CRM2DIM: A SAS macro for implementing the dual-agent Bayesian continual reassessment method

Comput Methods Programs Biomed. 2019 Jul:176:211-223. doi: 10.1016/j.cmpb.2019.04.025. Epub 2019 May 6.

Abstract

Background and objective: The continual reassessment method (CRM) is a model-based dose-finding design for single-agent phase I oncology trials. With the advance of targeted therapies in oncology, more and more phase I trials investigate drug combinations rather than a single agent in order to find one or more maximum tolerated dose combinations. Several designs have been proposed for such dose-finding trials but only a few software packages are available to implement them. One of the designs is the two-dimensional Bayesian CRM proposed by Wang and Ivanova. Our goal was to provide an easy-to-use program to implement this design.

Methods: We developed a new SAS macro, CRM2DIM, for implementing this design. This macro can be used to run a phase I dose-finding trial for two-drug combination and to perform simulations.

Results: We describe the program with its different features, including the possibility of running an initial design (start-up rule), the possibility of incorporating historical data, and the choice of using either a power or a logistic regression model with or without interaction term. We illustrate our program by presenting simulation results and by a hypothetical trial example.

Conclusions: The CRM2DIM macro provides a SAS implementation of the two-dimensional Bayesian CRM for dual-agent phase I oncology trials. It is an easy-to-use program that includes many useful features and provides statisticians involved in the early phases of development a new tool for designing dual-agent phase I oncology trials.

Keywords: CRM; Continual reassessment method; Dose-finding; Drug combinations; Phase I clinical trial; SAS MCMC procedure.

MeSH terms

  • Algorithms
  • Bayes Theorem*
  • Clinical Trials, Phase I as Topic
  • Dose-Response Relationship, Drug
  • Drug Administration Schedule
  • Humans
  • Logistic Models
  • Longitudinal Studies
  • Maximum Tolerated Dose*
  • Medical Oncology
  • Neoplasms / drug therapy*
  • Programming Languages
  • Research Design*
  • Software