Bronchiolitis is one of the most common infectious diseases for infants and young children. Previous studies showed a substantial burden of illness and health-related expenditures of the cost for hospitalizations for bronchiolitis. Currently a phase III, multicentre, randomized, double blind, placebo- controlled trial, named the BIPED Study, is being conducted to determine whether the combination of epinephrine and dexamethasone is effective in reducing hospital admission for infants presenting with bronchiolitis to the emergency department (ED).  

The IMPaCT team is working to determine the sample size for the BIPED study based on a Bayesian analysis. To achieve this, they are undertaking a remote elicitation exercise, which is used to convert experts’ knowledge into quantitative expressions to obtain a prior distribution. Then, they will use simulation based methods to determine the sample size required for the BIPED study based on the elicited prior distribution.  

This project will:

  1. Improve the current elicitation technique in multicentre, international randomized clinical trials (RCT) 
  2. Apply Bayesian sample size determination in a Phase III RCT  

Current elicitation approaches either require face-to-face sessions, which are costly to organize or expert surveys, which have low response rate. Neither of these methods are easy and practical to implement for multicentre, international RCT. Thus, we are using a novel approach to remotely elicit expert opinion to form the prior probability distribution, which is easy to implement and can be replicated by other clinical studies.