Constructing Relative Effect Priors for Research Prioritization and Trial Design: A Meta-epidemiological Analysis.

ABSTRACT:

Background

Bayesian methods have potential for efficient design of randomized clinical trials (RCTs) by incorporating existing evidence. Furthermore, value of information (VOI) methods estimate the value of reducing decision uncertainty, aiding transparent research prioritization. These methods require a prior distribution describing current uncertainty in key parameters, such as relative treatment effect (RTE). However, at the time of designing and commissioning research, there may be no data to base the prior on. The aim of this article is to present methods to construct priors for RTEs based on a collection of previous RCTs.

Methods

We developed 2 Bayesian hierarchical models that captured variability in RTE between studies within disease area accounting for study charact

SUBMITTER: Glynn D 

PROVIDER: S-EPMC10336712 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature