Department of Laboratory Medicine, University-Hospital of Padua, 35128 Padua, Italy.
Pharmacogenomics. 2011 Jan;12(1):15-25. doi: 10.2217/pgs.10.162.
A total of 371 patients under stable warfarin therapy were retrospectively selected to develop a pharmacogenetic algorithm to identify the individual maintenance dose.
MATERIALS & METHODS: The variables that were entered into the algorithm were: VKORC1, CYP2C9 and CYP4F2 polymorphisms, body surface area and age.
The percentage of cases whose predicted mean weekly warfarin dose was within 20% of the actual maintenance dose was 51.8% considering patients overall, and were 36.2, 66.2 and 55.4%, respectively, taking into account patients requiring low (≤25 mg/week), intermediate (25-45 mg/week) and high (≥45 mg/week) doses. The algorithm could correctly assign 73.8 and 63.2% of patients to the low- and high-dose regimens, respectively. We developed and validated a pharmacogenetic algorithm in a series of Italian patients, we then tested, in the same series of italian patients, the formulas of three published algorithms. These three algorithms were developed and validated by their authors in a series of patients different from our own. The performance of our algorithm in our patients series was slightly higher than that achieved when using the three other algorithms in our patients series.
The high predictive accuracy of low and high warfarin requirements of our algorithm warrants its application in prospective studies for clinical validation.
回顾性选择 371 例稳定华法林治疗患者，制定遗传药理学算法以确定个体维持剂量。
纳入算法的变量为：VKORC1、CYP2C9 和 CYP4F2 多态性、体表面积和年龄。
考虑到所有患者，预测平均每周华法林剂量与实际维持剂量相差 20%的病例比例为 51.8%，而考虑需要低（≤25mg/周）、中（25-45mg/周）和高（≥45mg/周）剂量的患者，这一比例分别为 36.2%、66.2%和 55.4%。该算法可正确将 73.8%和 63.2%的患者分别分配至低剂量和高剂量方案。我们在一系列意大利患者中开发并验证了遗传药理学算法，然后在同一组意大利患者中测试了三个已发表算法的公式。这三个算法由其作者在与我们自己不同的一系列患者中开发和验证。在我们的患者系列中，我们的算法的性能略高于在我们的患者系列中使用其他三个算法时的性能。
我们的算法对低和高华法林需求的高预测准确性证明了其在前瞻性研究中的临床验证中的应用价值。
