@article{APS9548,
author = {Yu-bin ZHU and Xian-hua HONG and Meng WEI and Jing HU and Xin CHEN and Shu-kui WANG and Jun-rong ZHU and Feng YU and Jian-guo SUN},
title = {Development of a novel individualized warfarin dose algorithm based on a population pharmacokinetic model with improved prediction accuracy for Chinese patients after heart valve replacement},
journal = {Acta Pharmacologica Sinica},
volume = {38},
number = {3},
year = {2017},
keywords = {},
abstract = {The gene-guided dosing strategy of warfarin generally leads to over-dose in patients at doses lower than 2 mg/kg, and only 50% of individual variability in daily stable doses can be explained. In this study, we developed a novel population pharmacokinetic (PK) model based on a warfarin dose algorithm for Han Chinese patients with valve replacement for improving the dose prediction accuracy, especially in patients with low doses. The individual pharmacokinetic (PK) parameter - apparent clearance of Sand R-warfarin (CLs) was obtained after establishing and validating the population PK model from 296 recruited patients with valve replacement. Then, the individual estimation of CLs, VKORC1 genotypes, the steady-state international normalized ratio (INR) values and age were used to describe the maintenance doses by multiple linear regression for 144 steady-state patients. The newly established dosing algorithm was then validated in an independent group of 42 patients and was compared with other dosing algorithms for the accuracy and precision of prediction. The final regression model developed was as follows: Dose=-0.023×AGE+1.834×VKORC1+0.952×INR+2.156×CLs (the target INR value ranges from 1.8 to 2.5). The validation of the algorithm in another group of 42 patients showed that the individual variation rate (71.6%) was higher than in the gene-guided dosing models. The over-estimation rate in patients with low doses (},
issn = {1745-7254}, url = {http://www.chinaphar.com/article/view/9548}
}