BACKGROUND: A limited sampling strategy (LSS) for estimating the area under the curve (AUC) of the prolonged-release formulation of tacrolimus (tacrolimus(PR)) is not available in pediatric patients, although the method is of real benefit to children. The objective of this study was to develop and validate a reliable and clinically applicable LSS using Bayesian estimation for estimating tacrolimus(PR) AUC in pediatric kidney transplant patients METHODS: The original tacrolimus pharmacokinetic dataset consisted of 22 full profiles from 22 pediatric kidney transplant patients. The Bayesian estimation method was used to develop the LSS. External validation was performed in an independent validation group which consisted of 20 full pharmacokinetic profiles from 12 pediatric kidney transplant patients. RESULTS: Bayesian estimator using C0h C2h and C3h gave the best predictive performance with a mean prediction error of 2.2 % in the external validation dataset. There was no correlation between the prediction error and age. The Bland-Altman analysis showed that the mean difference between the reference and Bayesian-estimated AUC0-24 was 3.5 (95 % confidence interval -3.5-10.5) ng h/mL CONCLUSIONS: A reliable and clinically applicable LSS for estimating AUC0-24 of tacrolimus(PR) was determined and validated in children. The prediction was unbiased and precise. It can be used as a routine procedure to perform AUC-based tacrolimus(PR) dosage optimization in pediatric renal transplant patients.
BACKGROUND: A limited sampling strategy (LSS) for estimating the area under the curve (AUC) of the prolonged-release formulation of tacrolimus (tacrolimus(PR)) is not available in pediatric patients, although the method is of real benefit to children. The objective of this study was to develop and validate a reliable and clinically applicable LSS using Bayesian estimation for estimating tacrolimus(PR) AUC in pediatric kidney transplant patients METHODS: The original tacrolimus pharmacokinetic dataset consisted of 22 full profiles from 22 pediatric kidney transplant patients. The Bayesian estimation method was used to develop the LSS. External validation was performed in an independent validation group which consisted of 20 full pharmacokinetic profiles from 12 pediatric kidney transplant patients. RESULTS: Bayesian estimator using C0h C2h and C3h gave the best predictive performance with a mean prediction error of 2.2 % in the external validation dataset. There was no correlation between the prediction error and age. The Bland-Altman analysis showed that the mean difference between the reference and Bayesian-estimated AUC0-24 was 3.5 (95 % confidence interval -3.5-10.5) ng h/mL CONCLUSIONS: A reliable and clinically applicable LSS for estimating AUC0-24 of tacrolimus(PR) was determined and validated in children. The prediction was unbiased and precise. It can be used as a routine procedure to perform AUC-based tacrolimus(PR) dosage optimization in pediatric renal transplant patients.
Authors: A Franciscus van der Meer; Marco A E Marcus; Daniël J Touw; Johannes H Proost; Cees Neef Journal: Ther Drug Monit Date: 2011-04 Impact factor: 3.681
Authors: W Zhao; V Elie; G Roussey; K Brochard; P Niaudet; V Leroy; C Loirat; P Cochat; S Cloarec; J L André; F Garaix; A Bensman; M Fakhoury; E Jacqz-Aigrain Journal: Clin Pharmacol Ther Date: 2009-10-28 Impact factor: 6.875
Authors: Joseph E Rower; Chris Stockmann; Matthew W Linakis; Shaun S Kumar; Xiaoxi Liu; E Kent Korgenski; Catherine M T Sherwin; Kimberly M Molina Journal: BMJ Paediatr Open Date: 2017-11-22