An objective of randomized placebo-controlled vaccine efficacy trials is to evaluate vaccine-induced immune responses as surrogate endpoints for clinical endpoints such as HIV infection. Dean Follmann introduced augmented vaccine trial designs for evaluating immunological surrogates, wherein baseline covariates are used to predict the counterfactual vaccine-induced immune responses of placebo recipients had they been vaccinated, or uninfected placebo recipients are vaccinated at study-closeout. For these designs with case-cohort sampling of immune responses, this talk describes a potential outcomes approach for evaluating the "causal effect predictiveness" of an immune response. Estimated likelihood methods are used for estimating the causal effect predictiveness surface, which has useful interpretation in terms of how well causal vaccine effects on the immune response predict causal vaccine effects on the clinical endpoint. The methods incorporate a model for predicting ounterfactual immune responses of placebo recipients, and apply to binary, time-to-event, or quantitative clinical endpoints. More generally, this talk describes a potential outcomes approach for evaluating surrogate endpoints that departs from traditional approaches that are based solely on observable statistical associations.



Seminar Date:
March 6, 2007