B1204
Title: Surrogate marker assessment using mediation analyses in a case-cohort design
Authors: Yen-Tsung Huang - Academia Sinica (Taiwan) [presenting]
Abstract: The identification of surrogate markers for gold-standard outcomes in clinical trials enables future cost-effective trials that target the identified markers. Due to resource limitations, these surrogate markers may be collected only for cases and for a subset of the trial cohort, i.e., the case-cohort design. Motivated by a COVID-19 vaccine trial, we propose methods of assessing the surrogate markers for a time-to-event outcome in a case-cohort design by using mediation and instrumental variable (IV) analyses. In the mediation analysis, we decomposed the vaccine effect on COVID-19 risk into an indirect effect (the effect mediated through the surrogate marker such as neutralizing antibodies), and a direct effect (the effect not mediated by the marker), and we propose that the mediation proportions are surrogacy indices. We employed weighted estimating equations derived from nonparametric maximum likelihood estimators (NPMLEs) under semiparametric probit models for the time-to-disease outcome. We plugged in the weighted NPMLEs to construct estimators for the aforementioned causal effects and surrogacy indices, and we determined the asymptotic properties of the proposed estimators. Applying the proposed mediation and IV analyses to a mock COVID-19 vaccine trial data, we found that 84.2\% of the vaccine efficacy was mediated by 50\% pseudovirus-neutralizing antibody.