Estimating Malaria Vaccine Efficacy in the Absence of a Gold Standard Case Definition: Mendelian Factorial Design
无金标准病例定义下的疟疾疫苗效力估计:孟德尔析因设计AI 解读 ↓
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AI 根据所提供的论文材料归类:摘要利用随机治疗与遗传变异识别疫苗效力,并提出受孟德尔随机化启发的设计,直接属于因果推断。
无金标准病例定义下的疟疾疫苗效力估计:孟德尔析因设计AI 解读 ↓
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Accurate estimates of malaria vaccine efficacy require a reliable definition of a malaria case. However, the symptoms of clinical malaria are unspecific, overlapping with other childhood illnesses. Additionally, children in endemic areas tolerate varying levels of parasitemia without symptoms. Together, this makes finding a gold-standard case definition challenging. We present a method to identify and estimate malaria vaccine efficacy that does not require an observable gold-standard case definition. Instead, we leverage genetic traits that are protective against malaria but not against other illnesses, for example, the sickle cell trait, to identify vaccine efficacy in a randomized trial. Inspired by Mendelian randomization, we introduce Mendelian factorial design, a method that augments a randomized trial with genetic variation to produce a natural factorial experiment, which identifies vaccine efficacy under realistic assumptions. A robust, covariance adjusted estimation procedure is developed for estimating vaccine efficacy on the risk ratio and incidence rate ratio scales. Simulations suggest that our estimator has good performance whereas standard methods are systematically biased. We demonstrate that a combined estimator using both our proposed estimator and the standard approach yields significant improvements when the Mendelian factor is only weakly protective. Our method can be applied in vaccine and prevention trials of other childhood diseases that have no gold-standard case definition and known genetic risk factors. Supplementary materials for this article are available online.