Studies of vaccine efficacy often record both the incidence of vaccine-targeted virus strains (primary outcome) and the incidence of non-targeted strains (secondary outcome). However, standard estimates of vaccine efficacy on targeted strains ignore the data on non-targeted strains. Assuming non-targeted strains are unaffected by vaccination, we regard the secondary outcome as a negative control outcome and show how using such data can (i) increase the precision of the estimated vaccine efficacy against targeted strains in randomized trials, and (ii) reduce confounding bias of that same estimate in observational studies. For objective (i), we augment the primary outcome estimating equation with a function of the secondary outcome that is unbiased for zero. For objective (ii), we jointly estimate the treatment effects on the primary and secondary outcomes. If the bias induced by the unmeasured confounders is similar for both types of outcomes, as is plausible for factors that influence the general risk of infection, then we can use the estimated efficacy against the secondary outcomes to remove the bias from estimated efficacy against the primary outcome. We demonstrate the utility of these approaches in studies of HPV vaccines that only target a few highly carcinogenic strains. In this example, using non-targeted strains increased precision in randomized trials modestly but reduced bias in observational studies substantially.
翻译:疫苗功效的研究往往记录到疫苗针对病毒菌株的发病率(主要结果)和非目标菌株的发病率(第二结果),然而,对目标菌株的疫苗功效的标准估计忽略了非目标菌株的数据。假设非目标菌株不受接种的影响,我们认为第二结果是一种消极控制结果,并表明如何使用这些数据:(一) 提高估计疫苗对随机试验中目标菌株的功效的精确度,以及(二) 减少观察研究中同一估计结果的混乱偏差。关于目标(一),我们增加主要结果估计方程,次级结果的函数对零不偏袒。关于目标(二),我们共同估计对初级和次要结果的治疗影响。如果非目标同源虫对两种结果的偏差相似,正如影响一般感染风险的因素一样,那么我们可以使用估计的疫苗功效来消除估计对初级结果的偏差。我们展示了这些方法在HPV疫苗的研究中的效用,这些方法只针对少数高度致癌性紧张程度,但仅针对少数高致癌性临界性试验。