Quantifying the impact of time-varying baseline risk adjustment in the self-controlled risk interval design
Quantifying the impact of time-varying baseline risk adjustment in the self-controlled risk interval design
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DOI：
10.1002/pds.3885
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发表时间：
2015-12-01
影响因子：
2.6
通讯作者：
Hua, Wei
中科院分区：
文献类型：
--
作者：
Li, Lingling;Kulldorff, Martin;Hua, Wei
目的自控风险区间设计通常用于评估急性暴露和不良事件之间的关联，隐含地调整固定的、不随时间变化的协变量。需要对时变的协变量进行明确的调整，例如，幼儿的年龄。它可以通过固定或随机调整来执行。随机平差方法可以提供有效的点和区间估计，但需要获得未暴露的基线样本的个人水平数据。固定调整法没有这一要求，将提供有效的点估计，但可能低估了方差。我们进行了一项全面的模拟研究来评估他们的表现。方法我们使用食品和药物管理局赞助的Mini-Sentinel许可证后快速免疫安全监测轮状病毒疫苗和5-36.9周儿童肠套叠研究的经验数据来设计模拟研究。令人困惑的是年龄。我们考虑了各种设计参数，包括样本量、相对风险、时变基线风险和风险区间长度。结果随机调整方法在几乎所有考虑的设置下都具有很好的性能。当用于估计时变基线风险的事件数至少等于用于估计相对风险的事件数时，固定调整方法可以作为一种很好的替代方法。结论我们成功地确定了固定调整方法可以作为一种较好的替代方法的环境，为选择和实施适当的分析方法进行自控风险区间设计提供了指导。版权所有(C)2015 John Wiley&Sons，Ltd.
Purpose The self-controlled risk interval design is commonly used to assess the association between an acute exposure and an adverse event of interest, implicitly adjusting for fixed, non-time-varying covariates. Explicit adjustment needs to be made for time-varying covariates, for example, age in young children. It can be performed via either a fixed or random adjustment. The random-adjustment approach can provide valid point and interval estimates but requires access to individual-level data for an unexposed baseline sample. The fixed-adjustment approach does not have this requirement and will provide a valid point estimate but may underestimate the variance. We conducted a comprehensive simulation study to evaluate their performance.Methods We designed the simulation study using empirical data from the Food and Drug Administration-sponsored Mini-Sentinel Post-licensure Rapid Immunization Safety Monitoring Rotavirus Vaccines and Intussusception study in children 5-36.9 weeks of age. The time-varying confounder is age. We considered a variety of design parameters including sample size, relative risk, time-varying baseline risks, and risk interval length.Results The random-adjustment approach has very good performance in almost all considered settings. The fixed-adjustment approach can be used as a good alternative when the number of events used to estimate the time-varying baseline risks is at least the number of events used to estimate the relative risk, which is almost always the case.Conclusions We successfully identified settings in which the fixed-adjustment approach can be used as a good alternative and provided guidelines on the selection and implementation of appropriate analyses for the self-controlled risk interval design. Copyright (C) 2015 John Wiley & Sons, Ltd.