A 3-hour postdose cyclosporine level during the first week after kidney transplantation predicts acute rejection and cyclosporine nephrotoxicity more accurately than trough levels

Assessment of the Cylex ImmuKnow cell function assay in pediatric heart transplant patients

BACKGROUND

The Cylex ImmuKnow (Cylex, Columbia, MD) cell function assay (CICFA) is a commercially available test of immune response that purportedly identifies solid organ transplant patients at risk for either acute rejection (AR) or infection. Data on the utility of this test in pediatric heart transplant patients are very limited. This study tested the hypothesis that CICFA is a clinically useful test in this transplant population.

METHODS

All children undergoing heart transplantation at the study center (1989-2006) for whom CICFA levels were obtained were reviewed. The association of CICFA levels with episodes of AR and significant infections was determined.

RESULTS

Among 83 patients (34 girls, 41%), 367 CICFA levels were obtained (median, 4.0; interquartile range [IQR], 2.0-6.0 per patient). There were 26 episodes of AR in 17 patients (20%) and 38 infections in 34 patients (41%). CICFA levels were similar among patients with AR at the time of the CICFA measurement (median, 325 [IQR, 163-480] adenosine triphosphate [ATP] ng/ml) vs patients without AR (median, 330 [IQR, 227-441] ATP ng/ml; p = 0.36). CICFA levels were similar among patients with infections within 1 month of CICFA measurement (median, 295 [IQR, 216-366] ATP ng/ml) and those without infections (median, 330 [IQR, 226-453] ATP ng/ml; p = 0.24).

CONCLUSIONS

The CICFA is not predictive of AR or significant infections in pediatric heart transplant patients. On the basis of the available evidence, this assay cannot be recommended as part of the routine management of pediatric heart transplant patients.

Single time point measurement by C2 or C3 is highly predictive in cyclosporine area under the curve estimation immediately after lung transplantation

BACKGROUND

The two h post-dose cyclosporine (CsA) concentration has been advocated as the optimal time point measurement for CsA area under the curve (AUC) estimation after solid organ transplantation. The aim of the study was to investigate whether intensified CsA monitoring is necessary, or if a single time point measurement is accurate to estimate the AUC in the very early period following lung transplantation (LuTX).

METHODS

Within the first two wk following transplantation, daily AUCs were calculated by serial CsA measurements at zero, one, two, three, four, and six h (C0-C6) in 12 consecutive lung transplant recipients. Correlation of single CsA measurements and AUC as well as linear regression analysis was performed to evaluate the most predictive single CsA blood level regarding the AUC.

RESULTS

A total of 606 CsA concentration measurements were performed and the 101 corresponding AUCs were calculated for each patient. Mean AUC was 3443 +/- 1451 microg/L. C0: 361 +/- 118 microg/L, C1: 481 +/- 231 microg/L, C2: 682 +/- 314 microg/L, C3: 715 +/- 347 microg/L, C4: 658 +/- 271 microg/L, C6: 571 +/- 260 microg/L. The correlation of CsA serum levels with AUC was the lowest at trough levels (C0) with a correlation coefficient (r = 0.31) and highest at three h (C3: r = 0.89) and two h (C2: r = 0.88).

CONCLUSIONS

Similar to a stable post-transplant period, CsA trough levels turned out to have poor correlation with the corresponding AUC early after LuTX. The highest correlation of C3 with the AUC may be explained by delayed intestinal resorption immediately post-operative, however C2 is a peer parameter. Optimum AUCs and corresponding C2 or C3 levels in the immediate post-operative phase however remain to be determined.

Sirolimus: Its role in nephrology (Review Article)

Sirolimus (Rapamycin, Wyeth Pharmaceuticals Australia Pty Ltd, Baulkham Hills, NSW, Australia) (SRL) has received increasing attention as an immunosuppressant in renal and other solid organ transplantation. Sirolimus is the first marketed agent in a new class of drugs with a novel mechanism of action. Sirolimus binds, like tacrolimus, to a member of the FK binding protein (FKBP) family. The SRL/FKBP complex binds to the protein kinase mTOR. Binding to mTOR blocks activation of signal transduction pathways causing arrest of the cell cycle in the G1 phase. It is now known that mTOR is a central regulator of cell growth and proliferation. The immunosuppressive properties of SRL are due primarily to blockade of interleukin-2 (IL-2)-induced proliferation of T cells. There is still much to be learnt about how best to use the drug. The key advantage over the current choice of immunosuppressive agents is the ability to preserve renal function and pathology while producing excellent rejection-free, graft survival rates. Thus, SRL may find its pivotal role as a calcineurin inhibitors replacement in patients whose grafts are affected by chronic allograft nephropathy. A second major driver for use may prove to be the impact of SRL on cancer incidence and prognosis. Studies still need to be performed to evaluate the best timing for commencement of SRL and the optimal dosage to minimize side-effects.

Bayesian estimation of cyclosporin exposure for routine therapeutic drug monitoring in kidney transplant patients

AIMS

AUC-based monitoring of cyclosporin A (CsA) is useful to optimize dose adaptation in difficult cases. We developed a population pharmacokinetic model to describe dose-exposure relationships for CsA in renal transplant patients and applied it to the Bayesian estimation of AUCs using three blood concentrations.

METHODS

A total of 84 renal graft recipients treated with CsA microemulsion were included in this study. Population pharmacokinetic analysis was conducted using NONMEM. A two-compartment model with zero-order absorption and a lag time best described the data. Bayesian estimation was based on CsA blood concentrations measured before dosing and 1 h and 2 h post dose. Predictive performance was evaluated using a cross-validation approach. Estimated AUCs were compared with AUCs calculated by the trapezoidal method. The Bayesian approach was also applied to an independent group of eight patients exhibiting unusual pharmacokinetic profiles.

RESULTS

Mean population pharmacokinetic parameters were apparent clearance 30 l h(-1), apparent volume of distribution 79.8 l, duration of absorption 52 min, absorption lag time 7 min. No significant relationships were found between any of the pharmacokinetic parameters and individual characteristics. A good correlation was obtained between Bayesian-estimated and experimental AUCs, with a mean prediction error of 2.8% (95% CI [-0.6, 6.2]) and an accuracy of 13.1% (95% CI [7.5, 17.2]). A good correlation was also obtained in the eight patients with unusual pharmacokinetic profiles (r(2) = 0.96, P < 0.01).

CONCLUSIONS

Our Bayesian approach enabled a good estimation of CsA exposure in a population of patients with variable pharmacokinetic profiles, showing its usefulness for routine AUC-based therapeutic drug monitoring.

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.

Role of postdose cyclosporine monitoring in living renal transplant recipients

Achieving optimal cyclosporine (Neoral) absorption is critical for successful graft outcome. Recently there have been studies on postdose monitoring of cyclosporine. Two- and 3-hour postdose cyclosporine levels measured by radioimmunoassay were correlated with occurrence of rejection and cyclosporine nephrotoxicity in 30 patients; C(2) and C(3) levels were significantly lower than the desired therapeutic levels in patients with acute rejection. Based on our study and those of others we suggest C(3) levels should be adopted in clinical practice.

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.