A practical approach for eliciting expert prior beliefs about cancer survival in phase III randomized trial

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.

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.

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.

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.