(untitled) (Epidemiology, Biostatistics, and Public Health, 2022)
Background: despite the widespread application of Bayesian methods in meta-analysis, the incorporation of clinical informative priors based upon expert opinion is rare. Methods: a questionnaire to elicit beliefs about five risk factors for falls in older people was administered to a sample of geriatricians and general practitioners (GPs). The experts were asked to provide a point estimate and upper and lower limits of each relative risk. The elicited opinions were translated into different prior distributions and included in a Bayesian meta-analysis of prospective studies. Frequentist, Bayesian non-informative and fully Bayesian approaches were compared. Results: almost all the clinicians provided the requested information. In most cases, the variability across published studies was greater or similar to that across clinicians. Geriatricians provided more consistent estimates than GPs. When fewer studies were available, the use of the informative prior provided by geriatricians reduced the width of the credibility interval with respect to the frequentist or Bayesian non-informative approaches. Enthusiastic and skeptical priors led to results strongly driven by the prior distribution. Conclusions: this study presents a feasible method for belief elicitation and Bayesian priors’ assessment. The inclusion of external information showed to be useful when only few and/or heterogeneous studies were available from the literature.