Brookhart M Alan, Wang Philip S, Solomon Daniel H, Schneeweiss Sebastian
Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital/Harvard Medical School, Boston, MA 02120, USA.
Epidemiology. 2006 May;17(3):268-75. doi: 10.1097/01.ede.0000193606.58671.c5.
Postmarketing observational studies of the safety and effectiveness of prescription medications are critically important but fraught with methodological problems. The data sources available for such research often lack information on indications and other important confounders for the drug exposure under study. Instrumental variable methods have been proposed as a potential approach to control confounding by indication in nonexperimental studies of treatment effects; however, good instruments are hard to find.
We propose an instrument for use in pharmacoepidemiology that is based on a time-varying estimate of the prescribing physician's preference for one drug relative to a competing therapy. The use of this instrument is illustrated in a study comparing the effect of exposure to COX-2 inhibitors with nonselective, nonsteroidal antiinflammatory medications on gastrointestinal complications.
Using conventional multivariable regression adjusting for 17 potential confounders, we found no protective effect due to COX-2 use within 120 days from the initial exposure (risk difference = -0.06 per 100 patients; 95% confidence interval = -0.26 to 0.14). However, the proposed instrumental variable method attributed a protective effect to COX-2 exposure (-1.31 per 100 patients; -2.42 to -0.20) compatible with randomized trial results (-0.65 per 100 patients; -1.08 to -0.22).
The instrumental variable method that we have proposed appears to have substantially reduced the bias due to unobserved confounding. However, more work needs to be done to understand the sensitivity of this approach to possible violations of the instrumental variable assumptions.
对处方药安全性和有效性进行上市后观察性研究至关重要,但存在诸多方法学问题。此类研究可用的数据来源往往缺乏所研究药物暴露的适应症及其他重要混杂因素的信息。在治疗效果的非实验性研究中,工具变量法已被提议作为一种控制适应症混杂的潜在方法;然而,好的工具难以找到。
我们提出一种用于药物流行病学的工具,该工具基于对开处方医生相对于竞争疗法对一种药物的偏好的时变估计。在一项比较接触COX - 2抑制剂与非选择性非甾体抗炎药对胃肠道并发症影响的研究中展示了该工具的使用。
使用针对17个潜在混杂因素进行调整的传统多变量回归分析,我们发现在首次暴露后120天内使用COX - 2药物没有保护作用(风险差异 = 每100名患者 - 0.06;95%置信区间 = - 0.26至0.14)。然而,所提出的工具变量法将保护作用归因于COX - 2暴露(每100名患者 - 1.31; - 2.42至 - 0.20),这与随机试验结果(每100名患者 - 0.65; - 1.08至 - 0.22)相符。
我们提出的工具变量法似乎已大幅减少了因未观察到的混杂因素导致的偏差。然而,还需要做更多工作来了解该方法对工具变量假设可能违反情况的敏感性。