Objective: To propose and compare practical approaches that allow eliciting and using expert opinions about the benefit effect on a censored endpoint, such as event-free survival (EFS), used in the planning of a clinical trial based on Bayesian methodology.
Study design and setting: Individual interviews of 37 experts. Bayesian normal models on the log hazard ratio (HR) of EFS were implemented. We illustrate our approach by using a trial of autologous stem cell transplantation (ASCT) vs. chemotherapy (CT) in chronic lymphocytic leukemia (CLL). We elicited experts' prior beliefs about the difference in 3-year EFS between the two treatment arms, either roughly or throughout weights over the difference scale. Subsequently, a Bayesian synthesis of the information reported in the trial protocol with that in the experts' prior was performed, using: (1) the postulated treatment effect based on null (skeptical) and alternative (enthusiastic) hypotheses with shared standard error; and (2) the expected difference derived from experts' distributions.
Results: As compared with the priors based on the trial protocol data, expert priors agreed with some average from enthusiastic and skeptical information, with close standard errors.
Conclusion: This case study illustrates a rational approach to construct an expert-based prior. It should be considered as part of the design of future Bayesian trials.