Cyclosporine pharmacokinetics and risk of recurrent rejection in recipients of simultaneous pancreas/kidney transplants

Limited sampling strategies for estimating intravenous and oral cyclosporine area under the curve in pediatric hematopoietic stem cell transplantation

BACKGROUND

The optimal monitoring strategy for cyclosporine (CsA) in pediatric hematopoietic stem cell transplantation (HSCT) patients remains unclear. Although there is a growing interest in the use of the area under the concentration-time curve (AUC), measurement of AUC in clinical settings is often impractical. The objective of this study was to identify and validate limited sampling strategies (LSSs) for the prediction of CsA AUC after intravenous (IV) and oral (PO) administration in this population.

METHODS

Sixty-eight pediatric patients who underwent HSCT and received CsA were investigated. Twelve-hour pharmacokinetic profiles (n = 138) performed per standard of care were collected. Weighted multiple linear regression was used to investigate all possible LSSs consisting of 4 or less concentration-time points. Their predictive performance was evaluated by leave one out cross validation and external validation by measuring the root mean squared relative error (RMSE%) and the 95th percentile of the absolute relative error (AE%). Values less than 20% were considered clinically acceptable.

RESULTS

Nine LSSs (4 IV and 5 PO) convenient for clinical application proved to have clinically acceptable performance. Notably, LSS based on C0, C2, and C4 was found to be accurate for estimation of CsA exposure after both IV and PO administration with the 95th percentile of AE% of 19.7% and 17.5%, respectively.

CONCLUSIONS

LSSs using 3 or 4 concentration-time points obtained within 4 hours postdose provide a convenient and reliable method to estimate CsA exposure in this population. These LSSs may facilitate future research aiming at better defining the relationship between AUC and clinical outcomes.

Impact of sampling time deviations on the prediction of the area under the curve using regression limited sampling strategies

The regression limited sampling strategy approach (R-LSS), which is based on a small number of blood samples drawn at selected time points, has been used as an alternative method for the estimation of the area under the concentration-time curve (AUC). However, deviations from planned sampling times may affect the performance of R-LSS, influencing related therapeutic decisions and outcomes. The aim of this study was to investigate the impact of different sampling time deviation (STD) scenarios on the estimation of AUC by the R-LSS using a simulation approach. Three types of scenarios were considered going from the simplest case of fixed deviations, to random deviations and then to a more realistic case where deviations of mixed nature can occur. In addition, the sensitivity of the R-LSS to STD in each involved sampling point was evaluated. A significant impact of STD on the performance of R-LSS was demonstrated. The tolerance of R-LSS to STD was found to depend not only on the number of sampling points but more importantly on the duration of the sampling process. Sensitivity analysis showed that sampling points at which rapid concentration changes occur were relatively more critical for AUC prediction by R-LSS. As a practical approach, nomograms were proposed, where the expected predictive performance of R-LSS was provided as a function of STD information. The investigation of STD impact on the predictive performance of R-LSS is a critical element and should be routinely performed to guide R-LSS selection and use.

Immunosuppressive drug monitoring - what to use in clinical practice today to improve renal graft outcome

Therapeutic drug monitoring (TDM) of immunosuppressive therapy is becoming an increasingly complex matter as the number of compounds and their respective combinations are continuously expanding. Unfortunately, in clinical practice, monitoring predose trough blood concentrations is often not sufficient for guiding optimal long-term dosing of these drugs. The excellent short-term results obtained nowadays in renal transplantation confer a misleading feeling of safety despite the fact that long-term results have not substantially improved, definitely not to a point where longer graft survival could counteract the increasing need for transplant organs and less toxicity and side-effects could ameliorate patient survival. It is therefore a challenging task to try to tailor immunosuppressive drug therapy to the individual patient profile and this in a time-dependent manner. For the majority of currently used immunosuppressive drugs, measurement of total drug exposure by determination of the dose-interval area under the concentration curve (AUC) seems to provide more useful information for clinicians in terms of concentration-exposure and exposure-response as well as reproducibility. To simplify this laborious way of measuring drug exposure, several validated abbreviated AUC profiles, accurately predicting the dose-interval AUC, have been put forward. Together with an increasing knowledge of the time-related pharmacokinetic behaviour of immunosuppressive drug and their metabolites, studies are focusing on how to apply abbreviated AUC sampling methods in clinical transplantation, taking into account the numerous factors affecting drug pharmacokinetics. Eventually, TDM using abbreviated AUC profiles has to be prospectively tested against classic methods of drug monitoring in terms of cost-effectiveness, feasibility and clinical relevance with the ultimate goal of improving patient and graft survival.

Limited sampling strategies for estimating cyclosporin area under the concentration-time curve: review of current algorithms

Cyclosporin, the drug of first choice in transplantation surgery, is characterized by a low therapeutic index and variable absorption, so close monitoring of the drug is required to optimize the dosing. Predose blood cyclosporin levels are measured routinely for therapeutic monitoring, but this approach is not optimal because the area under the concentration-time curve (AUC) correlates better with clinical events. However, conventional methods of measuring AUC require many blood samples, which is not viable in a routine clinical setting. AUC monitoring can be simplified for use in a clinical setting by using a limited sampling strategy (LSS) that allows AUC to be estimated using a small number of blood samples collected at specific times. This article reviews the current literature on estimating cyclosporin AUC using LSS. Thirty-eight papers suggesting the use of specific time points were found. LSS has been developed for different transplant types, with different dosing regimens, and with different assays. Most authors suggested either two- or three-sample equations. Results from authors who validated their models suggest that equations defined on one transplant type may be applicable to other transplant types, to both adults and children, and to early or late after transplantation. Moreover, it seems that there is flexibility in the choice of equations available to clinicians. The number of samples to collect for accurate estimations is a matter of debate, but a wise choice can minimize the number. The choice of the optimal LSS and validation are discussed.