Bayesian Approaches on Borrowing Historical Data for Vaccine Efficacy Trials. (2nd July 2020)

• Record Type: Journal Article
• Authors: Jin, Man; Feng, Dai; Liu, Guanghan
• Is Part Of: Statistics in biopharmaceutical research. Volume 12:Number 3(2020)
• Page Start: 284
• Page End: 292
• Publication Date: 2020-07-02
• Subjects: Bayesian approach -- Beta prior -- Hierarchical models -- Power prior -- Sample size calculations -- Vaccine efficacy trials; Pharmacy -- Statistical methods -- Periodicals; Pharmaceutical biotechnology -- Statistical methods -- Periodicals; Biopharmaceutics -- Periodicals; Biometry -- Periodicals; Pharmacy -- Statistical methods; Periodicals; 615.190727
• DOI: 10.1080/19466315.2020.1736617
• Languages: English
• ISSNs: 1946-6315

Abstract

Abstract : Abstract– To evaluate a novel vaccine, randomized clinical trials are often conducted to assess how much the infection or disease rate is reduced in the vaccinated group as compared to the unvaccinated group. Because of low incidence rate for the clinical endpoint, the sample size based on exact conditional binomial test is often very large for vaccine efficacy trials, which poses big challenge for study conduct and enrollment, especially in studies with very low incidence rates. Bayesian framework provides a natural avenue to use historical information, if there is evidence to suggest similarity of the responses between the historical and current studies. In this article, we first propose a hierarchical conditional binomial model to provide a Bayesian framework to use historical information for assessing vaccine efficacy. Secondly, we propose a beta prior distribution which is equivalent to the power prior to borrow partial historical information quantitatively. Simulations are conducted to evaluate the power and Type I error for vaccine efficacy study by borrowing historical information with the proposed analytic approaches. The proposed methods are demonstrated by an example to show the improved efficacy estimation through borrowing information from a historical study.