Population pharmacokinetics and Bayesian estimation of mycophenolate mofetil in patients with autoimmune hepatitis.

AIMS: Mycophenolate mofetil (MMF) is the most widely used second-line agent in autoimmune hepatitis (AIH). Individual dose adjustment of MMF may avoid adverse outcomes while maximizing efficacy. The aim of the present study was to develop population pharmacokinetic (popPK) models and maximum a posteriori Bayesian estimators (MAP-BEs) to estimate mycophenolic acid interdose area under the curve in AIH patients administered MMF using nonlinear mixed effect modelling. METHODS: We analysed 50 mycophenolic acid PK profiles from 34 different patients, together with some demographic, clinical, and laboratory test data. The median number of plasma samples per profile, immediately preceding and following the morning MMF dose, was 7. PopPK modelling was performed using parametric, top-down, nonlinear mixed effect modelling with NONMEM 7.3. MAP-BEs were developed based on the best popPK model and the best limited sampling strategy selected among several. RESULTS: The pharmacokinetic data were best described by a 2-compartment model, Erlang distribution to describe the absorption phase, and a proportional error. The mean (relative standard error) of popPK parameter estimates of clearance, intercompartmental clearance, central volume and absorption rate with the final model were: 21.6 L h-1 (11%), 22.7 L h-1 (19%), 35.9 L (21%) and 8.7 h-1 (9%), respectively. The peripheral volume was fixed to 300 L. The best MAP-BE relied on the limited sampling strategy at 0.33, 1 and 3 hours after MMF dose administration and was very accurate (bias = 5.6%) and precise (root mean squared prediction error <20%). CONCLUSION: The precise and accurate Bayesian estimator developed in this study for AIH patients on MMF can be used to improve the therapeutic management of these patients.

Evaluation of Longitudinal Exposure to Tacrolimus as a Risk Factor of Chronic Kidney Disease Occurrence Within the First-year Post-Liver Transplantation.

BACKGROUND: Renal failure is predictive of mortality in the early postliver-transplantation period and calcineurin inhibitors toxicity is a main challenge. Our aim is to assess the impact of longitudinal tacrolimus exposure (TLE) and other variables on chronic kidney disease (CKD)-free 1-year-survival. METHODS: Retrospective data of consecutive patients transplanted between 2011 and 2016 and treated with tacrolimus were collected. TLE and all relevant pre- and post-liver transplantation (LT) predictive factors of CKD were tested and included in a time-to-event model. CKD was defined by repeated estimated glomerular filtration rate (eGFR) values below 60 mL/min/1.73m2 at least for the last 3 months before M12 post-LT. RESULTS: Data from 180 patients were analyzed. CKD-free survival was 74.5% and was not associated with TLE. Pre-LT acute kidney injury (AKI) and eGFR at 1-month post-LT (eGFRM1) <60 mL/min/1.73m2 were significant predictors of CKD. By distinguishing 2 situations within AKI (ie, with or without hepatorenal syndrome [HRS]), only HRS-AKI remained associated to CKD. HRS-AKI and eGFRM1 <60 mL/min/1.73m2 increased the risk of CKD (hazard ratio, 2.5; 95% confidence interval, 1.2-4.9; hazard ratio, 4.8; 95% confidence interval, 2.6-8.8, respectively). CONCLUSIONS: In our study, TLE, unlike HRS-AKI and eGFRM1, was not predictive of CKD-free survival at 1-year post-LT. Our results once again question the reversibility of HRS-AKI.

Adherence profiles in kidney transplant patients: Causes and consequences.

OBJECTIVE: Adherence is a dynamic phenomenon and a critical determinant of transplant patients outcome. The objective of this longitudinal study was to explore adherence in kidney transplant patients followed-up for up to three years after transplantation. METHODS: Adherence was repeatedly estimated using the Morisky-Green-Levine 4-Item Medication Adherence Scale, in two successive cohorts of 345 (EPIGREN) and 367 (EPHEGREN) kidney transplant recipients. Mixed effect modeling with latent processes and latent classes was used to describe adherence time-profiles. RESULTS: Two latent classes were identified. The adherent class represented 85% of the patients. Patients of the poorer-adherence class displayed a lower adherence at one month (p<10-3), which worsened over time. Good adherence was associated with age >50 years, fewer depression episodes (5% vs. 13%, p = 0.001) and a better mental health component of quality of life (MCS-SF36 47 ±â€¯11 vs. 41 ±â€¯13, p = 0.015). Survival without acute rejection episodes was longer in the adherent class (p = 0.004). CONCLUSIONS: The risk of poor adherence in renal transplant patients can be detected as early as one month post-transplantation, using appropriate and easy tools adapted to routine monitoring. PRACTICE IMPLICATIONS: An early focus on vulnerable patients should allow putting into place actions in order to reduce the risk of poor outcome related to poor adherence.

A Prognostic Tool for Individualized Prediction of Graft Failure Risk within Ten Years after Kidney Transplantation.

Identification of patients at risk of kidney graft loss relies on early individual prediction of graft failure. Data from 616 kidney transplant recipients with a follow-up of at least one year were retrospectively studied. A joint latent class model investigating the impact of serum creatinine (Scr) time-trajectories and onset of de novo donor-specific anti-HLA antibody (dnDSA) on graft survival was developed. The capacity of the model to calculate individual predicted probabilities of graft failure over time was evaluated in 80 independent patients. The model classified the patients in three latent classes with significantly different Scr time profiles and different graft survivals. Donor age contributed to explaining latent class membership. In addition to the SCr classes, the other variables retained in the survival model were proteinuria measured one-year after transplantation (HR=2.4, p=0.01), pretransplant non-donor-specific antibodies (HR=3.3, p<0.001), and dnDSA in patient who experienced acute rejection (HR=15.9, p=0.02). In the validation dataset, individual predictions of graft failure risk provided good predictive performances (sensitivity, specificity, and overall accuracy of graft failure prediction at ten years were 77.7%, 95.8%, and 85%, resp.) for the 60 patients who had not developed dnDSA. For patients with dnDSA individual risk of graft failure was not predicted with a so good performance.

An adjustable predictive score of graft survival in kidney transplant patients and the levels of risk linked to de novo donor-specific anti-HLA antibodies.

Most predictive models and scores of graft survival in renal transplantation include factors known before transplant or at the end of the first year. They cannot be updated thereafter, even in patients developing donor-specific anti-HLA antibodies and acute rejection.We developed a conditional and adjustable score for prediction of graft failure (AdGFS) up to 10 years post-transplantation in 664 kidney transplant patients. AdGFS was externally validated and calibrated in 896 kidney transplant patients.The final model included five baseline factors (pretransplant non donor-specific anti-HLA antibodies, donor age, serum creatinine measured at 1 year, longitudinal serum creatinine clusters during the first year, proteinuria measured at 1 year), and two predictors updated over time (de novo donor-specific anti-HLA antibodies and first acute rejection). AdGFS was able to stratify patients into four risk-groups, at different post-transplantation times. It showed good discrimination (time-dependent ROC curve at ten years: 0.83 (CI95% 0.76-0.89).

Anti-hepatitis C virus drugs and kidney.

Hepatitis C virus (HCV) mainly targets the liver but can also induce extrahepatic manifestations. The kidney may be impacted via an immune mediated mechanism or a cytopathic effect. HCV patients are clearly at a greater risk of chronic kidney disease (CKD) than uninfected patients are, and the presence of CKD increases mortality. Interferon-based therapies and ribavirin are difficult to manage and are poorly effective in end-stage renal disease and hemodialysis. These patients should be given priority treatment with new direct anti-viral agents (DAAs) while avoiding peginterferon and ribavirin. The first results were convincing. To aid in the correct use of these drugs in patients with renal insufficiency, their pharmacokinetic properties and potential renal toxicity must be known. The renal toxicity of these new drugs was not a safety signal in clinical trials, and the drugs are generally efficient in these frail populations. These drugs are usually well tolerated, but recent cohort studies have demonstrated that these new regimens may be associated with renal side effects, especially when using sofosbuvir combinations. HCV, renal diseases and comorbidities are intimately linked. The close monitoring of renal function is required, particularly for at-risk patients (transplanted, HIV-coinfected, CKD, hypertensive or diabetic patients). New DAA regimens, which will soon be approved, will probably change the landscape.

Efficiency and Safety of an Early Dose Adjustment of Ribavirin in Patients Infected With Hepatitis C Underexposed to the Drug and Treated With Peginterferon Ribavirin.

BACKGROUND: Ribavirin exposure after the first dose (D0AUC0-4h) >1755 mcg·h·L is predictive of sustained virological response (SVR) in patients with hepatitis C treated with peginterferon and ribavirin. The aim of this study was to test the benefit of ribavirin early dose adjustment based on this target in naïve patients infected with genotype 1. METHODS: A multicenter randomized controlled trial with two parallel groups; fixed-dose (FD) group: standard of care in 2010-2011, ie, peginterferon-α2a 180 mcg·wk and weight-based ribavirin 1000-1200 mg/d during 48 weeks; adapted-dose (AD) group: increase of ribavirin dose if D0AUC0-4h <1755 mcg·h·L. RESULTS: A total of 221 patients were included, 110 in the AD group and 111 in the FD group with similar baseline characteristics. In the perprotocol analysis, SVR was higher in the AD group (55.1% versus 40.4%; P = 0.042), especially in patients with D0AUC0-4h <1755 mcg·h·L (54.3% versus 31.9%; P = 0.029). In the intention-to-treat analysis, the difference was not significant (50% versus 41%; P = 0.197). Ribavirin trough concentrations (C0s) at week 4 of treatment (intention-to-treat analysis) were higher in patients achieving SVR (2.06 versus 1.72 mg/L, P = 0.003). In the subgroup of patients with AUC0-4h <1755 mcg·h·L, 46% of patients with AD achieved a C0 >2.0 mg/L versus 22% of patients with FD (P = 0.013). Grade 1 anemia (but not other grades) was more frequent in the AD group (70% versus 48%, P = 0.001). The number of dose reductions or discontinuation of ribavirin was similar in both groups. CONCLUSIONS: Early ribavirin dose adjustment increases SVR in patients underexposed to ribavirin without increasing grade II-IV anemia. Such a strategy could be useful in patients with no access to new antiviral drugs.

Validation of the psychometrics properties of a French quality of life questionnaire among a cohort of renal transplant recipients less than one year.

BACKGROUND: Renal transplantation is considered as the treatment of choice for patients with end-stage renal disease. Health-related quality of life (HRQoL) of renal transplant recipients (RTR) is very important to assess, especially during the first year after transplantation. To provide new evidence about the suitability of HRQoL measures in RTR during the first post-transplant year, we explored the internal structure, reliability and external validity of a French specific HRQoL instrument, the Renal Transplant Quality of life Questionnaire Second Version (RTQ V2). METHODS: The data were issued from the French multicenter cohort of renal transplant patients followed during 4 years (EPIGREN). The HRQoL of RTR was assessed five times (at 1, 3, 6, 9 and 12 months after transplantation) with the RTQ V2, a specific instrument consisting of 32 items describing five dimensions. Socio-demographic information, clinical characteristics and HRQoL (i.e., RTQ V2 and SF-36) were collected. For the five times, psychometric properties of the RTQ V2 were compared to those reported from the reference population assessed in the validation study. RESULTS: Three hundred and thirty-four patients were enrolled. The proportions of well-projected items, item-internal consistency, item-discriminant validity, floor and ceiling effects, Cronbach's alpha coefficients and item goodness-of-fit statistics were satisfactory for each dimension at the five times of the study. The suitability indices of construct validity were higher than 90 % for each time (minimum-maximum: 90.8-97.4 %). The external validity was less satisfactory, with a suitability indices ranged from 46.7 % at M1 to 66.7 % at M12. However, the discrepancies with the reference population (mainly for the gender) appeared logical considering the scientific literature on HRQoL of RTR during the first post-transplant year and may not compromise the external validity. CONCLUSION: These results support the validity and reliability of the RTQ V2 for evaluating HRQoL in RTR during the first post-transplant year, and confirm that the RTQ V2 is a useful tool to assess the HRQoL precociously after transplant.

Ribavirin: Past, present and future.

Before the advent of direct acting antiviral agents (DAAs) ribavirin, associated to pegylated-interferon played a crucial role in the treatment of chronic hepatitis C, preventing relapses and breakthroughs. In the present era of new potent DAAs, a place is still devoted to the drug. Ribavirin associated with sofosbuvir alone is efficient in the treatment of most cases of G2 infected patients. All options currently available for the last difficult-to-treat cirrhotic G3 patients contain ribavirin. Reducing treatment duration to 12 wk in G1 or G4 cirrhotic compensated patients is feasible thanks to ribavirin. Retreating patients with acquired anti NS5A resistance-associated variants using ribavirin-based strategies could be useful. The addition of ribavirin with DAAs combinations however, leads to more frequent but mild adverse events especially in cirrhotic patients. Preliminary data with interferon-free second generation DAAs combinations without ribavirin suggest that future of the drug is jeopardized even in difficult-to-treat patients: The optimization of ribavirin dosage according to an early monitoring of blood levels has been suggested to be relevant in double therapy with peginterferon or sofosbuvir but not with very potent combinations of more than two DAAs.

Evolution and Determinants of Health-Related Quality-of-Life in Kidney Transplant Patients Over the First 3 Years After Transplantation.

BACKGROUND: Health-related quality of life (HRQOL) usually improved after kidney transplantation; however, a non-negligible number of patients did not benefit from transplantation in HRQOL. The aims of this cohort study were to describe the evolution of HRQOL in kidney transplant recipients to search for subgroups with distinct time profiles and to investigate these determinants. METHODS: Three hundred thirty-seven adult patients were followed up from 1 to 36 months after kidney transplantation. Each patient completed repeated HRQOL assessments (median, 5; range, 2-9). K-means for longitudinal data was used to identify homogeneous clusters of HRQOL time profiles obtained for the mental and physical composite scores (MCS and PCS) and for the 8 dimensions of the short-form 36 scale. Covariates associated with these clusters were investigated using random forest analysis. Magnitude and shape of the HRQOL variations over time were investigated using linear regression mixed models. RESULTS: Two longitudinal clusters were identified for the time profiles of PCS and MCS. Patients classified in the higher cluster (ie, 60% of the population) exhibited a steady-state HRQOL, similar on average to the general population, whereas in the lower cluster, PCS and MCS scores were significantly lower than in the general population. Muscular weakness in the first year after transplantation explained 19% of the interpatient variability of PCS 3 months after transplantation, whereas associated with anxiety, it explained 24% of interpatient MCS variability. CONCLUSIONS: This work suggests to promote (i) physical rehabilitation programs after transplantation to curb the muscular loss and (ii) systematic attention to the patient's anxiety.

The PROPKD Score: A New Algorithm to Predict Renal Survival in Autosomal Dominant Polycystic Kidney Disease.

The course of autosomal dominant polycystic kidney disease (ADPKD) varies among individuals, with some reaching ESRD before 40 years of age and others never requiring RRT. In this study, we developed a prognostic model to predict renal outcomes in patients with ADPKD on the basis of genetic and clinical data. We conducted a cross-sectional study of 1341 patients from the Genkyst cohort and evaluated the influence of clinical and genetic factors on renal survival. Multivariate survival analysis identified four variables that were significantly associated with age at ESRD onset, and a scoring system from 0 to 9 was developed as follows: being male: 1 point; hypertension before 35 years of age: 2 points; first urologic event before 35 years of age: 2 points; PKD2 mutation: 0 points; nontruncating PKD1 mutation: 2 points; and truncating PKD1 mutation: 4 points. Three risk categories were subsequently defined as low risk (0-3 points), intermediate risk (4-6 points), and high risk (7-9 points) of progression to ESRD, with corresponding median ages for ESRD onset of 70.6, 56.9, and 49 years, respectively. Whereas a score ≤3 eliminates evolution to ESRD before 60 years of age with a negative predictive value of 81.4%, a score >6 forecasts ESRD onset before 60 years of age with a positive predictive value of 90.9%. This new prognostic score accurately predicts renal outcomes in patients with ADPKD and may enable the personalization of therapeutic management of ADPKD.

eGFR decrease during antiviral C therapy with first generation protease inhibitors: a clinical significance?

BACKGROUND & AIMS: Renal toxicity of first generation protease inhibitors (PIs) was not a safety signal in phase III clinical trials, but was recently reported in recent studies. It appeared important to determine the clinical significance of these findings. METHODS: We retrospectively analysed 101 HCV patients receiving triple therapy with telaprevir (n = 36) or boceprevir (n = 26) or double therapy (n = 39) with peginterferon and ribavirin and having a close monitoring of eGFR (MDRD formula) during and after treatment. EGFR decline over time was assessed by a linear mixed-effects model (LMEM) with search for possible explanatory covariates. RESULTS: Patients treated with telaprevir presented a significant decrease of eGFR with the same kinetics: initial decrease at W (week) 4, nadir at W8 (mean decrease 17.0 ± 18.9 ml/min/1.73 m(2)) and return to baseline at W16. The W8 eGFR was correlated with the D0 eGFR (R(2) = 0.49). The LMEM showed that interindividual variability in the slope of eGFR vs time between D0 and W8 was non-significant and eGFR nadir could be predicted from eGFR obtained at D0. In multivariate analysis, eGFR intercept (i.e. baseline value) was associated with older age and male sex. CONCLUSION: The eGFR significantly varied in telaprevir group only. Our model showed that eGFR nadir mainly depended on initial eGFR. As telaprevir has been shown to inhibit mostly the drug transporter OCT2 which interacts with creatinine transport, the early decrease of eGFR observed could be a benign phenomenon. However, as unpredictable true renal toxicity may occur during therapy, we recommend a thorough follow-up of eGFR.

Ciclosporin population pharmacokinetics and Bayesian estimation in thoracic transplant recipients.

BACKGROUND AND OBJECTIVES: Therapeutic drug monitoring of ciclosporin has been recognized as an essential tool in the management of allograft transplant recipients, as it could help improve their outcome. However, there is still no consensus about the optimal method for monitoring ciclosporin after thoracic transplantation. Better knowledge of the pharmacokinetics of ciclosporin in thoracic transplant patients and design of tools dedicated to ciclosporin monitoring could help its practice and its outcome in this population of patients. The aims of this study were to (i) investigate the population pharmacokinetics of ciclosporin in thoracic (heart or lung) transplant patients and study the influence of a range of potential covariates, including demographic, clinical and genetic factors, on pharmacokinetic parameters; and (ii) develop a Bayesian estimator able to predict the individual pharmacokinetic parameters and exposures indices in this population of patients. METHODS: The analysis was performed with 187 full pharmacokinetic profiles obtained in 57 lung and 19 heart transplant patients within the first year post-transplantation. A population pharmacokinetic model was developed by non-linear mixed-effects modelling using NONMEM(®) (version 7.1) from an index dataset (118 profiles). On the basis of this population model and a limited number of blood samples, a Bayesian estimator able to determine ciclosporin area under the blood concentration-time curve (AUC) during a dosage interval was built and evaluated in the validation dataset (69 profiles). RESULTS: Ciclosporin pharmacokinetics were described using a two-compartment model with time-lagged first order absorption and first-order elimination. The final population model included sex as a covariate: ciclosporin apparent oral clearance was on average 37 % faster in male than in female patients (34.8 vs. 25.4 L/h, p < 0.001). Good predictive performance of the Bayesian estimator was obtained using three blood concentrations measured at 40 min, 2 h and 4 h post-dose, with a non-significant bias of -5 % between the estimated and the reference trapezoidal AUC and a good precision (relative mean square error = 13 %). CONCLUSION: Ciclosporin population pharmacokinetic analysis in thoracic transplant patients (including patients with cystic fibrosis) showed a significant influence of sex on apparent clearance. The Bayesian estimator developed in this study yielded accurate prediction of ciclosporin exposure in this population throughout the first year post-transplantation. This tool may allow routine ciclosporin dose individualization.

Association of sirolimus adverse effects with m-TOR, p70S6K or Raptor polymorphisms in kidney transplant recipients.

BACKGROUND: The mammalian target of rapamycin (m-TOR) inhibitor sirolimus is an immunosuppressive drug used in kidney transplantation. m-TOR binds with Raptor and phosphorylates p70S6 kinase, a protein involved in numerous cell signalling pathways. We examined the association of candidate polymorphisms in m-TOR, Raptor and p70S6K, sirolimus dose and exposure, and other time-independent as well as time-dependent covariates, with sirolimus-induced adverse events in kidney transplant recipients. METHODS: This study included a first group of 113 patients, switched from a calcineurin inhibitor to sirolimus, and a validation group of 66 patients from another clinical trial, with the same immunosuppressive regimen. The effects of gene polymorphisms and covariates on the total cholesterol, LDL cholesterol, triglycerides, haemoglobin, cutaneous adverse events, oedemas and infections were studied using multilinear regression, or logistic regression imbedded in linear mixed-effect models. RESULTS: An m-TOR variant haplotype was significantly associated with a decrease in haemoglobin levels in the two populations of patients (discovery group: ß=-0.82 g/dl, P=0.0076; validation group: ß=-1.58 g/dl, P=0.0308). Increased sirolimus trough levels were significantly associated with increased total cholesterol levels (discovery group: ß=0.02 g/l, P<0.0001; validation group: ß=0.02 g/l, P=0.0002) and triglyceride levels (discovery group: ß=0.02 g/l, P=0.0059; validation group: ß=0.05 g/l, P=0.0370). Sirolimus trough levels were also associated with an increased risk for cutaneous adverse events [odds ratio=1.97, 95% confidence interval (1.32-1.94), P=0.0009] and oedemas [odds ratio=1.16, 95% confidence interval (1.03-1.30), P=0.01342] in the discovery group, but this was not confirmed in the validation group. CONCLUSION: These results provide evidence of an association between an m-TOR haplotype and a decrease in haemoglobin in renal transplant recipients.

Population pharmacokinetic modelling and design of a Bayesian estimator for therapeutic drug monitoring of tacrolimus in lung transplantation.

BACKGROUND: Therapeutic drug monitoring of tacrolimus is a major support to patient management and could help improve the outcome of lung transplant recipients, by minimizing the risk of rejections and infections. However, despite the wide use of tacrolimus as part of maintenance immunosuppressive regimens after lung transplantation, little is known about its pharmacokinetics in this population. Better knowledge of the pharmacokinetics of tacrolimus in lung transplant recipients, and the development of tools dedicated to its therapeutic drug monitoring, could thus help improve their outcome. OBJECTIVES: The aims of this study were (i) to characterize the population pharmacokinetics of tacrolimus in lung transplant recipients, including the influence of biological and pharmacogenetic covariates; and (ii) to develop a Bayesian estimator of the tacrolimus area under the blood concentration-time curve from time zero to 12 hours (AUC(12)) for its therapeutic drug monitoring in lung transplant recipients. METHODS: A population pharmacokinetic model was developed by nonlinear mixed-effects modelling using NONMEM® version VI, from 182 tacrolimus full concentration-time profiles collected in 78 lung transplant recipients within the first year post-transplantation. Patient genotypes for the cytochrome P450 3A5 (CYP3A5) A6986G single nucleotide polymorphism (SNP) were characterized by TaqMan allelic discrimination. Patients were divided into an index dataset (n = 125 profiles) and a validation dataset (n = 57 profiles). A Bayesian estimator was derived from the final model using the index dataset, in order to determine the tacrolimus AUC(12) on the basis of a limited number of samples. The predictive performance of the Bayesian estimator was evaluated in the validation dataset by comparing the estimated AUC(12) with the trapezoidal AUC(12). RESULTS: Tacrolimus pharmacokinetics were described using a two-compartment model with Erlang absorption and first-order elimination. The model included cystic fibrosis (CF) and CYP3A5 polymorphism as covariates. The relative bioavailability in patients with CF was approximately 60% of the relative bioavailability observed in patients without CF, and the transfer rate constant between the transit compartments was 2-fold smaller in patients with CF than in those without CF (3.32 vs 7.06 h-1). The apparent clearance was 40% faster in CYP3A5 expressers than in non-expressers (24.5 vs 17.5 L/h). Good predictive performance was obtained with the Bayesian estimator developed using the final model and concentrations measured at 40 minutes and at 2 and 4 hours post-dose, as shown by the mean bias (1.1%, 95% CI -1.4, 3.7) and imprecision (9.8%) between the estimated and the trapezoidal AUC(12). The bias was >20% in 1.8% of patients. CONCLUSION: Population pharmacokinetic analysis showed that lung transplant patients with CF displayed lower bioavailability and a smaller transfer rate constant between transit compartments than those without CF, while the apparent clearance was faster in CYP3A5 expressers than in non-expressers. The Bayesian estimator developed in this study provides an accurate prediction of tacrolimus exposure in lung transplant patients, with and without CF, throughout the first year post-transplantation. This tool may allow routine tacrolimus dose individualization and may be used to conduct clinical trials on therapeutic drug monitoring of tacrolimus after lung transplantation.

Bayesian estimation of mycophenolate mofetil in lung transplantation, using a population pharmacokinetic model developed in kidney and lung transplant recipients.

BACKGROUND AND OBJECTIVES: The immunosuppressive drug mycophenolate mofetil is used to prevent rejection after organ transplantation. In kidney transplant recipients, it has been demonstrated that adjustment of the mycophenolate mofetil dose on the basis of the area under the concentration-time curve (AUC) of mycophenolic acid (MPA), the active moiety of mycophenolate mofetil, improves the clinical outcome. Because of the high risks of rejections and infections in lung transplant recipients, therapeutic drug monitoring of the MPA AUC might be even more useful in these patients. The aims of this study were to characterize the pharmacokinetics of MPA in lung and kidney transplant recipients, describe the differences between the two populations and develop a Bayesian estimator of the MPA AUC in lung transplant recipients. METHODS: In total, 460 MPA concentration-time profiles from 41 lung transplant recipients and 116 kidney transplant recipients were included. Nonlinear mixed-effects modelling was used to develop a population pharmacokinetic model. Patients were divided into an index dataset and a validation dataset. The pharmacokinetic model derived from the index dataset was used to develop a Bayesian estimator, which was validated using the 35 lung transplant recipients' profiles from the validation dataset. RESULTS: MPA pharmacokinetics were described using a two-compartment model with lag time, first-order absorption and first-order elimination. The influence of ciclosporin co-treatment and the changes over time post-transplantation were included in the model. Lung transplant recipients had, on average, a 53% slower absorption rate and 50% faster MPA apparent oral clearance than kidney transplant recipients (p < 0.001). In lung transplant recipients, the bioavailability was, on average, 31% lower in patients with cystic fibrosis than in patients without cystic fibrosis (p < 0.001). The Bayesian estimator developed using the population pharmacokinetic model--and taking into account ciclosporin co-treatment, cystic fibrosis and time post-transplantation, with concentrations measured at 0, 1 and 4 hours after mycophenolate mofetil dose administration--resulted in a non-significant bias and mean imprecision of 5.8 mg · h/L. This higher imprecision compared with those of similar estimators that have previously been developed in kidney transplantation might have been caused by the high MPA pharmacokinetic variability seen in the lung transplant recipients and by the fact that a large proportion of the patients did not receive ciclosporin, which reduces variability in the elimination phase of MPA by blocking its enterohepatic cycling. CONCLUSION: Lung transplant recipients have a slower MPA absorption rate and faster apparent oral clearance than kidney transplant recipients, while cystic fibrosis results in lower MPA bioavailability. A Bayesian estimator using MPA concentration-time samples at 0, 1 and 4 hours post-dose had the best predictive performance.

Pharmacological exposure to ribavirin: a key player in the complex network of factors implicated in virological response and anaemia in hepatitis C treatment.

Ribavirin remains today a pivotal drug in the treatment of hepatitis C; in standard double therapy, as well as in triple combination with direct antiviral agents, ribavirin reduces relapse and can double the sustained virological response obtained with peginterferon alone or in association with direct antiviral agents. In the complex network of interacting factors determining sustained virological response independently of known predictive factors related to host and virus, two modern tools are emerging: polymorphisms in the IL28B gene and very early exposure to ribavirin. The use of a pharmacokinetic-pharmacodynamic model of early ribavirin exposure to adjust the dose individually would help promote a safer ribavirin use and improve sustained virological response. The variability of the influence of ribavirin exposure on anaemia is probably genetically determined; however, the low prevalence of the implicated protective alleles of the inosine triphosphate pyrophosphatase gene could explain their lack of influence on sustained virological response.

Large scale analysis of routine dose adjustments of mycophenolate mofetil based on global exposure in renal transplant patients.

BACKGROUND: We report a feasibility study based on our large-scale experience with mycophenolate mofetil dose adjustment based on mycophenolic acid interdose area under the curve (AUC) in renal transplant patients. METHODS: Between 2005 and 2010, 13,930 requests for 7090 different patients (outside any clinical trial) were posted by more than 30 different transplantation centers on a free, secure web site for mycophenolate mofetil dose recommendations using three plasma concentrations and Bayesian estimation. RESULTS: This retrospective study showed that 1) according to a consensually recommended 30- to 60-mg·h/L target, dose adjustment was needed for approximately 35% of the patients, 25% being underexposed with the highest proportion observed in the first weeks after transplantation; 2) when dose adjustment had been previously proposed, the subsequent AUC was significantly more often in the recommended range if the dose was applied than not at all posttransplantation periods (72-80% vs. 43-54%); and 3) the interindividual AUC variability in the "respected-dose" group was systematically lower than that in the "not respected-dose" group (depending on the posttransplantation periods; coefficient of variation %, 31-41% vs 49-70%, respectively). Further analysis suggested that mycophenolic acid AUC should best be monitored at least every 2 weeks during the first month, every 1 to 3 months between months 1 and 12, whereas in the stable phase, the odds to be still in the 30- to 60-mg·h/L range on the following visit was still 75% up to 1 year after the previous dose adjustment. CONCLUSION: This study showed that the monitoring of mycophenolate mofetil on the basis of AUC measurements is a clinically feasible approach, apparently acceptable by the patients, the nurses, and the physicians owing to its large use in routine clinics.

Development and evaluation of a simulation procedure to take into account various assays for the Bayesian dose adjustment of tacrolimus.

BACKGROUND AND OBJECTIVES: Several analytical techniques with different performances are available for the measurement of tacrolimus blood concentrations. The performance of Bayesian estimators (MAP-BEs) allowing dose adjustments of tacrolimus is dependent on the precision of the analytical technique. Hence, any Bayesian estimator should only be used for concentration data obtained with the same assay employed for its development. The present study aimed at evaluating the feasibility of developing Bayesian estimators dedicated to different immunoassays, using the concentrations obtained with the reference high-performance liquid chromatography with mass spectrometric detection (LC-MS/MS) method and a simulation approach. PATIENTS AND METHODS: One hundred thirty-five full pharmacokinetic profiles of tacrolimus were obtained from 45 renal transplant patients using 3 different analytical techniques: 2 immunoassays [enzyme-multiplied immunoassay technique (EMIT) and chemiluminescent microparticle immunoassay (CMIA)] and LC-MS/MS. In a first step, 3 MAP-BEs were developed using the concentrations measured with the 3 techniques. Taking into account the correlation equations between the concentrations obtained with each of the immunoassays and LC-MS/MS, as well as the analytical error of the techniques, 2 hybrid MAP-BEs dedicated to the immunoassays were then developed after simulation of 100 pharmacokinetic profiles. Their performances were compared with those of the respective MAP-BEs developed using the actual immunoassay concentrations. RESULTS: The mean concentrations measured over the dosing interval using EMIT and CMIA were significantly higher than those measured using LC-MS/MS (+15% and +11% in the AUC0₋24 h value, respectively, P < 0.0001), leading to differences in dose recommendations of -0.9 ± 1.1 and -0.7 ± 0.9 mg, respectively. When applying the MAP-BE developed from LC-MS/MS data for the EMIT or CMIA concentrations, tacrolimus AUC0₋24 h was estimated with an imprecision >20% in 33% and 27% of the patients, respectively. In contrast, the "CMIA" and "EMIT" hybrid MAP-BEs provided a good AUC0₋24 h estimation in 85%-93% of the patients. CONCLUSIONS: This study showed the impact of the analytical technique on the performance of Bayesian estimators dedicated to tacrolimus dose adjustment and the feasibility to develop MAP-BE for a specific assay using results from a different assay, based on a limited method comparison study. This methodology could offer clinicians the opportunity to dose adjust tacrolimus whatever the assay used in their center.

Population pharmacokinetic model and Bayesian estimator for two tacrolimus formulations--twice daily Prograf and once daily Advagraf.

AIM: To investigate the differences in the pharmacokinetics of Prograf and the prolonged release formulation Advagraf and to develop a Bayesian estimator to estimate tacrolimus inter-dose area under the curve (AUC) in renal transplant patients receiving either Prograf or Advagraf. METHODS: Tacrolimus concentration-time profiles were collected, in adult renal transplant recipients, at weeks 1 and 2, and at months 1, 3 and 6 post-transplantation from 32 Prograf treated patients, and one profile was collected from 41 Advagraf patients more than 12 months post-transplantation. Population pharmacokinetic (popPK) parameters were estimated using nonmem. In a second step, the popPK model was used to develop a single Bayesian estimator for the two tacrolimus formulations. RESULTS: A two-compartment model with Erlang absorption (n= 3) and first-order elimination best described the data. In Advagraf patients, a bimodal distribution was observed for the absorption rate constant (K(tr) ): one group with a K(tr) similar to that of Prograf treated patients and the other group with a slower absorption. A mixture model for K(tr) was tested to describe this bimodal distribution. However, the data were best described by the nonmixture model including covariates (cytochrome P450 3A5, haematocrit and drug formulation). Using this model and tacrolimus concentrations measured at 0, 1 and 3h post-dose, the Bayesian estimator could estimate tacrolimus AUC accurately (bias = 0.1%) and with good precision (8.6%). CONCLUSIONS: The single Bayesian estimator developed yields good predictive performance for estimation of individual tacrolimus inter-dose AUC in Prograf and Advagraf treated patients and is suitable for clinical practice.