Remote, bivariate prior elicitation for a Bayesian non-inferiority randomized controlled trial

Prior distributions must be specified for the parameters of interest in a Bayesian clinical trial. When existing evidence on the effects of the trial interventions is limited or inconclusive, prior distributions can be constructed with expert elicitation. However, conventional elicitation requires face-to-face interactions and intensive pre-elicitation training, which can be infeasible and costly. Our remote elicitation was based on an established expert elicitation methodology, and we incorporated bivariate prior distributions to introduce dependencies between the elicited probabilities. We aimed to elicit a prior distribution for the Croup Dosing Trial, which assesses the efficacy of two separate doses of dexamethasone on the number of return visits to the emergency department within 7 days in children with croup. This trial evaluates the non-inferiority of 0.15 mg/kg of dexamethasone, compared to the standard dose of 0.60 mg/kg to treat croup.

We conducted three remote workshops to elicit expert beliefs on the efficacy of the two doses of dexamethasone. Each workshop consisted of two survey rounds, separated by a group discussion. Prior to the workshop, experts reviewed the same current literature that was provided on the effects of the two doses of dexamethasone. Beliefs were aggregated using expert-specific bivariate distributions with latent effects. The aggregated distribution, along with the surveyed non-inferiority margin, determined the sample size for the Bayesian non-inferiority trial design.

Twelve emergency medicine physicians participated in our remote elicitation exercise. The elicitation generated a prior distribution centered at 6% for the 0.60 mg/kg dose and 8% for the 0.15 mg/kg dose. The aggregated prior distribution produced a sample size of 1850, based on a non-inferiority margin of 4%.

We elicited a prior distribution that incorporated past evidence and expert opinion. The elicited prior is consistent with previous literature on the efficacy of the dexamethasone doses in treating croup. Our approach demonstrates the feasibility of remotely eliciting bivariate distributions to design clinical trials.

NCT06272383 (Registered May 8, 2024).