A single-centre experience of post-renal transplant lymphoproliferative disorder

Post-transplant lymphoproliferative disorder (PTLD) complicates 1 to 10% of all transplantations. Previous clinicopathological studies of PTLD have been limited by small numbers, short follow-up times, outdated data, heterogeneity of pooled solid-organ transplant results, and selective inclusion of early-onset disease. We therefore undertake here a retrospective analysis and identify all cases of PTLD that complicated renal transplantation at the Princess Alexandra Hospital between 30 June 1969 and 31 May 2001. Tumour samples were subsequently retrieved for pathological review and for Epstein-Barr virus-encoded RNA in situ hybridisation (EBER-ISH). Of 2,030 renal transplantation patients, 29 (1.4%) developed PTLD after a median period of 0.5 years (range 0.1 to 23.3 years). PTLD patients were more likely to have received cyclosporine (76% versus 62%, P

Sampling times for monitoring tacrolimus in stable adult liver transplant recipients

The aim of this study was to determine the most informative sampling time(s) providing a precise prediction of tacrolimus area under the concentration-time curve (AUC). Fifty-four concentration-time profiles of tacrolimus from 31 adult liver transplant recipients were analyzed. Each profile contained 5 tacrolimus whole-blood concentrations (predose and 1, 2, 4, and 6 or 8 hours postdose), measured using liquid chromatography-tandem mass spectrometry. The concentration at 6 hours was interpolated for each profile, and 54 values of AUC(0-6) were calculated using the trapezoidal rule. The best sampling times were then determined using limited sampling strategies and sensitivity analysis. Linear mixed-effects modeling was performed to estimate regression coefficients of equations incorporating each concentration-time point (C0, C1, C2, C4, interpolated C5, and interpolated C6) as a predictor of AUC(0-6). Predictive performance was evaluated by assessment of the mean error (ME) and root mean square error (RMSE). Limited sampling strategy (LSS) equations with C2, C4, and C5 provided similar results for prediction of AUC(0-6) (R-2 = 0.869, 0.844, and 0.832, respectively). These 3 time points were superior to C0 in the prediction of AUC. The ME was similar for all time points; the RMSE was smallest for C2, C4, and C5. The highest sensitivity index was determined to be 4.9 hours postdose at steady state, suggesting that this time point provides the most information about the AUC(0-12). The results from limited sampling strategies and sensitivity analysis supported the use of a single blood sample at 5 hours postdose as a predictor of both AUC(0-6) and AUC(0-12). A jackknife procedure was used to evaluate the predictive performance of the model, and this demonstrated that collecting a sample at 5 hours after dosing could be considered as the optimal sampling time for predicting AUC(0-6).