Department of Pharmacy, Faculty of Pharmacy, Mahidol University, Bangkok, Thailand.
Department of Pharmaceutical Care, Faculty of Pharmacy, Chiangmai University, Chiangmai, Thailand.
Cardiovasc Ther. 2018 Apr;36(2). doi: 10.1111/1755-5922.12315. Epub 2018 Jan 3.
This study was conducted to compare predictive accuracy of the available pharmacogenetics (PGx)-guided warfarin dosing algorithms derived from Caucasian, Asian, and mixed population to identify a suitable algorithm for Thai population.
Ten warfarin dosing algorithms derived from different population including Caucasian, East Asian, South-East Asian, and mixed races were selected and tested with clinical and genetic data of Thai patients. Comparative performances of these algorithms were tested using mean dose error (MDE) between actual warfarin maintenance dose (AWMD) and predicted dose generated by each dosing algorithm, and percentage of ideal dose prediction (IDP). Sensitivity analysis for predictive accuracy was also conducted by stratifying patients into low (AWMD ≤21 mg/wk), intermediate (AWMD >21 to <49 mg/wk), and high maintenance dose (AWMD ≥49 mg/wk) groups.
Data of 165 patients were included for the analyses. Mean actual warfarin dose of the study population was 25.03 ± 10.53 mg/wk. Large variability of MDE, ranging from -12.11 to 11.24 mg/wk, among algorithms was observed. International Warfarin Pharmacogenetics Consortium, Gage et al, and Ohno et al algorithms had comparable performances to Sangviroon et al algorithm, as observed by MDE of <1 mg/wk with percentage of IDP ≥40%. Further sensitivity analyses among patients requiring low and intermediate maintenance doses confirmed such findings with IDP percentage ranging from 37.8% to 59.2%. Among high-dose group, only Ohno et al and Sarapakdi et al algorithms had acceptable performance.
Warfarin PGx-guided dosing algorithms derived from large, mixed population performed comparably to Sangviroon et al algorithm. Certain algorithms should be avoided due to significant dose prediction error.
本研究旨在比较来自白种人、亚洲人和混合人群的可用药物遗传学(PGx)指导华法林剂量算法的预测准确性,以确定适合泰国人群的算法。
选择了来自不同人群的 10 种华法林剂量算法,包括白种人、东亚人、东南亚人和混合人群,并使用泰国患者的临床和遗传数据对这些算法进行了测试。通过比较每个剂量算法生成的实际华法林维持剂量(AWMD)和预测剂量之间的平均剂量误差(MDE),以及理想剂量预测百分比(IDP),测试了这些算法的性能。还通过分层患者为低(AWMD≤21mg/wk)、中(AWMD>21 至<49mg/wk)和高维持剂量(AWMD≥49mg/wk)组,对预测准确性进行了敏感性分析。
纳入了 165 名患者的数据进行分析。研究人群的平均实际华法林剂量为 25.03±10.53mg/wk。算法之间的 MDE 差异很大,范围从-12.11 到 11.24mg/wk。国际华法林药物遗传学联合会、Gage 等人和 Ohno 等人的算法与 Sangviroon 等人的算法表现相当,观察到 MDE<1mg/wk,IDP 百分比≥40%。在需要低和中维持剂量的患者中进行的进一步敏感性分析证实了这一发现,IDP 百分比范围从 37.8%到 59.2%。在高剂量组中,只有 Ohno 等人和 Sarapakdi 等人的算法具有可接受的性能。
来自大型混合人群的华法林 PGx 指导剂量算法与 Sangviroon 等人的算法表现相当。由于剂量预测误差较大,某些算法应避免使用。