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利用自身配对阴性对照设计推断自然获得的免疫力。

Inference of Naturally Acquired Immunity Using a Self-matched Negative-Control Design.

机构信息

From the Center for Computational Biology, College of Engineering, University of California, Berkeley, Berkeley, CA.

Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA.

出版信息

Epidemiology. 2021 Mar 1;32(2):168-178. doi: 10.1097/EDE.0000000000001305.

Abstract

Host adaptive immune responses may protect against infection or disease when a pathogen is repeatedly encountered. The hazard ratio of infection or disease, given previous infection, is typically sought to estimate the strength of protective immunity. However, variation in individual exposure or susceptibility to infection may introduce frailty bias, whereby a tendency for infections to recur among individuals with greater risk confounds the causal association between previous infection and susceptibility. We introduce a self-matched "case-only" inference method to control for unmeasured individual heterogeneity, making use of negative-control endpoints not attributable to the pathogen of interest. To control for confounding, this method compares event times for endpoints due to the pathogen of interest and negative-control endpoints during counterfactual risk periods, defined according to individuals' infection history. We derive a standard Mantel-Haenszel (matched) odds ratio conveying the effect of prior infection on time to recurrence. We compare performance of this approach to several proportional hazards modeling frameworks and estimate statistical power of the proposed strategy under various conditions. In an example application, we use the proposed method to reestimate naturally acquired protection against rotavirus gastroenteritis using data from previously published cohort studies. This self-matched negative-control design may present a flexible alternative to existing approaches for analyzing naturally acquired immunity, as well as other exposures affecting the distribution of recurrent event times.

摘要

当病原体反复出现时,宿主适应性免疫反应可能会预防感染或疾病。给定先前的感染,通常会寻求感染或疾病的危害比,以估计保护性免疫的强度。然而,个体接触或易感染的差异可能会引入脆弱性偏差,即具有更高风险的个体中感染再次发生的趋势会混淆先前感染和易感性之间的因果关系。我们引入了一种自我匹配的“仅病例”推理方法来控制未测量的个体异质性,利用与研究病原体无关的阴性对照终点。为了控制混杂因素,该方法比较了在假想风险期内由于研究病原体和阴性对照终点而导致的终点的事件时间,该假想风险期是根据个体的感染史定义的。我们推导出一个标准的 Mantel-Haenszel(匹配)优势比,传达先前感染对复发时间的影响。我们比较了这种方法与几种比例风险建模框架的性能,并在各种条件下估计了所提出策略的统计功效。在一个示例应用中,我们使用所提出的方法使用先前发表的队列研究的数据重新估计轮状病毒胃肠炎的自然获得性保护。这种自我匹配的阴性对照设计可能是分析自然获得性免疫以及其他影响复发性事件时间分布的暴露的现有方法的灵活替代方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f59f/7850593/403746cbd96b/ede-32-168-g001.jpg

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