Schneeweiss S
Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Clin Pharmacol Ther. 2007 Aug;82(2):143-56. doi: 10.1038/sj.clpt.6100249. Epub 2007 Jun 6.
Physicians and insurers need to weigh the effectiveness of new drugs against existing therapeutics in routine care to make decisions about treatment and formularies. Because Food and Drug Administration (FDA) approval of most new drugs requires demonstrating efficacy and safety against placebo, there is limited interest by manufacturers in conducting such head-to-head trials. Comparative effectiveness research seeks to provide head-to-head comparisons of treatment outcomes in routine care. Health-care utilization databases record drug use and selected health outcomes for large populations in a timely way and reflect routine care, and therefore may be the preferred data source for comparative effectiveness research. Confounding caused by selective prescribing based on indication, severity, and prognosis threatens the validity of non-randomized database studies that often have limited details on clinical information. Several recent developments may bring the field closer to acceptable validity, including approaches that exploit the concepts of proxy variables using high-dimensional propensity scores, within-patient variation of drug exposure using crossover designs, and between-provider variation in prescribing preference using instrumental variable (IV) analyses.
医生和保险公司需要在常规护理中权衡新药与现有治疗方法的有效性,以便做出治疗和药品处方集的决策。由于美国食品药品监督管理局(FDA)对大多数新药的批准要求证明其相对于安慰剂的疗效和安全性,因此制造商对进行此类直接比较试验的兴趣有限。比较效果研究旨在对常规护理中的治疗结果进行直接比较。医疗保健利用数据库及时记录大量人群的药物使用情况和选定的健康结果,并反映常规护理,因此可能是比较效果研究的首选数据源。基于适应症、严重程度和预后的选择性处方所导致的混杂因素,威胁着非随机数据库研究的有效性,这类研究通常在临床信息方面细节有限。最近的几项进展可能会使该领域更接近可接受的有效性,包括利用高维倾向评分的代理变量概念、使用交叉设计的药物暴露患者内变异以及使用工具变量(IV)分析的处方偏好提供者间变异等方法。