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

Joseph G. Ibrahim, Ming Hui Chen, Haitao Chu

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

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.

Original languageEnglish (US)
Article number183
JournalBMC Medical Research Methodology
Volume12
DOIs
StatePublished - 2012

Keywords

  • Cure rate model
  • Historical data
  • Posterior distribution
  • Prior distribution

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