Abstract
In randomized clinical trials designed to compare the magnitude of vaccine-induced immune responses between vaccination regimens, the statistical method used for the analysis typically does not account for baseline participant characteristics. This article shows that incorporating baseline variables predictive of the immunogenicity study endpoint can provide large gains in precision and power for estimation and testing of the group mean difference (requiring fewer subjects for the same scientific output) compared to conventional methods, and recommends the "semiparametric efficient" method described in Tsiatis et al. [Tsiatis AA, Davidian M, Zhang M, Lu X. Covariate adjustment for two-sample treatment comparisons in randomized clinical trials: a principled yet flexible approach. Stat Med 2007. doi:10.1002/sim.3113] for practical use. As such, vaccine clinical trial programs can be improved (1) by investigating baseline predictors (e.g., readouts from laboratory assays) of vaccine-induced immune responses, and (2) by implementing the proposed semiparametric efficient method in trials where baseline predictors are available.