All Times EDT
Keywords: Bayesian design, Group sequential design, Interim analysis, Vaccine trial, Phase III
Phase III trials often require large sample sizes, leading to high costs and delays in clinical decision-making. Group sequential designs can improve trial efficiency by allowing early stopping for efficacy and/or futility and thus may decrease the sample size, trial duration and associated costs. Bayesian approaches may offer additional benefits by incorporating previous information into the analyses and using decision criteria that are more practically relevant than those used in frequentist approaches. Frequentist group sequential designs have often been used for phase III studies, but the use of Bayesian group sequential designs is less common. This talk will present how Bayesian group sequential designs was used for phase III trials conducted in COVID-19 mRNA vaccine trial. This trial incorporates multiple interim analyses to assess early efficacy and futility of the vaccine. The Bayesian framework enabled us to obtain efficient designs using decision criteria based on the probability of benefit or harm. It also enabled us to incorporate information from previous studies on the treatment effect via the prior distributions. For COVID-19 vaccine trial, vaccine efficacy was based on achieving a sufficiently high Bayesian posterior probability. In addition, this trial has incorporated early stopping for futility based on Bayesian predictive probabilities. The talk will include key statistical aspects and regulatory challenges of the design.