Bayesian Analysis

Commensurate Priors for Incorporating Historical Information in Clinical Trials Using General and Generalized Linear Models

Brian P. Hobbs, Daniel J. Sargent, and Bradley P. Carlin

Full-text: Open access

Abstract

Assessing between-study variability in the context of conventional random-effects meta-analysis is notoriously difficult when incorporating data from only a small number of historical studies. In order to borrow strength, historical and current data are often assumed to be fully homogeneous, but this can have drastic consequences for power and Type I error if the historical information is biased. In this paper, we propose empirical and fully Bayesian modifications of the commensurate prior model (Hobbs et al. 2011) extending Pocock (1976), and evaluate their frequentist and Bayesian properties for incorporating patient-level historical data using general and generalized linear mixed regression models. Our proposed commensurate prior models lead to preposterior admissible estimators that facilitate alternative bias-variance trade-offs than those offered by pre-existing methodologies for incorporating historical data from a small number of historical studies. We also provide a sample analysis of a colon cancer trial comparing time-to-disease progression using a Weibull regression model.

Article information

Source
Bayesian Anal. Volume 7, Number 3 (2012), 639-674.

Dates
First available in Project Euclid: 28 August 2012

Permanent link to this document
https://projecteuclid.org/euclid.ba/1346158779

Digital Object Identifier
doi:10.1214/12-BA722

Mathematical Reviews number (MathSciNet)
MR2981631

Zentralblatt MATH identifier
1330.62131

Keywords
clinical trials historical controls meta-analysis Bayesian analysis survival analysis correlated data

Citation

Hobbs, Brian P.; Sargent, Daniel J.; Carlin, Bradley P. Commensurate Priors for Incorporating Historical Information in Clinical Trials Using General and Generalized Linear Models. Bayesian Anal. 7 (2012), no. 3, 639--674. doi:10.1214/12-BA722. https://projecteuclid.org/euclid.ba/1346158779


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