Spline-based self-controlled case series method.

Spline-based self-controlled case series method.
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基于样条的自控病例系列方法。

DOI:
10.1002/sim.7311
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发表时间:
2017
影响因子:
2
通讯作者:
Ghebremichael-Weldeselassie Y
Ghebremichael-Weldeselassie Y
中科院分区:
医学3区
文献类型:
--
作者:
Ghebremichael-Weldeselassie Y

文献摘要

相似文献

自身对照病例系列(SCCS)方法是队列和病例对照方法等研究设计的替代方法,用于调查疫苗或其他药物暴露的时间与不良事件之间的潜在关联。它只需要关于病例的信息,即至少经历过一次不良事件的个人,并自动控制所有可能改变暴露与不良事件之间真实关联的固定混杂变量。另一方面,年龄等时变混杂因素不是自动控制的,必须明确允许。最初的SCCS方法使用阶跃函数来表示风险期(暴露时间的窗口)和年龄效应。因此,暴露风险期和/或年龄组必须事先确定,但组边界的选择不当可能会导致估计有偏见。在本文中,我们提出了一种非参数SCCS方法,其中年龄效应和曝光效应同时用样条函数来表示。为了避免在SCCS方法的似然函数中对这两个样条函数的乘积进行数值积分,我们根据M-样条积分的定义定义了I-样条的第一、二、三次积分。仿真研究表明,该方法具有较好的性能。这种新方法被应用于儿科疫苗的数据。版权所有©2017 John Wiley&Sons,Ltd.
The self‐controlled case series (SCCS) method is an alternative to study designs such as cohort and case control methods and is used to investigate potential associations between the timing of vaccine or other drug exposures and adverse events. It requires information only on cases, individuals who have experienced the adverse event at least once, and automatically controls all fixed confounding variables that could modify the true association between exposure and adverse event. Time‐varying confounders such as age, on the other hand, are not automatically controlled and must be allowed for explicitly. The original SCCS method used step functions to represent risk periods (windows of exposed time) and age effects. Hence, exposure risk periods and/or age groups have to be prespecified a priori, but a poor choice of group boundaries may lead to biased estimates. In this paper, we propose a nonparametric SCCS method in which both age and exposure effects are represented by spline functions at the same time. To avoid a numerical integration of the product of these two spline functions in the likelihood function of the SCCS method, we defined the first, second, and third integrals of I‐splines based on the definition of integrals of M‐splines. Simulation studies showed that the new method performs well. This new method is applied to data on pediatric vaccines. Copyright © 2017 John Wiley & Sons, Ltd.