Sample size formulae for the Bayesian continual reassessment method

Bayesian Model Averaging Continual Reassessment Method BMA-CRM

This document provides the statistical background for the Bayesian model averaging continual reassessment method (BMA-CRM). The BMA-CRM is a Bayesian model-based phase I clinical trial design. The primary goal of the BMA-CRM is to identify the maximum tolerated dose (MTD) of a new drug, which is typically defined as the dose with a doselimiting toxicity (DLT) probability that is closest to the ...

The flexible bivariate continual reassessment method

Continual reassessment method with multiple toxicity constraints.

This paper addresses the dose-finding problem in cancer trials in which we are concerned with the gradation of severe toxicities that are considered dose limiting. In order to differentiate the tolerance for different toxicity types and grades, we propose a novel extension of the continual reassessment method that explicitly accounts for multiple toxicity constraints. We apply the proposed meth...

The continual reassessment method and its applications: a Bayesian methodology for phase I cancer clinical trials.

We discuss the continual reassessment method (CRM) and its extension with practical applications in phase I and I/II cancer clinical trials. The CRM has been proposed as an alternative design of a traditional cohort design and its essential features are the sequential (continual) selection of a dose level for the next patients based on the dose-toxicity relationship and the updating of the rela...

The Continual Reassessment Method for Multiple Toxicity Grades: A Bayesian Model Selection Approach

Grade information has been considered in Yuan et al. (2007) wherein they proposed a Quasi-CRM method to incorporate the grade toxicity information in phase I trials. A potential problem with the Quasi-CRM model is that the choice of skeleton may dramatically vary the performance of the CRM model, which results in similar consequences for the Quasi-CRM model. In this paper, we propose a new mode...