Estimating and Testing Vaccine Sieve Effects Using Machine Learning

When available, vaccines are an effective means of disease prevention. Unfortunately, efficacious vaccines have not yet been developed for several major infectious diseases, including HIV and malaria. Vaccine sieve analysis studies whether and how the efficacy of a vaccine varies with the genetics of the pathogen of interest, which can guide subsequent vaccine development and deployment. In sieve analyses, the effect of the vaccine on the cumulative incidence corresponding to each of several possible genotypes is often assessed within a competing risks framework. In the context of clinical trials, the estimators employed in these analyses generally do not account for covariates, even though the latter may be predictive of the study endpoint or censoring. Motivated by two recent preventive vaccine efficacy trials for HIV and malaria, we develop new methodology for vaccine sieve analysis. Our approach offers improved validity and efficiency relative to existing approaches by allowing covariate adjustment through ensemble machine learning. We derive results that indicate how to perform statistical inference using our estimators. Our analysis of the HIV and malaria trials shows markedly increased precision—up to doubled efficiency in both trials—under more plausible assumptions compared with standard methodology. Our findings provide greater evidence for vaccine sieve effects in both trials. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.若可及，疫苗乃是疾病预防的有效手段。遗憾的是，包括人类免疫缺陷病毒（HIV）和疟疾在内的多种重大传染病，目前仍未研发出具备保护效力的疫苗。疫苗筛分析（vaccine sieve analysis）旨在探究疫苗保护效力是否以及如何随目标病原体的遗传学特征发生变化，可为后续疫苗研发与部署提供指导。于疫苗筛分析中，通常会借助竞争风险框架，评估疫苗对多种潜在基因型对应的累积发病率的影响。在临床试验场景中，此类分析所采用的估计量通常未考虑协变量的影响，尽管协变量往往可对研究终点或删失情况起到预测作用。受两项近期开展的HIV与疟疾预防性疫苗效力临床试验的启发，本文提出了适用于疫苗筛分析的全新方法论。相较于现有方法，本方法通过集成机器学习实现协变量调整，从而提升了分析的有效性与统计效率。我们推导了可指导基于本研究估计量开展统计推断的理论结果。针对HIV与疟疾临床试验的分析结果显示，相较于标准方法，在更为合理的假设前提下，本方法的精度显著提升——两项试验的统计效率均可达原有水平的两倍。本研究结果为两项试验中存在疫苗筛效应提供了更为充分的证据支撑。本文的补充材料（包含可复现研究的标准化材料说明）可作为在线附录获取。