Bayesian adaptive clinical trials: a dream for statisticians only?

Stat Med. 2012 May 20;31(11-12):1002-13. doi: 10.1002/sim.4363. Epub 2011 Sep 9.

Abstract

Adaptive or 'flexible' designs have emerged, mostly within frequentist frameworks, as an effective way to speed up the therapeutic evaluation process. Because of their flexibility, Bayesian methods have also been proposed for Phase I through Phase III adaptive trials; however, it has been reported that they are poorly used in practice. We aim to describe the international scientific production of Bayesian clinical trials by investigating the actual development and use of Bayesian 'adaptive' methods in the setting of clinical trials. A bibliometric study was conducted using the PubMed and Science Citation Index-Expanded databases. Most of the references found were biostatistical papers from various teams around the world. Most of the authors were from the US, and a large proportion was from the MD Anderson Cancer Center (University of Texas, Houston, TX). The spread and use of these articles depended heavily on their topic, with 3.1% of the biostatistical articles accumulating at least 25 citations within 5 years of their publication compared with 15% of the reviews and 32% of the clinical articles. We also examined the reasons for the limited use of Bayesian adaptive design methods in clinical trials and the areas of current and future research to address these challenges. Efforts to promote Bayesian approaches among statisticians and clinicians appear necessary.

MeSH terms

  • Bayes Theorem*
  • Clinical Trials, Phase I as Topic / statistics & numerical data*
  • Clinical Trials, Phase III as Topic / statistics & numerical data*
  • Data Interpretation, Statistical
  • Humans
  • Meta-Analysis as Topic
  • Models, Statistical
  • Research Design / statistics & numerical data