Tan S L, Li Z, Song G B, Liu L M, Zhang W, Peng J, Zhang T, Jia F F, Zhou G, Zhou H H, Zhou X M
Institute of Clinical Pharmacology, Central South University, Changsha, China.
Pharmazie. 2012 Nov;67(11):930-7.
Pharmacogenetics-based algorithms would be especially desirable for patients undergoing heart valve replacement (HVR), who are particularly sensitive to warfarin during the initial treatment phase following surgery. We aimed to derive a warfarin dosing algorithm from data of Chinese patients undergoing HVR, and to compare it with previously published dosing algorithms as applied to our HVR patients.
641 Chinese HVR patients on stable maintenance dose of warfarin were enrolled from a single clinic site. Data of 321 patients were used to derive a warfarin dosing algorithm using stepwise multiple linear regression analysis. Previously published algorithms were selected from Pubmed database for comparison. The performance of all the algorithms was characterized according to mean absolute error (MAE) and percentage of predicted doses falling within +/- 20% of clinically observed doses (percentage of ideal prediction) in the other 320 patients.
The newly developed algorithm included eight factors: VKORC1-1639G > A, CYP2C9*3, BSA, age, number of increasing INR drugs, smoking habit, preoperative stroke history and hypertension. Our algorithm accounted for 56.4% of variations in the inter-patient warfarin stable doses. All the algorithms showed better performance in a medium-dose (1.88-4.38 mg/day) and high-dose (> or = 4.38 mg/day) groupings than in a low-dose (< or = 1.88 mg/day) grouping. Compared with the 14 previously published algorithms, our algorithm had the lowest MAE (-0.07 mg/day) and the highest percentage of ideal prediction (62.8%) in the total validation cohort.
Our warfarin dosing algorithm is potentially useful for patients whose population profiles are similar to those of our patients.
基于药物遗传学的算法对于接受心脏瓣膜置换术（HVR）的患者尤为适用，这些患者在术后初始治疗阶段对华法林特别敏感。我们旨在从中国接受HVR的患者数据中推导华法林给药算法，并将其与应用于我们的HVR患者的先前发表的给药算法进行比较。
从单个临床地点招募了641名接受稳定维持剂量华法林治疗的中国HVR患者。使用321名患者的数据，通过逐步多元线性回归分析推导华法林给药算法。从PubMed数据库中选择先前发表的算法进行比较。根据平均绝对误差（MAE）以及预测剂量落在临床观察剂量的+/- 20%范围内的百分比（理想预测百分比），对其他320名患者中所有算法的性能进行表征。
新开发的算法包括八个因素：VKORC1-1639G>A、CYP2C9*3、体表面积（BSA）、年龄、增加国际标准化比值（INR）药物的数量、吸烟习惯、术前中风史和高血压。我们的算法解释了患者间华法林稳定剂量变化的56.4%。所有算法在中剂量（1.88 - 4.38毫克/天）和高剂量（≥4.38毫克/天）分组中的表现优于低剂量（≤1.88毫克/天）分组。与先前发表的14种算法相比，我们的算法在总验证队列中的平均绝对误差最低（-0.07毫克/天），理想预测百分比最高（62.8%）。
我们的华法林给药算法对于人群特征与我们的患者相似的患者可能有用。
