Zhao Li, Chen Chunxia, Li Bei, Dong Li, Guo Yingqiang, Xiao Xijun, Zhang Eryong, Qin Li
Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, P. R. China.
Department of Cardiothoracic Surgery, West China Hospital, Sichuan University, Chengdu, P.R. China.
PLoS One. 2014 Apr 11;9(4):e94573. doi: 10.1371/journal.pone.0094573. eCollection 2014.
To study the performance of pharmacogenetics-based warfarin dosing algorithms in the initial and the stable warfarin treatment phases in a cohort of Han-Chinese patients undertaking mechanic heart valve replacement.
We searched PubMed, Chinese National Knowledge Infrastructure and Wanfang databases for selecting pharmacogenetics-based warfarin dosing models. Patients with mechanic heart valve replacement were consecutively recruited between March 2012 and July 2012. The predicted warfarin dose of each patient was calculated and compared with the observed initial and stable warfarin doses. The percentage of patients whose predicted dose fell within 20% of their actual therapeutic dose (percentage within 20%), and the mean absolute error (MAE) were utilized to evaluate the predictive accuracy of all the selected algorithms.
A total of 8 algorithms including Du, Huang, Miao, Wei, Zhang, Lou, Gage, and International Warfarin Pharmacogenetics Consortium (IWPC) model, were tested in 181 patients. The MAE of the Gage, IWPC and 6 Han-Chinese pharmacogenetics-based warfarin dosing algorithms was less than 0.6 mg/day in accuracy and the percentage within 20% exceeded 45% in all of the selected models in both the initial and the stable treatment stages. When patients were stratified according to the warfarin dose range, all of the equations demonstrated better performance in the ideal-dose range (1.88-4.38 mg/day) than the low-dose range (<1.88 mg/day). Among the 8 algorithms compared, the algorithms of Wei, Huang, and Miao showed a lower MAE and higher percentage within 20% in both the initial and the stable warfarin dose prediction and in the low-dose and the ideal-dose ranges.
All of the selected pharmacogenetics-based warfarin dosing regimens performed similarly in our cohort. However, the algorithms of Wei, Huang, and Miao showed a better potential for warfarin prediction in the initial and the stable treatment phases in Han-Chinese patients undertaking mechanic heart valve replacement.
研究基于药物遗传学的华法林剂量算法在接受机械心脏瓣膜置换术的汉族患者初始和稳定华法林治疗阶段的表现。
我们检索了PubMed、中国知网和万方数据库，以选择基于药物遗传学的华法林剂量模型。2012年3月至2012年7月期间连续招募接受机械心脏瓣膜置换术的患者。计算每位患者的预测华法林剂量，并与观察到的初始和稳定华法林剂量进行比较。利用预测剂量落在实际治疗剂量20%范围内的患者百分比（20%范围内的百分比）和平均绝对误差（MAE）来评估所有选定算法的预测准确性。
在181例患者中测试了包括Du、Huang、Miao、Wei、Zhang、Lou、Gage和国际华法林药物遗传学联盟（IWPC）模型在内的总共8种算法。Gage、IWPC和6种基于汉族药物遗传学的华法林剂量算法的MAE在准确性上小于0.6mg/天，并且在初始和稳定治疗阶段的所有选定模型中，20%范围内的百分比均超过45%。当根据华法林剂量范围对患者进行分层时，所有方程在理想剂量范围（1.88 - 4.38mg/天）内的表现均优于低剂量范围（<1.88mg/天）。在比较的8种算法中，Wei、Huang和Miao算法在初始和稳定华法林剂量预测以及低剂量和理想剂量范围内均显示出较低的MAE和较高的20%范围内的百分比。
所有选定的基于药物遗传学的华法林给药方案在我们的队列中表现相似。然而，Wei、Huang和Miao算法在接受机械心脏瓣膜置换术的汉族患者的初始和稳定治疗阶段对华法林预测显示出更好的潜力。
