Evaluation of Bayesian Forecasting Methods for Prediction of Tacrolimus Exposure Using Samples Taken on Two Occasions in Adult Kidney Transplant Recipients

This study examined the predictive performance of Bayesian forecasting programs/services for the estimation of future tacrolimus area under the curve (AUC) from 0 to 12 hours (AUC0–12) in kidney transplant recipients. Methods: Tacrolimus concentrations were measured in 20 adult kidney transplant recipients, 1 month post-transplant, on 2 occasions one week apart. Twelve samples were taken predose and 13 samples were taken postdose at the specified times on the first and second sampling occasions, respectively. The predicted AUC0–12 (AUCpredicted) was estimated using Bayesian forecasting programs/services and data from both sampling occasions for each patient and compared with the fully measured AUC0–12 (AUCmeasured) calculated using the linear trapezoidal rule on the second sampling occasion. The bias (median percentage prediction error [MPPE]) and imprecision (median absolute prediction error [MAPE]) were determined. Results: Three programs/services were evaluated using different LSSs (C0; C0, C1, C3; C0, C1, C2, C4; and all available concentrations). MPPE and MAPE for the prediction of fully measured AUC0–12 were
Source: Therapeutic Drug Monitoring - Category: Drugs & Pharmacology Tags: Original Article Source Type: research