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bcrm: Bayesian Continual Reassessment Method Designs for Phase I Dose-Finding Trials

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  • Sweeting, Michael
  • Mander, Adrian
  • Sabin, Tony

Abstract

This paper presents the R package bcrm for conducting and assessing Bayesian continual reassessment method (CRM) designs in Phase I dose-escalation trials. CRM designsare a class of adaptive design that select the dose to be given to the next recruited patient based on accumulating toxicity data from patients already recruited into the trial, often using Bayesian methodology. Despite the original CRM design being proposed in'90, the methodology is still not widely implemented within oncology Phase I trials. The aim of this paper is to demonstrate, through example of the bcrm package, how a variety of possible designs can be easily implemented within the R statistical software, and how properties of the designs can be communicated to trial investigators using simple textual and graphical output obtained from the package. This in turn should facilitate an iterative process to allow a design to be chosen that is suitable to the needs of the investigator. Our bcrm package is the first to offer a large comprehensive choice of CRM designs, priors and escalation procedures, which can be easily compared and contrasted within the package through the assessment of operating characteristics.

Suggested Citation

  • Sweeting, Michael & Mander, Adrian & Sabin, Tony, 2013. "bcrm: Bayesian Continual Reassessment Method Designs for Phase I Dose-Finding Trials," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 54(i13).
    • Handle: RePEc:jss:jstsof:v:054:i13
    DOI: http://hdl.handle.net/10.18637/jss.v054.i13
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    References listed on IDEAS

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    1. Ying Kuen Cheung & Rick Chappell, 2002. "A Simple Technique to Evaluate Model Sensitivity in the Continual Reassessment Method," Biometrics, The International Biometric Society, vol. 58(3), pages 671-674, September.
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    Cited by:

    1. Nancy Flournoy & José Moler & Fernando Plo, 2020. "Performance Measures in Dose‐Finding Experiments," International Statistical Review, International Statistical Institute, vol. 88(3), pages 728-751, December.

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