What is the impact of variability of immunosuppressive exposure on outcomes?

Transcription

What is the impact of variability
of immunosuppressive exposure
on outcomes?
Professor Teun van Gelder
Departments of Hospital Pharmacy and Internal Medicine
Erasmus Medical Center
Rotterdam
The Netherlands
Prescribing information is available in the booklet
in the meeting folder
The step programme is funded and developed by Astellas Pharma Europe Ltd
ADV/13/0078/Eud October 2013
Amsterdam
Rotterdam
Defining success in transplant therapy
 The goal for transplant therapy is to prevent and treat rejection of the
graft and maintain graft survival and function over the long term
 Long-term success following transplantation depends upon appropriate
and consistent exposure to a combination of immunosuppressive drugs1
 Tacrolimus has a narrow therapeutic index, which results in a tightly
defined range of optimal drug exposure2−4
 However, variability in tacrolimus exposure has been reported,5
highlighting the need for strategies to ensure patients have consistent
exposure to tacrolimus
1. Cervelli M, Russ G. Aus J Pharmacy 2012;93:83‒86; 2. Hesselink DA et al. Pharmacogenomics
2005;6:323−37; 3. ADVAGRAF Summary of Product Characteristics; 4. EMA: Scientific Discussion, 2007; 5.
Scott LJ et al. Drugs 2003;63:1247‒1297
What is variability of immunosuppressive
exposure and why does it occur?
Oral bioavailability of CNIs varies:1–6
•
•
Between different patients (inter-patient variability)
–
Age, gender, race, weight
–
Genetic polymorphisms (CYP3A5)
–
Drug−drug interactions (azoles, ritonavir)
–
Liver dysfunction
Within a given patient (intra-patient variability)
–
Non-adherence
–
Gastrointestinal metabolism & motility
–
Diarrhoea
–
Food & drug interactions
–
Assay variability
1. Venkataramanan R et al. Clin Pharmacokinet 1995;29:404–430.; 2. Schiff J et al. Clin J Am Soc Nephrol 2007;2:374–384;
3. Antignac M et al. Br J Pharmacol 2007;64:750–757; 4. de Jonge H et al. Ther Drug Monit 2009;31:416–435; 5. Scholten
EM et al. Kidney Int 2005;67:2440–2447; 6. Vasquez EM et al. Am J Health Syst Pharm 2003;60:266–269
What causes variability in exposure to tacrolimus?
Absorption and metabolism of tacrolimus
 Mean oral bioavailability of tacrolimus is ~25%1,2
 Membrane transporter P-glycoprotein (P-gP), and metabolic enzyme
cytochrome P450 3A4 (CYP3A4) remove ~50% of the dose from the gut1,2
 Hepatic CYP3A4 removes a further 10%1,2
Adapted from
Cervelli 20122
1. Undre NA. Nephrol Dial Transplant 2003;18(Suppl1):i12‒15; 2. Cervelli M, Russ G. Aus J Pharmacy 2012;93:83‒86
Pharmacogenetics
1
 Genetic polymorphisms in genes encoding CYP3A5, and to a lesser extent
2
3
CYP3A4, affect inter-patient variability
CYP3A5 allele
Consequence4
Prevalence*5
Homozygous CYP3A5*1
Normal metaboliser
0%
Homozygous CYP3A5*3
Slow metaboliser
Requires lower doses to maintain trough levels
89%
Heterozygous
(CYP3A5*1/3*)
Intermediate metaboliser
Requires intermediate doses to maintain trough levels
11%
*in 136 kidney transplant patients5
 It has been suggested that intra-patient variability is also correlated with the
CYP3A5 genotype,6 although other studies dispute this correlation3
 Genetic polymorphisms in genes encoding P-gP (MDR1) may also affect
inter-patient variability, but this remains controversial7
1. Staatz CE et al. Clin Pharmacokinet 2010;49:141‒175; 2. Ellens L et al. Clin Chem 2011;57:1574‒1583; 3. Pashaee N et al. Ther Drug Monit
2011;33:369‒371; 4. Larriba J et al. Tranplant Proc 2010;42:257‒259; 5. Stratta P et al. Eur J Clin Pharmacol 2012;68:671‒680;18:339-348; 6. Yong
Chung J et al. Ther Drug Monit 2010;32:67−72; 7. Li Y et al. Transpl Immunol 2012;27:12‒18
Dose-corrected tacrolimus C0
(n=26)
(n=110)
Hesselink DA et al. Pharmacogenetics and Genomics 2008;18:339–348
Variability can be identified by verifying patients’ past
trough levels in relation to a constant dose
CV% calculation
High variability
Low variability
Tacrolimus daily dose (mg/day)
Target trough (ng/mL)
Visit 1
5
6.2
Visit 1
Tacrolimus daily dose (mg/day)
5
Target trough (ng/mL)
6
Visit 2
5
7.9
Visit 2
5
6.8
Visit 3
5
5.2
Visit 3
5
5.5
Visit 4
5
8.5
Visit 4
5
5.8
Visit 5
5
4.9
Visit 5
5
5.3
SD
1.60
MEAN
6.54
CV
25%
SD
0.58
MEAN
5.88
CV
10%
(Illustrative example)
Variability is a marker of inconsistent exposure, and can
serve as a predictor of poor outcome
TACROLIMUS TROUGH LEVELS OVER TIME IN TWO DIFFERENT PATIENTS
(ILLUSTRATIVE EXAMPLE)
High variability SD >2ng/ml
ng/ml
Low variability SD <2ng/ml
Trough level
8
Mean
Tightening trough
levels results in
a lower mean
5
Tacrolimus trough values over time
Is high variability in CNI exposure a risk factor
for poor long-term outcomes?
Acute
rejection1,2,6
Reduced longterm graft
survival2,5,6
Chronic
rejection3
High
variability in
CNI exposure
Decreased renal
function2,6
Interstitial
fibrosis and
tubular atrophy4
1. Stevenson KS et al. Congress of the European Society for Organ Transplantation 2011. Oral presentation MO–021; 2. Waiser J
et al. Nephrol Dial Transplant 2002;17:1310–1317; 3. Kahan BD et al. J Am Soc Nephrol 2000;11:1122–1131; 4. Stoves J et al.
Transplantation 2002;74:1794–1797; 5. Borra LCP et al. Nephrol Dial Transplant 2010;25:2757–2763; 6. Whalen H et al. Congress
of the European Society for Organ Transplantation 2013. Abstract P076
High intra-patient variability in tacrolimus
exposure is a strong predictor of graft loss1
Cumulative survival (%)
INFLUENCE OF VARIABILITY IN TACROLIMUS CLEARANCE ON GRAFT LOSS 12 MONTHS POST-TRANSPLANT
• 70.6% of graft failures occurred
in the patients with high intrapatient variability
Low variability (≤median variability)
Post-transplant years
High variability (>median variability)
Composite endpoint ‘graft failure’: 1. graft loss, 2. biopsy-proven chronic allograft nephropathy and 3. doubling of plasma
creatinine concentration between 12 months post-transplant and last follow-up
Variability (%) : sum of (mean trough tacrolimus plasma concentration minus each individual plasma concentration) /mean
plasma concentration x100 (plasma concentrations measured at outpatient clinic up to 12 months post-transplant)
1. Borra LCP et al. Nephrol Dial Transplant 2010;25:2757–2763
High intra-patient variability in tacrolimus exposure negatively
impacts acute rejection, renal function and graft survival1
Acute rejection
eGFR*
P=0.0059
RR = 2.6
P=0.001
RR = 0.9
LV n=10/125; HV n=25/122
LV n=125; HV n=122
Low variability <16%
Graft loss
P=0.0182
RR = 82.5
LV n=1/125; HV n=8/122
High variability >16%
*SDs were 19.73 and 21.41 in the LV and HV group, respectively; HV was defined as variability > observed median and low variability as < observed median (median variability of
tacrolimus trough levels = 16%)
RR, relative risk, calculated by dividing percentage in high variability group by percentage in low variability group
1. Clancy M et al. Congress of the European Society for Organ Transplantation 2013. Abstract P076
Targeting and maintaining tacrolimus trough levels within
target range is a constant challenge in transplantation
• Even in the Symphony study, 40−50% of pts were outside target range1
Tacrolimus trough
level [ng/mL]
– Only 11% of patients on low-dose tacrolimus were within target range at all
times during the first 2 months after transplantation1
12
Low-dose tacrolimus (N=401)3
10
8
6
4
2
0
0
4
8 12 16 20 24 28 32 36 40 44 48 52
Weeks
‘One important reason why it is difficult to keep
levels within target ranges is intra-patient variability’1
Intra-patient CV: 28%
Inter-patient CV: 42%2
(patients receiving 6mg/day of Tac)
1. Ekberg H et al. Transplantation 2009;87:1360−1366
2. Ekberg H et al. Nephrol Dial Transplant 2010;25;2004–2010
3. Ekberg H et al. New Eng J Med 2007;357:2562-2575
Adapted from
Identifying patients with high variability in
tacrolimus exposure
 Due to the influence of various factors,
it is difficult to predict which patients
are likely to have high variability in
tacrolimus exposure1
Intra-patient
variability can be
difficult to predict1
Lack of standardised protocols
Diverse mechanisms responsible
for variability
(eg adherence, GI motility)
Differences in assay
methodology/timing
1. Cervelli M, Russ G. Aus J Pharmacy 2012;93:83–86
Non-adherence
 A single forgotten dose of tacrolimus can immensely impact steady-state
exposure1
 30% decrease in trough level
 20% of total exposure (AUC) is lost in the next five dosing intervals
 3−5 doses are necessary to restore the steady state
1. Saint-Marcoux F et al. Am J Transplant 2013;S5:111 (Abstract 263)
Problems with measuring tacrolimus variability
When it comes to identifying patients with high/low variability,
several issues should be considered
 How often are tacrolimus trough levels measured?
 How many measurements are needed and over what time period?
 Last 2–3 measurements?
 Measurements over the past 2 years?
 Clinicians may not have access to historical patient data
 Calculating CV or SD requires a stable dose
 Dose adjustments need to be considered
 Calculating CV can be complex
 Other potential methods focusing on outliers may be beneficial
The lower the target trough concentrations, the lower
the margin for variation
[7.5–12.5]  SD 2.5
Target troughs ng/mL
10
[5.3–8.8]  SD 1.8
7
•
Symphony study:
mean 6.5ng/mL1
[3–5]  SD 1
4
0
1
2
Margin for variation (ng/mL)
•
There is less room for variability when targeting low tacrolimus trough levels
• CNI minimisation requires stable tacrolimus levels
Illustrative figure based on value of mean tac trough from Ekberg H et al. Am J Transplant 2009;9:1876–1885
Summary
• High within-patient variability in tacrolimus exposure is a
significant risk factor for graft loss
• Variability can be inter- (between patients) and intra- (within
a given patient) and is caused by a number of factors in
addition to non-adherence
• It is difficult to predict which patients will have high
variability
• Reduced variability may improve long-term outcomes and
facilitate targeting of low tacrolimus levels

What is the impact of variability of immunosuppressive exposure on outcomes?

Transcription

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