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Open Access Research article

Bayesian methods in clinical trials: a Bayesian analysis of ECOG trials E1684 and E1690

Joseph G Ibrahim1*, Ming-Hui Chen2 and Haitao Chu3

Author Affiliations

1 Department of Biostatistics, University of North Carolina, McGavran Greenberg Hall, CB#7420, Chapel Hill, NC, 27599, USA

2 Department of Statistics, University of Connecticut, Storrs, CT, USA

3 Division of Biostatistics, University of Minnesota, Minneapolis, MN, USA

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BMC Medical Research Methodology 2012, 12:183  doi:10.1186/1471-2288-12-183

Published: 29 November 2012

Abstract

Background

E1684 was the pivotal adjuvant melanoma trial for establishment of high-dose interferon (IFN) as effective therapy of high-risk melanoma patients. E1690 was an intriguing effort to corroborate E1684, and the differences between the outcomes of these trials have embroiled the field in controversy over the past several years. The analyses of E1684 and E1690 were carried out separately when the results were published, and there were no further analyses trying to perform a single analysis of the combined trials.

Method

In this paper, we consider such a joint analysis by carrying out a Bayesian analysis of these two trials, thus providing us with a consistent and coherent methodology for combining the results from these two trials.

Results

The Bayesian analysis using power priors provided a more coherent flexible and potentially more accurate analysis than a separate analysis of these data or a frequentist analysis of these data. The methodology provides a consistent framework for carrying out a single unified analysis by combining data from two or more studies.

Conclusions

Such Bayesian analyses can be crucial in situations where the results from two theoretically identical trials yield somewhat conflicting or inconsistent results.

Keywords:
Cure rate model; Historical data; Prior distribution; Posterior distribution