal tissue) and make use of
different transmission routes, specialisation towards these niches or transmission routes
may have occurred. Although a recent study among MSM and women with anorectal C.
trachomatis did not support an indication for tissue tropism.48 Also, MSM-associated strains
appear to be much more clonal and homogeneously clustered, while the heterosexualassociated strains are numerous and heterogeneous. The latter indicates a slowly evolving
endemic disease that has diversified over time by stochastic effects. The MSM-associated
strains may have arisen from more recent clonal outbreaks similar to the LGV outbreak. The
typical MSM- and heterosexual-associated C. trachomatis clusters may also originate from
network-associated factors. Compared with heterosexuals, MSM in general report higher
numbers of partners. In addition, MSM mix more often with partners that differ in age,
ethnicity, nationality, and lifestyle.49 Therefore the sexual network structure of MSM is much
more interconnected, giving rise to a large international transmission network, also seen for
HCV.27 In contrast, less interconnected networks typically found among heterosexuals may
lead to a more heterogeneous C. trachomatis strain distribution and a more local spread.50
Mapping of networks is important to identify determinants that could potentially lower the
prevalence of C. trachomatis in specific groups. Mathematical modelling can be of additional
value to assess the impact that targeted interventions might have on the prevalence and
incidence within a population.
Chapter 5: STI diagnostic test
evaluations
Point-of-care test for detection urogenital chlamydia shows low sensitivity (Chapter 5.1)
In general, POC tests for Chlamydia trachomatis (Ct) show disappointing test performance.
However, one study sponsored by the manufacturer (Diagnostics for the Real World)
reported over 80% sensitivity with their Chlamydia Rapid Test (CRT). We evaluated the CRT
in a real-life clinical setting and found a disappointingly low sensitivity of 41.2%. Especially
samples with a low Ct load were not detected by the CRT. We concluded that the sensitivity
of CRT for detecting urogenital Ct in this non–manufacturer-sponsored study did not meet
the expectations as described previously. Improved POC are needed as a meaningful
diagnostic to reduce the disease burden of chlamydia.
195
High performance and acceptability of self-collected rectal swabs for diagnosis of Chlamydia
trachomatis and Neisseria gonorrhoea (Chapter 5.2)
Identification of STI can be hampered by the infrequent assessment of the ano-rectal site.
Self-collected rectal swabs (SRS) may overcome barriers for rectal testing, as this procedure
is less invasive and easy to implement in both clinical and non-clinical settings. At the
Amsterdam outpatient STI clinic, we evaluated the validity, feasibility, and acceptability of
SRS compared with health care provider-collected rectal swabs (PRS) for the diagnosis of anal
CT and NG in both MSM and women who report receptive anal intercourse. We concluded
that SRS is a feasible, valid, and acceptable alternative for MSM and women attending STI
clinics. Subsequently, SRS has been implemented as a standard of care among women
reporting anal sex at the Amsterdam outpatient STI clinic and among MSM included in the
Amsterdam Cohort Studies. However, self-sampling cannot always replace clinic inspection
and anoscopic examination. Especially in high-risk groups and in the case of complaints it
is important to inspect the anal mucosa for anal warts, ulceration, tumour, discharge, or
abscesses.
Clinical value of Treponema pallidum real-time PCR for diagnosis of syphilis (Chapter 5.3)
The diagnosis of syphilis can be complicated as it is based on diverse pathogen and hostrelated parameters, like clinical manifestations, dark-field microscopy, and serology. A
new method to identify syphilis is Nucleic Acid Amplification Tests (NAAT ). Therefore, we
assessed the clinical value of a Treponema pallidum real-time PCR (a DNA based NAAT) for
the diagnosis of syphilis. Good agreement was found between the T. pallidum real-time PCR
to diagnose primary stage syphilis based on an ulcer swab, and 2 diagnostic algorithms; an
STI setting (with dark field microscopy) and a simulated general practitioner setting (in the
absence of dark field microscopy). In contrast, the T. Pallidum real-time PCR performed on
scarified suspected skin lesions for the detection of secondary syphilis had a disappointingly
low sensitivity. We concluded that the T. pallidum real-time PCR is a fast, efficient, and reliable
test for the diagnosis of primary syphilis in an STI outpatient clinic and a general practitioner
setting, but it has no added diagnostic value for the diagnosis of secondary syphilis. The
T. pallidum real-time PCR is currently used to diagnose primary syphilis infections at the
Amsterdam STI outpatient clinic and available via the Public Health Laboratory for general
practitioners and health care specialists.
To date, NAAT performed in laboratories are the standard diagnostics to detect STI in highincome countries, but the landscape of diagnostic testing for STI will change in the near
future. The development and use of point-of-care (POC) diagnostics will increase, with the
advantage that results will be readily available enabling prompt treatment. Furthermore,
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Chapter 6
POC tests have the potential to offer STI testing and treatment in non-clinical venues in the
community, such as churches, beauty salons, saunas, and cafés. In contrast to HIV, HCV, and
syphilis, no reliable antibody-based POC tests are available for chlamydia or gonorrhoea as
these infections are confined to mucosal tissue and normally invoke little to no production
of antibodies.51 Most POC tests for detection of chlamydia currently described are based
on immunoassays that detect antigen or lipopolysaccharide specific to C. trachomatis and
showed very low sensitivities.52,53 NAAT based POC tests for the detection C. trachomatis
and N. gonorrhoea are in development. Recently, a study reported on a chlamydia rapid
test based on recombinase polymerase amplification, which might have potential to be
applicable in POC settings as chlamydia could be detected within 20 minutes directly from
urine samples.54
Studies in this thesis were all clinic-based, but currently home-collection kits are
increasingly available where the individual collects specimen at home and sends it to a
laboratory for analysis. In addition, self-testing, where the test is completely performed and
the result interpreted by laypersons, will increase. However, concerns are being raised about
the quality of the available tests and whether non-medical trained individuals will be able
to correctly interpret the test results. Nonetheless, this latter discussion is not new; more
than a century ago the interpretation of a thermometer to determine fever was restricted
to doctors, whereas nowadays most households have one for medically unsupervised use.
Modern technologies, for example a video clip on the internet, can instruct individuals how
to perform a self-test. Other challenges lie in the appropriate linkage to care for individuals
tested positive with a self-test, partner notification, and surveillance. Independent test
evaluations are needed to reveal the performance of new tests and advice to customers is
necessary to guide them trough the offers made online. Epidemiological studies are needed
to assess the impact of the developments in home-collection testing and self-testing and to
guide policy making.
Concluding remarks
The last few decades much progress has been made in the detection, treatment, and
prevention of HIV, HCV, and STI. To continue the battle against these infections, the extent
to which the aforementioned interventions can be brought to scale will determine their
population-level impact. Therefore, resources, scale-up of testing, availability of therapy,
appropriate (biomedical) interventions, and the infrastructure to provide implementation
are needed for success. As transmission is ongoing in specific subgroups, new interventions
are still needed and research on their effect in the real world remains very important. Cross
border collaborations are necessary to gain insight into international transmission networks
197
and to jointly make subsequent steps to control the infection. Large collaborations are
needed to study outcomes that individual studies are not able to address. The development
of advanced statistical methods might be beneficial to solve complex research questions
and better describe epidemics. Epidemiology will remain important to monitor changing
epidemics over time, evaluate interventions and clinical outcomes, and to guide public
health strategies to minimise further disease burden. To enrich the analysis, conclusions
and recommendations a multidisciplinary approach with data sources from adjacent fields
like clinical data, immunology, virology, genetics, and psychosocial sciences is required.
Moreover, vigilance and surveillance is warranted to identify new and re-emerging infections.
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Chapter 6
Appendix
201
202
Appendix: Summary
Summary
C
hapter 1 provides a brief overview on the epidemiology of HIV, HCV and STI worldwide,
describes aspects of prevention and epidemiology and presents the outline of the
studies described in this thesis.
Chapter 2: HIV progression
The studies described in Chapters 2 and 3 use data from CASCADE Collaboration in
EuroCoord, one of the largest cohorts worldwide among HIV seroconverters.
In Chapter 2.1 we examined long-term non-progression (LTNP) of HIV infection among
4979 HIV seroconverters. Non-progression was defined as being HIV-positive without AIDS,
antiretroviral therapy-naive and with CD4 cell counts ≥500 cells/mm³. The median time to
progression was about 2 years and at 5, 10 and 15 years the estimated progression-free
survival of 18%, 4%, and 1% respectively. At 10 years of HIV seroconversion, 283 individuals
were exhibiting LTNP, of whom most lost this status subsequently. In the multivariable
analyses, loss of LTNP status was significantly associated with lower CD4 counts at 10 years
following seroconversion, but not with higher HIV RNA at 10 years of HIV seroconversion, age,
mode of infection, sex, or calendar year of seroconversion. We concluded that progressionfree survival is a rare but real phenomenon. Studies on the few unique individuals with
durable control might help in the development of prophylactic and therapeutic vaccines.
Chapter 3: HIV and HCV co-infection
In Chapter 3.1 we described the hepatitis C (HCV) epidemic among 3014 HIV-positive men
who have sex with men (MSM). We estimated the HCV incidence from 1990 to 2007. To
capture the data structure of HCV infection we used three estimation methods. Our study
showed that, regardless of the estimation method applied, HCV incidence had already
increased among HIV infected MSM in the period before 2000 but from 2002 onwards
it increased substantially. We concluded that raising awareness is necessary to minimize
further spread of HCV among HIV-infected MSM. Incidence estimates obtained from cohort
studies may help identify changes in the spread of important infections earlier.
In Chapter 3.2 we determined the effect of HCV co-infection on cause-specific
mortality among 9164 HIV seroconverters before and after 1997, when combination
antiretroviral therapy (cART) became widely available. We showed that in the cART era, HIV
and/or AIDS-related mortality was higher among co-infected individuals than those with
only HIV infection in each risk group (i.e. injection-drug users, MSM, heterosexual adults
and hemophiliac patients). Furthermore, compared to individuals infected with only HIV,
co-infected individuals had higher risk of death from hepatitis or liver disease. Among
203
individuals infected with only HIV or with co-infection, the mortality from HIV infection
and/or AIDS-related causes and hepatitis or liver disease decreased significantly after 1997,
compared to the pre-cART era. Our data underscore the importance of early diagnosis of
HCV infection in HIV-infected individuals and the need for routine screening of HCV among
high risk groups, including those not (yet) infected with HIV. Furthermore, our findings
highlight the importance of interventions to increase the uptake of HCV treatment in coinfected individuals.
Chapter 4: Chlamydia infections in Suriname and the Netherlands
In Chapters 4 and 5 data is used that is collected Suriname at an STI clinic and family planning
clinic and/or in the Netherlands at the outpatient STI clinic of Amsterdam. For Chapter 5.2
also data from the STI clinic of South Limburg is used. Suriname is a society composed of
many ethnic groups, such as Creoles, Maroons, Hindustani, Javanese, Chinese, Caucasians,
and indigenous Amerindians.
In Chapter 4.1 we estimated determinants for urogenital Chlamydia trachomatis
(Ct) infections and identified ethnic sexual mixing patterns among ethnic groups in
Paramaribo, Suriname. We included 1508 heterosexual adults at two outpatient clinics.
Overall chlamydia prevalence was 15%. Younger participants and participants of Creole
and Javanese ethnicity were more frequently infected with urogenital chlamydia. Sexual
mixing with other ethnic groups did differ significantly per ethnicity but this mixing was not
independently significantly associated with chlamydia. We typed the Ct-positive samples
and identified three large Ct clusters. Although the proportion from various ethnic groups
differed significantly between the clusters, all five major ethnic groups were represented in
all three clusters. We recommend to target prevention activities to the whole community at
risk, with a focus on the younger age groups. Furthermore, adequate testing facilities and
subsequent treatment are needed to reduce the disease burden of chlamydia in Suriname.
In Chapter 4.2 we studied the role of Surinamese migrants in the transmission of
Chlamydia trachomatis (Ct) between Suriname and The Netherlands. We typed 426 Ctpositive samples through multilocus sequence typing (MLST). The MLST strain distribution
of Surinamese migrants differed significantly from both the native Surinamese and Dutch
populations, but was not an intermediate state between these two populations. Based
on data from the questionnaires, sexual mixing occurred frequently between Surinamese
migrants in Amsterdam and the native populations of Suriname and the Netherlands. Yet,
the MLST cluster distribution did not differ significantly between participants who mixed
and those who did not. We concluded that migrants did not seem to form an effective bridge
population for Ct transmission between the native populations. Our data do not seem to
justify the need for joint campaigns to reduce the transmission of Ct strains between both
countries. However we recommend intensified preventive campaigns to decrease the Ct
204
Appendix: Summary
burden both in Suriname and in the Netherlands.
In Chapter 4.3 we revealed distinct transmission networks of Chlamydia trachomatis
(Ct) in MSM and heterosexual adults in Amsterdam, The Netherlands. Using ompA genovar
typing, heterosexuals were mainly affected with genovars E, F, and D, while MSM had
predominantly genovars D, G, and J infections. When MLST was applied, differences in
Ct strain distribution proved to be much more apparent. We identified eight clusters of
which 4 consisted of samples from MSM (90%–100%). The other 4 clusters consisted
mainly of samples from heterosexuals (87%–100%). Genetic diversity was much lower in
the MSM clusters than in heterosexual clusters. Ct transmission patterns among MSM and
heterosexuals were largely distinct. We hypothesize that these differences are due to sexual
host behavior, but bacterial factors may play a role as well.
Chapter 5: STI diagnostic test evaluations
In Chapter 5.1 we evaluated a point-of-care test for detection of urogenital chlamydia in
912 women in two clinics in Suriname. Our study showed that the Chlamydia Rapid Test
(CRT) compared to NAAT had a sensitivity and specificity of 41% and 96%, respectively. The
positive predictive value and negative predictive value were 59% and 93% respectively.
Quantitative Ct bacterial load was 73 times higher in NAAT-positive/CRT-positive samples
compared to NAAT-positive/CRT-negative samples. Sensitivity of CRT in samples with low
Ct load was much lower than in samples with high Ct load which indicates that the CRT
fails especially in the low load chlamydia infections. Human cell load did not differ between
true-positive and false-negative CRT results, thus thoroughness of sampling seems of no
influence. Improved POC are needed as meaningful diagnostic to reduce the disease burden
of chlamydia.
In Chapter 5.2 we examined the performance and acceptability of self-collected
rectal swabs for diagnosis of Chlamydia trachomatis (Ct) and Neisseria gonorrhoeae (Ng) in
1458 MSM and 936 women in two STI clinics in the Netherlands. The prevalence of rectal
Ct was 11% among MSM and 9% among women. Rectal Ng prevalence was 7% and 2%
respectively. Self-collected rectal swab (SRS) performance for Ct and Ng diagnosis was good
in both groups and was comparable for both study regions. Almost all individuals would visit
the STI clinic again if SRS was standard practice. We concluded that SRS is a feasible, valid,
and acceptable alternative for MSM and women attending STI clinics. We recommend that
rectal screening should be an essential part of an STI consultation as anal STI are frequently
present among both MSM and women. Also SRS should be considered for other settings as
well.
The diagnosis of syphilis can be complicated when it is based on diverse clinical
manifestations, dark-field microscopy, and serology. Therefore, in Chapter 5.3 we assessed
the clinical value of a Treponema pallidum real-time PCR in an STI clinic setting for diagnosis
205
of syphilis among 716 patients with suspected primary syphilis and 133 patients with
suspected secondary syphilis. We simulated a general practitioner setting without the
availability of point-of-care diagnostics. Good agreement was found between the T. pallidum
real-time PCR and standard diagnostics for primary syphilis, both in the STI clinic and general
practitioner setting. Yet, the low sensitivity of the T. Pallidum real-time PCR for the detection
of secondary syphilis was disappointing. We concluded that the T. pallidum real-time PCR is a
fast, efficient, and reliable test for the diagnosis of primary syphilis in an STI outpatient clinic
and a general practitioner setting, but it has no added diagnostic value for the diagnosis of
secondary syphilis.
In Chapter 6, an overview is given of what the findings of the studies included in this
thesis add to the already existing knowledge and what recommendations arise from the
research. This is followed by a discussion based on recent literature and future directions
for prevention and research.
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Appendix: Samenvatting
Samenvatting
H
oofdstuk 1 geeft een kort overzicht van de epidemiologie van hiv, HCV en soa’s
wereldwijd, het beschrijft aspecten van preventie en epidemiologie en presenteert de
hoofdlijnen van de in dit proefschrift beschreven studies.
Hoofdstuk 2: hiv progressie
In de studies die in hoofdstuk 2 en 3 worden beschreven wordt gebruik gemaakt van data
van CASCADE Collaboration in Eurocoord, wereldwijd een van de grootste cohorten onder
hiv seroconverters.
In hoofdstuk 2.1 hebben we het fenomeen van lange termijn non-progressie (LTNP)
bij hiv-infectie onderzocht onder 4.979 hiv seroconverters. Het idee is dat sommige mensen
die besmet raken met hiv gedurende een lange periode een goed werkend immuunsysteem
behouden. Het is niet duidelijk waardoor dit komt maar beter inzicht zou kunnen helpen
bij de ontwikkeling van profylactische en therapeutische hiv vaccins. Non-progressie werd
gedefinieerd als hiv-positief zonder aids, en zonder antiretrovirale therapie en met CD4aantallen ≥ 500 cellen/mm3. De mediane tijd tot progressie was ongeveer 2 jaar en de
geschatte progressievrije overleving na 5, 10 en 15 jaar was respectievelijk 18%, 4% en 1%.
Tien jaar na hiv seroconversie, vertoonden 283 personen LTNP, van wie de meesten deze
status na die 10 jaar verloren. Het verlies van LTNP status was significant geassocieerd met
een lager CD4-aantal 10 jaar na seroconversie, maar niet met een hoger aantal virusdeeltjes
10 jaar na hiv seroconversie, leeftijd, wijze van besmetting, geslacht of kalenderjaar van
seroconversie. We concludeerden dat de progressievrije overleving een zeldzaam fenomeen
is maar wel degelijk voorkomt.
Hoofdstuk 3: hiv en HCV co-infectie
In hoofdstuk 3.1 wordt de HCV epidemie onder 3014 hiv-positieve mannen die seks hebben
met mannen (MSM) beschreven. We schatten de HCV incidentie in de periode 1990-2007
en hebben drie schatting-methoden gebruikt om rekening te houden met de niet volledige
data over HCV-co- infectie status. Onze studie toonde aan dat de HCV incidentie onder hiv
geïnfecteerde MSM, ongeacht de gebruikte schattingsmethode, al was toegenomen in de
periode vóór 2000, maar dat de incidentie vooral toenam vanaf 2002. We concludeerden
dat het nodig is om bewustzijn te vergroten ten aanzien van seksuele verspreiding van
HCV onder hiv-geïnfecteerde MSM om verdere verspreiding te minimaliseren. Incidentie
schattingen verkregen met behulp van cohort studies kunnen helpen om veranderingen in
de verspreiding van deze en andere belangrijke infecties eerder te identificeren.
In hoofdstuk 3.2 hebben we het effect van HCV co-infectie op oorzaak-specifieke
207
mortaliteit bij 9164 hiv seroconverters bepaald voor en na 1997, toen antiretrovirale
combinatietherapie (cART) op grote schaal beschikbaar kwam. We toonden aan dat in het
cART tijdperk de hiv en/of aids- gerelateerde sterfte hoger was bij HCV co-geïnfecteerden dan
bij mensen met alleen hiv; dit geldt voor alle risicogroepen (injecterende drugsgebruikers,
MSM, heteroseksuele volwassenen en hemofiliepatiënten). Daarnaast hadden cogeïnfecteerde individuen een groter risico op overlijden door hepatitis of leverziekte in
vergelijking met personen die besmet waren met alleen hiv. Onder individuen met alleen
hiv of met een hiv/HCV co-infectie, was de mortaliteit van hiv- en/of aids - gerelateerde
oorzaken en hepatitis of leverziekte aanzienlijk afgenomen na 1997, vergeleken met het
pre-cART tijdperk. Onze gegevens onderstrepen het belang van een vroege diagnose van
HCV- infectie bij hiv-geïnfecteerde individuen en de noodzaak van routinematige screening
van HCV onder risicogroepen, waaronder degenen die (nog) niet besmet zijn met hiv.
Bovendien benadrukken onze bevindingen het belang van maatregelen om de behandeling
van HCV co-geïnfecteerde individuen op te schalen.
Hoofdstuk 4: Chlamydia infecties in Suriname en Nederland
In de hoofdstukken 4 en 5 worden gegevens gebruikt die verzameld zijn bij een soapolikliniek en een family planning kliniek in Paramaribo (Suriname) en/of bij de soapolikliniek in Amsterdam (Nederland). Voor hoofdstuk 5.2 worden ook gegevens van de
soa-polikliniek van Zuid-Limburg gebruikt. Suriname is een samenleving die bestaat uit vele
etnische groepen, zoals Creolen, Marrons, Hindoestanen, Javanen, Chinezen, blanken, en
de inheemse Indianen.
In hoofdstuk 4.1 schatten we determinanten voor urogenitale Chlamydia trachomatis
(Ct ) infecties en identificeren we het hebben van seksueel contact met iemand van een
andere etnische afkomst onder etnische groepen in Paramaribo, Suriname. Er zijn 1508
heteroseksuele volwassenen op twee poliklinieken geïncludeerd. De chlamydia prevalentie
was 15%. Urogenitale chlamydia infecties kwamen het meest voor bij jongere deelnemers
en deelnemers van Creoolse en Javaanse afkomst. Het hebben van seksueel contact
met iemand van een andere etnische afkomst was weliswaar significant verschillend
per etniciteit maar dit was niet significant geassocieerd met een chlamydia infectie. We
typeerden de gevonden chlamydia bacteriën en deze bleken onder te verdelen in drie grote
Ct clusters. Hoewel het aandeel van de verschillende etnische groepen significant verschilde
tussen de clusters kwamen alle vijf grote etnische groepen voor in elk van de drie clusters.
Wij raden aan om preventieactiviteiten te richten op de hele gemeenschap die risico loopt
op een Ct infectie, met een focus op de jongere leeftijdsgroepen. Daarnaast zijn adequate
testfaciliteiten en daaropvolgende behandeling nodig om de ziektelast van chlamydia te
verminderen in Suriname.
In hoofdstuk 4.2 bestudeerden we of Surinaamse migranten een brugpopulatie
208
Appendix: Samenvatting
vormen in de verspreiding van Chlamydia trachomatis (Ct) tussen Suriname en Nederland.
We typeerden 426 Ct- positieve monsters met behulp van multilocus sequence typing
(MLST). De verdeling van de Ct- stammen die gevonden werden bij Surinaamse migranten
verschilde significant van die bij zowel de Surinaamse als de Nederlandse autochtone
bevolking, en was geen tussenstadium tussen deze twee autochtone populaties. Uit de
vragenlijsten bleek dat er vaak seksueel contact was tussen Surinamers in Amsterdam en
de autochtone bevolking van Suriname en Nederland. Toch verschilde de MLST cluster
distributie niet significant tussen deelnemers die aangaven seksueel contact te hebben
gehad met iemand van een andere bevolkingsgroep en deelnemers die aangaven dat niet
te hebben gehad. We concludeerden dat migranten geen effectieve brug populatie lijken
te vormen voor Ct transmissie tussen de autochtone bevolkingsgroepen. Onze gegevens
lijken niet de noodzaak te rechtvaardigen van gezamenlijke campagnes om de overdracht
van Ct tussen beide landen te verminderen. Toch raden we aan om preventie campagnes te
intensiveren en te richten op de lokale risicopopulaties om de Ct last in zowel Suriname als
Nederland te verlagen.
In hoofdstuk 4.3 onderzochten we verschillende transmissienetwerken van Chlamydia
trachomatis (Ct) tussen MSM en heteroseksuele volwassenen in Amsterdam. Uit ompA
genovar typering bleek dat heteroseksuelen vooral genovars E, F en D hadden, terwijl MSM
overwegend genovars D, G en J hadden. Met MLST werden de verschillen in Ct distributie
duidelijker. We vonden acht clusters waarvan 4 bestonden uit monsters van MSM (90%
-100%). De andere 4 clusters bestonden voornamelijk uit monsters van heteroseksuelen
(87% -100%). De clusters die bij MSM voorkwamen waren genetisch minder divers dan de
heteroseksuele clusters. Ct transmissiepatronen onder MSM en heteroseksuelen waren
grotendeels verschillend. Onze hypothese is dat deze verschillen het gevolg zijn van seksueel
gedrag van de gastheer, maar bacteriële of biologische gastheer factoren kunnen ook een
rol spelen.
Hoofdstuk 5: evaluaties van diagnostische testen voor soa’s
In hoofdstuk 5.1 evalueerden we een point-of-care test (POC) voor detectie van urogenitale
chlamydia bij 912 vrouwen in twee klinieken in Suriname. Er is grote behoefte aan dit soort
snelle goedkope en betrouwbare testen, met name in ontwikkelingslanden. Onze studie
toonde aan dat een eerder enthousiast ontvangen Chlamydia Rapid Test (CRT) niet goed
werkte, in tegenstelling tot in de studies die door de fabrikant waren betaald. In vergelijking
met de referentietest (nucleic acid amplification test (NAAT)) bleken de sensitiviteit en
specificiteit van de CRT respectievelijk 41% en 96%. De positief voorspellende waarde en
negatief voorspellende waarde waren respectievelijk 59% en 93%. De gevoeligheid van
de CRT was met name teleurstellend in monsters met weinig bacteriële Ct deeltjes (load)
vergeleken met de monsters met veel bacteriële Ct deeltjes. Dit duidt erop dat de CRT
209
met name faalt in het aantonen van chlamydia infecties met een lage load. Het aantal
humane cellen verschilde niet tussen waar-positieve en fout-negatieve CRT resultaten, dus
grondigheid van afname van het monster lijkt niet van invloed. Verbeterde POC zijn nodig
als zinvol diagnosticum om de ziektelast van chlamydia verminderen.
In hoofdstuk 5.2 hebben we in twee soa-poliklinieken in Nederland de test prestatie
en de patiënt acceptatie van een zelf-afgenomen rectaal uitstrijkje (ZRU) voor de diagnose
van Chlamydia trachomatis (Ct) en Neisseria gonorrhoeae (Ng) onderzocht onder 1458
MSM en 936 vrouwen, en vergeleken met een door de verpleegkundige afgenomen rectaal
uitstrijkje. De prevalentie van rectale Ct was 11% onder MSM en 9% bij de vrouwen. Rectale
Ng prevalentie was respectievelijk 7% en 2%. De ZRU voldeed goed voor het diagnosticeren
van Ct en Ng in beide groepen en was vergelijkbaar voor beide studie regio’s. Bijna alle mensen
zouden de soa-polikliniek opnieuw bezoeken als ZRU was standaard werd aangeboden. We
raden rectale screening aan als een essentieel onderdeel van een soa consult omdat anale
soa vaak voorkomen bij zowel MSM als vrouwen. We concludeerden dat ZRU een haalbaar,
valide, en acceptabel alternatief is voor anale bemonstering bij MSM en vrouwen die een
soa-polikliniek bezoeken. ZRU zou ook voor andere settings overwogen moeten worden.
Syfilis diagnostiek kan ingewikkeld zijn omdat het gebaseerd is op diverse bevindingen
zoals de klinische manifestatie, donker veld microscopie en serologie. Daarom onderzochten
we in hoofdstuk 5.3 de klinische waarde van een Treponema pallidum real-time PCR in
een soa-kliniek voor de vereenvoudiging van syfilis diagnostiek onder 716 patiënten met
verdenking op primaire syfilis en 133 patiënten met verdenking op secundaire syfilis.
We simuleerden een huisartspraktijk waar donkerveld microscopische diagnostiek niet
beschikbaar is. Goede overeenkomst werd gevonden tussen de T. pallidum real-time PCR en
standaard diagnostiek voor primaire syfilis, zowel in de soa- polikliniek als in de gesimuleerde
huisartspraktijk. De lage gevoeligheid van de T. pallidum real-time PCR voor de detectie
van secundaire syfilis is teleurstellend. We concludeerden dat de T. pallidum real-time PCR
een snelle, efficiënte en betrouwbare test is voor de diagnose van primaire syfilis in een
soa-polikliniek en een huisartspraktijk, maar het heeft geen toegevoegde waarde voor het
diagnosticeren van secundaire syfilis.
In hoofdstuk 6 wordt ingegaan op wat de bevindingen van de studies in dit proefschrift
toevoegen aan de reeds bestaande kennis en welke aanbevelingen voortvloeien uit
het onderzoek. Daarna volgt een discussie op basis van recente literatuur en worden
aanbevelingen gedaan ten aanzien van preventie maatregelen en voor toekomstig
onderzoek.
210
Appendix: Dankwoord
Dankwoord
D
it promotieonderzoek levert niet alleen een bijdrage aan de wetenschap, maar mede
door de samenwerking met zoveel mensen in de afgelopen jaren het heeft mij ook
verrijkt als persoon. Ik heb erg genoten van de samenwerking en op deze plek wil ik graag
iedereen hartelijk danken voor zijn of haar bijdrage aan dit proefschrift. Een aantal van hen
wil ik in het bijzonder noemen.
Als eerste gaat mijn dank uit naar alle deelnemers aan de diverse studies, in totaal ruim
38.000 personen. Zonder jullie medewerking had dit onderzoek nooit kunnen plaatsvinden.
I would like to thank all those who participated in the studies, without whom this research
would not have been possible.
Henry en Maria, jullie zijn twee heel verschillende personen maar ik zag bij jullie
als mijn promotores wel een aantal overeenkomsten. Jullie passie voor onderzoek is heel
inspirerend, evenals jullie onophoudelijke stroom van nieuwe onderzoeksideeën. Beiden
hebben jullie mij op een persoonlijke en motiverende wijze begeleid, waarvoor mijn hartelijke
dank. Het vertrouwen, de vrijheid en de mogelijkheden die jullie mij gegeven hebben om
mij te ontwikkelen als wetenschapper, waardeer ik zeer. Ik heb veel van jullie geleerd en
ik ben blij dat we onze samenwerking voortzetten. Henry, waar ter wereld jij ook bent, de
snelheid waarmee jij input levert op een vraag of een manuscript is bewonderenswaardig.
Maria, jouw epidemiologisch inzicht is enorm: dank dat je mij daar zoveel in hebt geleerd.
Roel, jij hebt mij heel even begeleid als promotor. Dank voor je scherpe inzichten en
stimulans om de analyses en resultaten zo simpel mogelijk weer te geven.
Ronald, copromotor, jouw grote statistische kennis en inzicht zijn zeer waardevol
geweest en je hebt zelfs nieuwe technieken ontwikkeld om de data uit de studies beter te
beschrijven. Dank voor al je geduldige uitleg; ik heb veel geleerd van alle discussies die we
hebben gevoerd over de juiste statistische methode en van jouw vaardigheid met R.
Geachte leden van de promotiecommissie, hartelijk dank voor uw bereidheid om
mijn proefschrift op zijn wetenschappelijke waarde te beoordelen en zitting te nemen in
de promotiecommissie. Highly esteemed Prof. Porter, dear Kholoud, thank you very much
for your willingness to review this thesis and for your presence as opponent at the defense
ceremony, I find it a great honour.
Alle coauteurs wil ik bedanken voor hun bijdrage aan de verschillende studies.
Reinier en Ray, in het bijzonder dank ik jullie voor de prettige samenwerking en voor alle
lab-inzichten die jullie met mij hebben gedeeld: wat een mooi teamwork om alle epi-data
met de lab-resultaten te koppelen.
Iedereen die betrokken was bij de CUSTEPA studie in Suriname, met name de
medewerkers van de Dermatologische Dienst en Stichting Lobi en in het bijzonder Antoon en
211
Leslie, wil ik heel hartelijk bedanken voor de samenwerking. Wat hebben we deze prachtige
studie uiteindelijk tot een goed einde kunnen brengen. Dank voor jullie gastvrijheid: het was
een onvergetelijke tijd. Ik hoop dat we onze samenwerking in de toekomst voort kunnen
zetten en dat er spoedig een goede chlamydia sneltest beschikbaar komt.
Members of CASCADE collaboration, thank you for welcoming me as junior researcher.
Co-authors, you all have so much knowledge. Thank you for sharing that with me, and for
your critical questions and input on the papers, always accompanied by kind words. Working
with you has been both inspiring and enjoyable.
Er zijn meer GGD-collega’s op een of andere manier betrokken geweest dan ik hier
persoonlijk kan noemen, maar jullie inbreng is zeer gewaardeerd.
Beste (oud-)collega’s van de afdeling onderzoek, met jullie heb ik het meeste meegemaakt
de afgelopen jaren en jullie zorgen voor een geweldige werksfeer! Dank voor alle
samenwerking, inhoudelijke discussies en gezelligheid, ook buiten werktijd.
Beste collega’s van de soa-polikliniek, jullie zijn een heel professioneel team en jullie
creativiteit en humor is ongeëvenaard. Dank voor jullie inzet bij de verschillende studies.
Beste collega’s van het streeklab, met name de afdeling moleculair en de administratie,
dank voor jullie praktische hulp en voor het meedenken in alle logistieke zaken.
Paranimfen, Jorien en Freke, wat fijn dat jullie tijdens de verdediging aan mijn zijde
staan. Jorien, lieve malaika, dank voor je vriendschap. Freke, mijn trouwe kamergenoot,
dank voor al je gezelligheid, het delen van ups en downs op onderzoeksgebied en je gedeelde
enthousiasme voor het ontdekken van nieuwe sneltoetsen.
Lieve vrienden, dank voor jullie interesse, aanmoedigingen en nuchtere adviezen de
afgelopen jaren tijdens dit promotietraject. Maar met name dank voor alle nodige afleiding
en relativering bij diners, weekendjes weg, borrels en feestjes, vakanties, kleedje-roseetjeavonden, theemomenten etc. Komt er nog een promovendouche?
Dearest friends, many thanks for your support along the way during this PhD-trajectory. I
have loved spending time with you, thank you for all those wonderful moments we have
had over the last couple of years. For the two of you whose influence is clearly visible in this
thesis a special thank you: Claire, thank you for your editing work. Sergei, many thanks for
the lay out and cover design of the thesis, I am proud of the result.
Lieve pap en mam, en lieve Jan, Marieke en Marleen, wat ben ik dankbaar dat jullie
mijn familie zijn. Jullie staan altijd voor mij klaar. Dank jullie wel voor alle liefde, steun en
interesse. Ik houd van jullie.
212
Appendix: Curriculum Vitae
Curriculum Vitae
J
annie van der Helm was born in Meppel, the Netherlands on April 5, 1980. After
graduating from secondary school (CSG Jan Arentsz, Alkmaar) she started her Bachelor
in Biomedical Science at the Radboud University (RU) Nijmegen in 2000. She completed
an internship at the department of Biochemistry at the Radboud Institute for Molecular
Life Sciences for which she received the RU student research prize in medical sciences. In
2003 she obtained her Bachelor of Science degree, majoring in Toxicology. Subsequently
she started a Masters of Science degree, majoring in Human Health Risk Assessment and
followed additional classes in Epidemiology. She performed internships at the Public Health
Service (GGD) Amsterdam, the GGD Hulpverlening Gelderland Midden in Arnhem, and at
the Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania. After her
graduation in 2006, she worked as datamanager at the Public Health Service Amsterdam
and two years later combined this with her PhD research, the results of which are presented
in this dissertation. At present, Jannie continues her research as a postdoctoral fellow at the
Public Health Service Amsterdam.
213
List of publications
Geraets DT, Grünberg AW, van der Helm JJ, Schim van der Loeff MF, Quint KD, Sabajo LO,
de Vries HJ. Cross-sectional study of genital carcinogenic HPV infections in Paramaribo,
Suriname: prevalence and determinants in an ethnically diverse population of women in a
pre-vaccination era. Sex Transm Infect. 2014 Jun 11. [Epub ahead of print]
De Vos AS, Coutinho RA, Prins M, van der Helm JJ, Kretzschmar MEE. Treatment as
prevention among injecting drug users; extrapolating from the Amsterdam cohort study.
AIDS. 2014 Mar 27;28(6):911-8
Bom RJ*, van der Helm JJ*, Bruisten SM, Grünberg AW, Schim van der Loeff MF, Sabajo LO,
de Vries HJ. The role of Surinamese migrants in the transmission of Chlamydia trachomatis
between Paramaribo, Suriname and Amsterdam, the Netherlands. PLoS One, 2013 Nov
13;8(11):e77977. *both authors contributed equally.
van der Helm JJ, Bom RJ, Grünberg AW, Bruisten SM, Schim van der Loeff MF, Sabajo
LO, de Vries HJ. Urogenital Chlamydia trachomatis Infections among Ethnic Groups in
Paramaribo, Suriname; Determinants and Ethnic Sexual Mixing Patterns. PLoS One. 2013 Jul
17;8(7):e68698.
van der Helm J, Geskus R, Sabin C, Meyer L, Del Amo J, Chêne G, Dorrucci M, Muga R,
Porter K, Prins M; CASCADE collaboration in EuroCoord. Effect Of HCV Infection On CauseSpecific Mortality Following HIV Seroconversion Before And After 1997. Gastroenterology.
2013 Apr;144(4):751-760.
de Vos AS, van der Helm JJ, Matser A, Prins M, Kretzschmar ME. Decline in incidence of HIV
and hepatitis C virus infection among injecting drug users in Amsterdam; evidence for harm
reduction? Addiction. 2013 Jan 24.
Bom RJ, van der Helm JJ, Schim van der Loeff MF, van Rooijen MS, Heijman T, Matser A,
de Vries HJ, Bruisten SM. Distinct Transmission Networks of Chlamydia trachomatis in Men
Who Have Sex with Men and Heterosexual Adults in Amsterdam, The Netherlands. PLoS
One. 2013;8(1):e53869.
van der Helm JJ, Sabajo LOA, Grunberg AW, Morré SA, Speksnijder AGCL, de Vries HJC.
214
Appendix: List of publications
Point-of-Care Test for Detection of Urogenital Chlamydia in Women Shows Low Sensitivity.
A Performance Evaluation Study in Two Clinics in Suriname. PLoS One. 2012; 7(2): e32122
De Vos A, van der Helm JJ, Prins M, Kretzschmar M. Determinants of persistent spread of
HIV in HCV-infected populations of injecting drug users. Epidemics 2012 June;4(2):57-67
Grady BPX, van den Berg CHSB, van der Helm JJ, Schinkel J, Coutinho RA, Krol A, Prins M. No
impact of hepatitis C virus infection on mortality among drug users during the first decade
after seroconversion. Clin Gastroenterol Hepatol. 2011 Sep;9(9):786-792.
van der Helm JJ, Prins M, Del Amo J, Bucher HCV, Chêne G, Dorrucci M, Gill J, Hamouda O,
Sannes M, Porter K, Geskus RB; on behalf of the CASCADE Collaboration. The hepatitis C
epidemic among HIV-positive MSM: incidence estimates from 1990 to 2007. AIDS 2011 May
15;25(8):1083-1091.
Heymans R*, van der Helm JJ*, de Vries HJ, Fennema HS, Coutinho RA, Bruisten SM. Clinical
value of Treponema pallidum real-time PCR for diagnosis of syphilis.J Clin Microbiol. 2010
Feb;48(2):497-502. Epub 2009 Dec 9. *both authors contributed equally.
de Vries HJ, van der Helm JJ, Schim van der Loeff MF, van Dam AP. Multidrug-resistant
Neisseria gonorrhoeae with reduced cefotaxime susceptibility is increasingly common in men
who have sex with men, Amsterdam, the Netherlands. Euro Surveill. 2009;14(37):pii=19330.
van der Helm JJ, Hoebe CJ, van Rooijen MS, Brouwers EE, Fennema HS, Thiesbrummel HF,
Dukers-Muijrers NH. High performance and acceptibility of self-collected rectal swabs for
diagnosis of Chlamydia trachomatis and Neisseria gonorrhoeae in men who have sex with
men and women. Sex Transm Dis. 2009 Aug;36(8):493-7
Heymans R, Kolader ME, van der Helm JJ, Coutinho RA, Bruisten SM. TprK gene regions are
not suitable for epidemiological syphilis typing. Eur J Clin Microbiol Infect Dis. 2009 Jul;28(7)
:875-8
de Vries HJ, Catsburg A, van der Helm JJ, Beukelaar EC, Morré SA, Fennema JS, Thiesbrummel
H. No indication of Swedish Chlamydia trachomatis variant among STI clinic visitors in
Amsterdam. Euro Surveill 2007; Feb8;12(2:)E070208.3.
215
Portfolio
AMC Graduate School for Medical Science – PhD Portfolio
Name PhD student: Jannie J. van der Helm
Name PhD supervisors: Prof. dr. H.J.C. de Vries and Prof. dr. M. Prins
Relevant training
Graduate school AMC Amsterdam
2012 R
2012 BROK/Good Clinical Practice
2011 Scientific writing
2009 Advanced biostatistics
Netherlands Intitute for Health Sciences (NIHES) Rotterdam
2009 Demography of Ageing
2009 Health Economics
2008 Topics in Meta-analysis
2008 Causal Inference
2007 Survival Analysis
Oral Presentations
ISHCI 13th International Symposium on Human Chlamydial Infections Pacific Grove
(California, USA, June 2014). What is the optimal time to retest STI clinic visitors with a
urogenital chlamydia infection?
AACM 9th Annual Amsterdam Chlamydia Meeting (Amsterdam, the Netherlands,
February 2014). By invitation: The role of Surinamese migrants in the transmission of
Chlamydia trachomatis between Paramaribo, Suriname and Amsterdam, the Netherlands.
NVED 15th Annual scientific meeting Nederlandse Vereniging voor Experimentele
Dermatologie (Lunteren, the Netherlands, January 2014). The role of Surinamese migrants in
the transmission of Chlamydia trachomatis between Paramaribo, Suriname and Amsterdam,
the Netherlands.
SPAOGS, AMC, GGD en SWOS in collaboration with AGIS (Paramaribo, Suriname,
November 2013) By invitation: Chlamydia urogenital infections in Paramaribo and
Amsterdam: A tale of two cities. Symposium Hepatitis C, Chlamydia, HPV.
Eurogin (Florence, Italy, November 2013). High-risk urogenital HPV infections in
216
Appendix: Portfolio
Paramaribo, Suriname: Prevalence and risk factors in an ethnically diverse population of
women.
NVTG Symposium Uniting Streams – Dutch Society for Tropical Medicine &
International Health (Amsterdam, the Netherlands, October 2013). By invitation: Chlamydia
urogenital infections in Paramaribo and Amsterdam: A tale of two cities.
WEON Werkgroep Epidemiologisch Onderzoek Nederland (Utrecht, the Netherlands,
June 2013). High-risk urogenital HPV infections in Paramaribo, Suriname: Prevalence and
risk factors among ethnic diverse women.
3rd Suriname/Dutch Conference on Tropical Dermatology (Paramaribo, Suriname,
April 2013). By invitation: Chlamydia urogenital infections in Paramaribo and Amsterdam: A
tale of two cities.
Nationaal congres Soa*Hiv*Seks (Amsterdam, the Netherlands, November 2012).
HIV self tests in combination with internet counselling: a low-treshold strategy to increase
diagnosis of HIV infections.
7th Etnische minderheden congres (Utrecht, the Netherlands, October 2012). HIV self
tests in combination with internet counselling: a low-treshold strategy to increase diagnosis
of HIV infections.
19th International AIDS conference (Washington DC, USA, July 2012). Announcing a
new method of HIV testing: the planning of robust home testing for HIV combined with
internet counselling.
7th meeting of the European Society for Chlamydia research (Amsterdam, the
Netherlands, July 2012). Urogenital Chlamydia trachomatis infection is a hyperendemic
disease in Paramaribo, Suriname. Results from a multiethnic society.
EASL International Liver Congress 2012 (Barcelona, Spain, April 2012). The effect of
HCV coinfection on cause-specific mortality following HIV seroconversion in the pre-cART
and cART eras.
NVED 13th Annual scientific meeting Nederlandse Vereniging voor Experimentele
Dermatologie (Lunteren, the Netherlands, February 2012). Urogenital Chlamydia trachomatis
is a hyperendemic disease in Paramaribo, Suriname; results from a multiethnic society.
Ministry of Health (Paramaribo, Suriname, January 2012). By invitation: CUSTEPA
study, results and future implications.
NVTG Symposium Uniting Streams – Dutch Society for Tropical Medicine &
International Health (Amsterdam, the Netherlands, September 2011). Urogenital Chlamydia
trachomatis is a hyperendemic disease in Paramaribo, Suriname; results from a multiethnic
society.
WEON Werkgroep Epidemiologisch Onderzoek Nederland (IJmuiden, the Netherlands, June 2011). The characterization of long-term non-progression of HIV-1 infection
since seroconversion.
217
CASCADE workshop (Pisa, Italy, May 2011). The characterization of long-term nonprogression of HIV-1 infection since seroconversion.
AACM 7th Annual Amsterdam Chlamydia Meeting (Amsterdam, the Netherlands,
December 2010). Results of the CUSTEPA study.
2nd Suriname/Dutch Conference on Tropical Dermatology (Paramaribo, Suriname,
November 2010). Results of the CUSTEPA study
2nd work conference Ministry of Health Suriname – Public Health Service Amsterdam
(Paramaribo, Suriname, August 2010). First results of the CUSTEPA study.
18th International AIDS conference (Vienna, Austria, July 2010). The characterization
of long-term non-progression of HIV-1 infection since seroconversion.
WEON Werkgroep Epidemiologisch Onderzoek Nederland (Nijmegen, the Netherlands, June 2010). Effect of Hepatitis C coinfection on cause-specific mortality following HIV
seroconversion in the pre- and HAART eras.
WEON Werkgroep Epidemiologisch Onderzoek Nederland (WEON) (Amsterdam, the
Netherlands, June 2009). The Hepatitis C epidemic among HIV-positive men who have sex
with men started before 2000; methodological considerations.
CASCADE workshop (Barcelona, Spain, May 2009). Incidence of HCV among MSM and
the effect of HCV on cause-specific mortality.
Verpleegkundig symposium 2008 (Amersfoort, the Netherlands, May 2008). Use of
vaginal herbal steambaths by Surinamese women.
CASCADE workshop (Krakow, Poland, May 2008). The effect of hepatitis B and hepatitis
C coinfection on HIV progression: methodological considerations.
Dutch Conference of Public Health (Groningen, the Netherlands, April 2008). High
performance and acceptability of self-collected anal swabs for diagnosis of Chlamydia
trachomatis and neisseria gonorrhoeae in men and women.
1st Suriname/Dutch Conference on Tropical Dermatology (Paramaribo, Suriname,
March 2008). CUSTEPA study, Urogenital Chlamydia Rapid Test Evaluation in Paramaribo
and Amsterdam.
Poster presentations as first author
STD & AIDS World Congress (Vienna, Austria, July 2013)
Van der Helm JJ, Geraets D, Grunberg AW, Quint K, Sabajo LOA, de Vries HJC. High-risk
urogenital HPV infections in Paramaribo, Suriname: Prevalence and risk factors among
ethnic diverse women.
Van der Helm JJ, Koekenbier RH, van Rooijen MS, de Vries HJC. What is the optimal
time to rescreen STI clinic visitors with a urogenital chlamydia infection?
NCHIV 6th Netherlands Conference on HIV Pathogenesis, Prevention and Treatment
218
Appendix: Portfolio
(Amsterdam, November 2012)
Van der Helm JJ, Geskus RB, Sabin C, Meyer L, del Amo J, Chêne G, Dorrucci M, Muga R,
Porter K, Prins M. Effect of Hepatitis C coinfection on cause-specific mortality following HIV
seroconversion in the pre-cART and cART eras
AIDS conference (Washington DC, USA, July 2012). Van der Helm JJ, Zuure FR, Fennema
JSA, Davidovich U, Prins M on behalf of the HIVtest@Home study group. Announcing a new
method of HIV testing: the planning of robust home testing for HIV combined with internet
counselling.
ISSTDR (Québec City, Canada, July 2011). Van der Helm JJ, Grunberg AW, Speksnijder
AGCL, de Vries HJC, Sabajo LOA. Urogenital Chlamydia trachomatis is a hyperendemic
disease in Paramaribo Suriname. Results from a multiethnic society.
Van der Helm JJ, Sabajo LOA, Morré SA, Grunberg AW, Speksnijder AGCL, de Vries
HJC. Novel Chlamydia trachomatis Point of Care rapid test shows low clinical sensitivity in
urogenital Chlamydia infections in Paramaribo, Suriname.
WEON (IJmuiden, the Netherlands, June 2011). Van der Helm JJ, Grunberg AW,
Speksnijder A, de Vries HJC, Sabajo LOA. Urogenital Chlamydia trachomatis is a hyperendemic
disease in Paramaribo Suriname. Results from a multiethnic society.
EASL (Berlin, Germany, March 2011). Van der Helm JJ, Prins M, del Amo J, Bucher HC,
Chêne G, Dorrucci M, Gill MJ, Hamouda O, Sannes M, Porter K, Geskus RB. The hepatitis C
epidemic among HIV-positive men who have sex with men: incidence estimates from 19902007.
IWHOD (Prague, Czech Republic, March 2011). 15th International workshop on HIV
observational databases. Van der Helm JJ, Geskus RB, Touloumi G, Prins M. Evaluation of
two strategies dealing with missing HCV status in a study on the effect of HCV coinfection on
mortality following HIV seroconversion.
NCHIV 4th Netherlands Conference on HIV Pathogenesis, Prevention and Treatment
(Amsterdam, November 2010). Van der Helm JJ, Geskus R, Sabin C, Meyer L, del Amo J,
Chêne G, Dorucci M, Muga R, Porter K, Prins M on behalf of the CASCADE Collaboration.
Effect of Hepatitis C coinfection on cause-specific mortality following HIV seroconversion in
the pre- and cART eras.
Van der Helm JJ, Lodi S, Porter K, Geskus R, Jansen I, Meyer L, Sabin C, Schuitemaker
H, Gunsenheimer-Bartmeyer B, d’Arminio-Monforte A, Prins M on behalf of the CASCADE
Collaboration. The characterization of long-term non- progression of HIV-1 infection since
seroconversion.
18th International AIDS conference (Vienna, Austria, July 2010). Van der Helm JJ,
Geskus R, Sabin C, Meyer L, del Amo J, Muga R, Porter K, Prins M on behalf of the CASCADE
Collaboration. Effect of Hepatitis C coinfection on cause-specific mortality following HIV
seroconversion in the pre- and cART eras.
219
IWHOD 14th International workshop on HIV observational databases (Sitges, Spain,
March 2010). Van der Helm JJ, Jansen I, Porter K, Geskus R, Lodi S, Meyer L, Sabin C,
Schuitemaker H, Gunsenheimer-Bartmeyer B, d’Arminio Monforte A, Prins M on behalf of
The characterization of long-term non-progression of HIV-1 infection since
seroconversion.
CROI 17th Conference on retroviruses and opportunistic infections (San Francisco,
USA, February 2010). Van der Helm JJ, Geskus RB, del Amo J, Chêne G, Gill J, Hamouda O,
Sannes M, Porter K, Prins M. The Hepatitis C epidemic among HIV-positive men who have
sex with men started before 2000.
NCHIV 3rd Netherlands Conference on HIV Pathogenesis, Prevention and Treatment
(Amsterdam, November 2009) Van der Helm JJ, Geskus RB, del Amo J, Porter K, Prins M. The
Hepatitis C epidemic among HIV-positive men who have sex with men started before 2000.
ISSTDR 18th International society for STD research (London, UK, June 2009). Van der
Helm JJ, Roekevisch E, Stolte I, de Vries HJC.
Trends over time in risk behaviour of MSM with LGV proctitis. Does the epidemic
spread into the community at large? Van der Helm JJ, Geskus RB, del Amo J, Porter K, Prins
M. The Hepatitis C epidemic among HIV-positive men who have sex with men started before
2000.
Chlamydia research 6th meeting of the European Society for Chlamydia research
(Aarhus, Denmark, July 2008). van der Helm JJ, Brouwers E, van Rooijen M, Hoebe
CJP, Fennema JSA, Thiesbrummel HFJ, Dukers-Muijrers NHTM. High performance and
acceptability of self-collected anal swabs for diagnosis of Chlamydia trachomatis and
neisseria gonorrhoeae in men and women.
ECCMID 2008 18th European Congress of Clinical Microbiology and Infectious
Diseases (Barcelona, Spain April 2008) van der Helm JJ, Brouwers E, van Rooijen M,
Hoebe CJP, Fennema JSA, Thiesbrummel HFJ, Dukers-Muijrers NHTM. High performance
and acceptability of self-collected anal swabs for diagnosis of chlamydia trachomatis and
neisseria gonorrhoeae in men and women.
Teaching
Lectures ‘Confounding and effect modification’ in the course ‘Epidemiology’ for students
Medical Biology, University of Amsterdam, Amsterdam, the Netherlands (March 2009, 2010
and 2011).
220
Appendix: Portfolio
Parameters of Esteem
Prizes
2013 Amsterdam Medical Centre (AMC) Award Societal Impact of Research 2013. Second
prize in appreciation of her outstanding and well targeted activities for societal impact in
Public Media in 2012.
2010 Best poster award at the 14th International Workshop for HIV Observational Databases,
Sitges, Spain for the poster on the characterization of long-term non-progression of HIV-1
infection since seroconversion.
Scholarships
2012 EASL Young Investigator Bursary to attend the International Liver Congress, Barcelona,
Spain, April 18-22.
2011 Scholarship to attend the 19th ISSTDR, Québec City, Canada, July 10-13.
2010 Scholarship Award to attend the 18th International AIDS Conference, Vienna, Austria,
July 18-23.
2010 Young Investigator Award to attend the 17th Conference on Retroviruses and
Opportunistic Infections, San Francisco, USA, February 16-19.
Grants
Co-applicant with Freke Zuure. PI Prof. dr. Maria Prins. HIV self testing combined with
internet counselling: a low threshold strategy to increase diagnoses of HIV-infections. From
ZonMw; 2011; Project number 200320018.
221
222
Notes
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