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药物相互作用自控病例系列研究中的宽限期与暴露错误分类

Grace periods and exposure misclassification in self-controlled case-series studies of drug-drug interactions.

作者信息

Zhang Hanxi, Bilker Warren B, Leonard Charles E, Hennessy Sean, Miano Todd A

机构信息

Center for Real-World Safety and Effectiveness of Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.

Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.

出版信息

Am J Epidemiol. 2025 Mar 4;194(3):802-810. doi: 10.1093/aje/kwae231.

Abstract

The self-controlled case-series (SCCS) research design is increasingly used in pharmacoepidemiologic studies of drug-drug interactions (DDIs), with the target of inference being the incidence rate ratio (IRR) associated with concomitant exposure to the object plus precipitant drug vs the object drug alone. While day-level drug exposure can be inferred from dispensing claims, these inferences may be inaccurate, leading to biased IRRs. Grace periods (periods assuming continued treatment impact after days' supply exhaustion) are frequently used by researchers, but the impact of grace period decisions on bias from exposure misclassification remains unclear. Motivated by an SCCS study examining the potential DDI between clopidogrel (object) and warfarin (precipitant), we investigated bias due to precipitant or object exposure misclassification using simulations. We show that misclassified precipitant treatment always biases the estimated IRR toward the null, whereas misclassified object treatment may lead to bias in either direction or no bias, depending on the scenario. Further, including a grace period for each object dispensing may unintentionally increase the risk of misclassification bias. To minimize such bias, we recommend (1) avoiding the use of grace periods when specifying object drug exposure episodes and (2) including a washout period following each precipitant exposed period. This article is part of a Special Collection on Pharmacoepidemiology.

摘要

自控病例系列(SCCS)研究设计在药物相互作用(DDI)的药物流行病学研究中越来越常用,其推断目标是与同时暴露于目标药物加引发药物相对于单独暴露于目标药物相关的发病率比(IRR)。虽然可以从配药记录推断每日药物暴露情况,但这些推断可能不准确,导致IRR出现偏差。研究人员经常使用宽限期(即假设在供应天数耗尽后持续存在治疗影响的时间段),但宽限期决策对暴露错误分类偏差的影响尚不清楚。受一项SCCS研究的启发,该研究考察了氯吡格雷(目标药物)和华法林(引发药物)之间潜在的DDI,我们通过模拟研究了由于引发药物或目标药物暴露错误分类导致的偏差。我们发现,错误分类的引发药物治疗总是使估计的IRR向无效值偏倚,而错误分类的目标药物治疗可能导致偏差方向不定或无偏差,这取决于具体情况。此外,为每次目标药物配药设定宽限期可能会无意中增加错误分类偏差的风险。为了尽量减少此类偏差,我们建议:(1)在确定目标药物暴露发作时避免使用宽限期;(2)在每个引发药物暴露期之后设置一个洗脱期。本文是药物流行病学特刊的一部分。

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