title: Incorporation of genuine prior information in cost-effectiveness analysis of clinical trial data.
abstract: The Bayesian approach to statistics has been growing rapidly in popularity as an alternative to the frequentist approach in the appraisal of healthcare technologies in clinical trials. Bayesian methods have significant advantages over classical frequentist statistical methods and the presentation of evidence to decision makers. A fundamental feature of a Bayesian analysis is the use of prior information as well as the clinical trial data in the final analysis. However, the incorporation of prior information remains a controversial subject that provides a potential barrier to the acceptance of practical uses of Bayesian methods. The purpose of this paper is to stimulate a debate on the use of prior information in evidence submitted to decision makers. We discuss the advantages of incorporating genuine prior information in cost-effectiveness analyses of clinical trial data and explore mechanisms to safeguard scientific rigor in the use of such prior information.
authors.affiliation: University of Sheffield, USA.
authors.forename: John W
authors.initials: JW
authors.lastname: Stevens
authors.forename: Anthony
authors.initials: A
authors.lastname: O'Hagan
mesh_terms: D001499:Bayes Theorem; D002986:Clinical Trials as Topic / Q000191:economics*; D003362:Cost-Benefit Analysis / Q000706:statistics & numerical data*; D006801:Humans; D013673:Technology Assessment, Biomedical / Q000191:economics*; D006113:United Kingdom