TL;DR
This paper introduces methods to improve the accuracy and precision of HPV vaccine efficacy estimates by leveraging data on non-targeted strains as negative controls, especially in observational studies.
Contribution
It proposes novel statistical approaches that incorporate non-targeted HPV strain data to enhance efficacy estimation and reduce bias in both randomized and observational studies.
Findings
Increased precision in randomized trials
Significant bias reduction in observational studies
Effective use of non-targeted strain data as negative controls
Abstract
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…
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