Peter Gilbert, PhD
Professor, Vaccine and Infectious Disease Division
Fred Hutchinson Cancer Research Center
Statistical Evaluation of Immune Correlates of Protection in the Moderna COVE COVID-19 Vaccine Efficacy Trial
Randomized, double-blind phase 3 COVID-19 vaccine efficacy trials assess how well candidate vaccines prevent infection and disease caused by the SARS-CoV-2 virus. The NIH-supported COVID-19 Prevention Network (CoVPN) is co-conducting (with vaccine manufacturers) five such phase 3 trials, which include the objective to assess post-vaccination antibody biomarkers as various types of “immune correlates of protection (CoPs).” CoPs can be formally defined using several statistical frameworks, including risk prediction, treatment effect modification, treatment effect mediation, and surrogate/replacement endpoint evaluation. An ultimate application of the statistical analyses is to help define surrogate endpoints that can constitute the basis for traditional or accelerated approval of vaccines. I will describe application of CoVPN statistical methods to the Moderna COVE study. Based on controlled effects causal inference, vaccine efficacy estimates were 78% (95% CI 54, 89%), 91% (87, 94%), and 96% (94, 98%) at post-vaccination neutralizing antibody titers of 10, 100, or 1000 IU50/ml, respectively. Based on natural effects mediation analysis, an estimated 68% (58, 78%) of the vaccine’s overall efficacy was mediated through neutralizing antibody titers. These results help define a biomarker with utility to influence decision-making for COVID-19 vaccines. Issues in assessing and interpreting CoPs are discussed, including the genetics of SARS-CoV-2.
