Gilbert Peter B, Fong Youyi, Kenny Avi, Carone Marco
Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA and Department of Biostatistics, University of Washington, Seattle, WA, USA.
Department of Biostatistics, University of Washington, Seattle, WA, USA.
Biostatistics. 2022 Jul 15. doi: 10.1093/biostatistics/kxac24.
An immune correlate of risk (CoR) is an immunologic biomarker in vaccine recipients associated with an infectious disease clinical endpoint. An immune correlate of protection (CoP) is a CoR that can be used to reliably predict vaccine efficacy (VE) against the clinical endpoint and hence is accepted as a surrogate endpoint that can be used for accelerated approval or guide use of vaccines. In randomized, placebo-controlled trials, CoR analysis is limited by not assessing a causal vaccine effect. To address this limitation, we construct the controlled risk curve of a biomarker, which provides the causal risk of an endpoint if all participants are assigned vaccine and the biomarker is set to different levels. Furthermore, we propose a causal CoP analysis based on controlled effects, where for the important special case that the biomarker is constant in the placebo arm, we study the controlled vaccine efficacy curve that contrasts the controlled risk curve with placebo arm risk. We provide identification conditions and formulae that account for right censoring of the clinical endpoint and two-phase sampling of the biomarker, and consider G-computation estimation and inference under a semiparametric model such as the Cox model. We add modular approaches to sensitivity analysis that quantify robustness of CoP evidence to unmeasured confounding. We provide an application to two phase 3 trials of a dengue vaccine indicating that controlled risk of dengue strongly varies with 50$%$ neutralizing antibody titer. Our work introduces controlled effects causal mediation analysis to immune CoP evaluation.
风险免疫关联指标（CoR）是疫苗接种者体内与传染病临床终点相关的免疫生物标志物。保护免疫关联指标（CoP）是一种能够可靠预测针对临床终点的疫苗效力（VE）的CoR，因此被视为可用于加速批准或指导疫苗使用的替代终点。在随机安慰剂对照试验中，CoR分析由于未评估疫苗的因果效应而受到限制。为解决这一限制，我们构建了生物标志物的对照风险曲线，该曲线给出了如果所有参与者都接种疫苗且生物标志物设定为不同水平时终点的因果风险。此外，我们提出了基于对照效应的因果CoP分析，对于安慰剂组中生物标志物恒定的重要特殊情况，我们研究将对照风险曲线与安慰剂组风险进行对比的对照疫苗效力曲线。我们提供了考虑临床终点右删失和生物标志物两阶段抽样的识别条件和公式，并在诸如Cox模型等半参数模型下考虑G计算估计和推断。我们增加了模块化的敏感性分析方法，以量化CoP证据对未测量混杂因素的稳健性。我们给出了登革热疫苗两项3期试验的应用，表明登革热的对照风险随50%中和抗体滴度有很大差异。我们的工作将对照效应因果中介分析引入免疫CoP评估。
