Sensitivity analysis and external adjustment for unmeasured confounders in epidemiologic database studies of therapeutics
Sensitivity analysis and external adjustment for unmeasured confounders in epidemiologic database studies of therapeutics
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DOI：
10.1002/pds.1200
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发表时间：
2006-05-01
影响因子：
2.6
通讯作者：
Schneeweiss, Sebastian
中科院分区：
文献类型：
--
作者：
Schneeweiss, Sebastian
大型医疗保健利用数据库经常用于分析处方药和生物制剂的非预期效应。需要临床参数、生活方式或非处方药详细信息的混杂因素通常在此类数据集中不被测量，从而导致残余混杂偏倚.Objective This paper提供了一种系统的敏感性分析方法，以调查使用卫生保健利用数据库的药物流行病学研究中残余混杂因素的影响.方法确定了敏感性分析的四种基本方法：（1）基于一系列知情假设的敏感性分析;（2）分析以确定解释观察到的药物结局相关性所需的剩余混杂因素的强度;（3）考虑到使用代数解的调查数据中关于单一二元混杂因素的额外信息，对药物结局相关性进行外部调整;（4）外部调整，考虑来自外部信息来源的任何分布的多个混杂因素的联合分布，使用倾向得分校准。结论敏感性分析和外部调整可以提高我们对流行病学数据库研究中药物和生物制剂效应的理解。随着易于应用的技术的可用性，敏感性分析应更频繁地使用，取代残留混杂的定性讨论。版权所有（c）2006约翰威利父子有限公司。
Background Large health care utilization databases are frequently used to analyze unintended effects of prescription drugs and biologics. Confounders that require detailed information on clinical parameters, lifestyle, or over-the-counter medications are often not measured in such datasets, causing residual confounding bias.Objective This paper provides a systematic approach to sensitivity analyses to investigate the impact of residual confounding in pharmacoepidemiologic studies that use health care utilization databases.Methods Four basic approaches to sensitivity analysis were identified: (1) sensitivity analyses based on an array of informed assumptions; (2) analyses to identify the strength of residual confounding that would be necessary to explain an observed drug-outcome association; (3) external adjustment of a drug-outcome association given additional information on single binary confounders from survey data using algebraic solutions; (4) external adjustment considering the joint distribution of multiple confounders of any distribution from external sources of information using propensity score calibration.Conclusion Sensitivity analyses and external adjustments can improve our understanding of the effects of drugs and biologics in epidemiologic database studies. With the availability of easy-to-apply techniques, sensitivity analyses should be used more frequently, substituting qualitative discussions of residual confounding. Copyright (c) 2006 John Wiley & Sons, Ltd.