Volume 16 Supplement 2

3rd International Clinical Trials Methodology Conference

Open Access

A pragmatic approach to the design and calibration of a Bayesian CRM dose finding trial

  • Michael Cole1,
  • Deborah Stocken1 and
  • Christina Yap2
Trials201516(Suppl 2):P210

https://doi.org/10.1186/1745-6215-16-S2-P210

Published: 16 November 2015

The Continual Reassessment Method (CRM) is not widely used in early phase dose finding trials partly because the logistics of development and implementation are perceived as complex and time consuming. Details are presented of the steps involved when designing such a trial using an adaptation of a Bayesian CRM calibration algorithm proposed by Cheung [1].

In addition to clinician centred parameters including target toxicity probability and number of test doses, the Bayesian CRM requires specification of the prior probability of toxicity associated with each of the test doses and the prior SD of the single model parameter. Cheung’s simple pragmatic approach is used to aid selection of these parameters.

Competing designs are assessed in terms of risk-adjusted accuracy and trial specific requirements including the mean number of patients treated above the maximum tolerated dose. Performance measures are estimated by Monte Carlo simulation across a range of scenarios chosen solely upon the target toxicity level and the number of test doses.

We demonstrate that following this pragmatic approach to CRM design calibration, design of CRM trials need not be overly complex or time-consuming.

Authors’ Affiliations

(1)
Newcastle University
(2)
University of Birmingham

References

  1. Cheung YK: Dose Finding by the Continual Reassessment Method. 2011, New York: Chapman & Hall/CRC PressView ArticleGoogle Scholar

Copyright

© Cole et al. 2015

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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