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 The step programme is funded and developed by Astellas Pharma Europe Ltd ADV/13/0078/Eud October 2013 Rotterdam The step programme is funded and developed by Astellas Pharma Europe Ltd ADV/13/0078/Eud October 2013 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 The step programme is funded and developed by Astellas Pharma Europe Ltd ADV/13/0078/Eud October 2013 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 The step programme is funded and developed by Astellas Pharma Europe Ltd ADV/13/0078/Eud October 2013 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 The step programme is funded and developed by Astellas Pharma Europe Ltd ADV/13/0078/Eud October 2013 What causes variability in exposure to tacrolimus? 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 The step programme is funded and developed by Astellas Pharma Europe Ltd ADV/13/0078/Eud October 2013 Dose-corrected tacrolimus C0 (n=26) (n=110) Hesselink DA et al. Pharmacogenetics and Genomics 2008;18:339–348 The step programme is funded and developed by Astellas Pharma Europe Ltd ADV/13/0078/Eud October 2013 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) The step programme is funded and developed by Astellas Pharma Europe Ltd ADV/13/0078/Eud October 2013 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 The step programme is funded and developed by Astellas Pharma Europe Ltd ADV/13/0078/Eud October 2013 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 The step programme is funded and developed by Astellas Pharma Europe Ltd ADV/13/0078/Eud October 2013 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 The step programme is funded and developed by Astellas Pharma Europe Ltd ADV/13/0078/Eud October 2013 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 The step programme is funded and developed by Astellas Pharma Europe Ltd ADV/13/0078/Eud October 2013 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 The step programme is funded and developed by Astellas Pharma Europe Ltd ADV/13/0078/Eud October 2013 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 The step programme is funded and developed by Astellas Pharma Europe Ltd ADV/13/0078/Eud October 2013 What causes variability in exposure to tacrolimus? 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) The step programme is funded and developed by Astellas Pharma Europe Ltd ADV/13/0078/Eud October 2013 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 step programme is funded and developed by Astellas Pharma Europe Ltd ADV/13/0078/Eud October 2013 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 The step programme is funded and developed by Astellas Pharma Europe Ltd ADV/13/0078/Eud October 2013 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 The step programme is funded and developed by Astellas Pharma Europe Ltd ADV/13/0078/Eud October 2013
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