Institute of Geriatric Cardiology, General Hospital of People's Liberation Army, Beijing 100853, China.
Thromb Res. 2012 Sep;130(3):435-40. doi: 10.1016/j.thromres.2012.02.003. Epub 2012 Feb 27.
Multiple warfarin pharmacogenetic algorithms have been confirmed to predict warfarin dose more accurately than clinical algorithm or the fixed-dose approach. However, their performance has never been objectively evaluated in patients under low intensity warfarin anticoagulation, which is optimal for prevention of thromboembolism in Asian patients.
We sought to compare the performances of 8 eligible pharmacogenetic algorithms in a cohort of Chinese patients (n=282) under low intensity warfarin anticoagulation with target international normalized ratio (INR) ranged from 1.6 to 2.5. The performance of each algorithm was evaluated by calculating the percentage of patients whose predicted dose fell within 20% of their actual therapeutic dose (percentage within 20%), and the mean absolute error (MAE) between each predicted dose and actual stable dose.
In the entire cohort, the pharmacogenetic algorithms could predict warfarin dose with the average MAE of 0.87 ± 0.17 mg/day (0.73-1.17 mg/day), and the average percentage within 20% of 43.8% ± 8.1% (29.1% - 52.1%). By pairwise comparison, warfarin dose prediction was significantly more accurate with the algorithms derived from Asian patients (48.6% - 50.0%) than those from Caucasian patients (29.1% - 39.7%; odds ratio [OR]: 1.61-3.36, p ≤ 0.02). Algorithms with additional covariates of INR values or CYP4F23 performed better than those without the covariates (adding INR: OR: 1.71 (1.08-2.72), p =0.029; adding CYP4F23: OR: 2.67(1.41-5.05), p =0.004). When the patients were stratified according to the dose range, the algorithms from Caucasian and racially mixed populations tended to perform better in higher dose group (≥ 4.5mg/day), and algorithms from Asian populations performed better in intermediate dose group (1.5-4.5mg/day). None of the algorithms performed well in lower dose group (≤ 1.5mg/day).
No eligible pharmacogenetic algorithm could perform the best for all dosing range in the Chinese patients under low intensity warfarin anticoagulation. Construction of a refinement pharmacogenetic algorithm integrating 3 genotypes (CYP2C9, VKORC1 and CYP4F2) and INR data should be warranted to improve the warfarin dose prediction in such patients.
多种华法林药物遗传学算法已被证实能比临床算法或固定剂量法更准确地预测华法林剂量。然而，它们在亚洲患者血栓栓塞预防的低强度华法林抗凝下的表现从未被客观评估过，这是最理想的。
我们试图在一个低强度华法林抗凝的中国患者队列（n=282）中比较 8 种合格的药物遗传学算法的性能，目标国际标准化比值（INR）范围为 1.6 至 2.5。通过计算预测剂量与实际稳定剂量相差 20%的患者百分比（20%内的百分比）和每个预测剂量与实际稳定剂量之间的平均绝对误差（MAE），来评估每个算法的性能。
在整个队列中，药物遗传学算法可以预测华法林剂量，平均 MAE 为 0.87±0.17mg/天（0.73-1.17mg/天），20%内的平均百分比为 43.8%±8.1%（29.1%-52.1%）。通过两两比较，来自亚洲患者的算法（48.6%-50.0%）比来自白种人的算法（29.1%-39.7%；比值比[OR]：1.61-3.36，p≤0.02）能更准确地预测华法林剂量。有 INR 值或 CYP4F23 附加协变量的算法比没有协变量的算法更好（增加 INR：OR：1.71（1.08-2.72），p=0.029；增加 CYP4F23：OR：2.67（1.41-5.05），p=0.004）。当根据剂量范围对患者进行分层时，来自白种人和混合种族人群的算法在较高剂量组（≥4.5mg/天）中表现更好，而来自亚洲人群的算法在中等剂量组（1.5-4.5mg/天）中表现更好。没有一个算法在低剂量组（≤1.5mg/天）表现良好。
在低强度华法林抗凝的中国患者中，没有一种合格的药物遗传学算法可以在所有剂量范围内表现最好。应构建一种整合 3 种基因型（CYP2C9、VKORC1 和 CYP4F2）和 INR 数据的精细化药物遗传学算法，以提高此类患者的华法林剂量预测准确性。
