Evaluation Of Bayesian Forecasting Methods For Prediction Of Tacrolimus Exposure Using Samples Taken On Two Occasions In Adult Kidney Transplant Recipients

THERAPEUTIC DRUG MONITORING(2021)

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摘要
Background: Bayesian forecasting-based limited sampling strategies (LSSs) for tacrolimus have not been evaluated for the prediction of subsequent tacrolimus exposure. 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 (AUC(0-12)) 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 AUC(0-12) (AUC(predicted)) was estimated using Bayesian forecasting programs/services and data from both sampling occasions for each patient and compared with the fully measured AUC(0-12) (AUC(measured)) 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 AUC(0-12) were <15% for each program/service (with the exclusion of when only C0 was used), when using estimated AUC from data on the same (second) occasion. The MPPE and MAPE for the prediction of a future fully measured AUC(0-12) were <15% for 2 programs/services (and for the third when participants who had a tacrolimus dose change between sampling days were excluded), when the occasion 1-AUC(predicted), using C0, C1, and C3, was compared with the occasion 2-AUC(measured). Conclusions: All 3 Bayesian forecasting programs/services evaluated had acceptable bias and imprecision for predicting a future AUC(0-12), using tacrolimus concentrations at C0, C1, and C3, and could be used for the accurate prediction of tacrolimus exposure in adult kidney transplant recipients.
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关键词
tacrolimus, Bayesian forecasting, therapeutic drug monitoring, kidney transplant
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