The Randomized CRM: An Approach to Overcoming the Long-Memory Property of the CRM

摘要

The primary object of a phase I clinical trial is to determine the maximum tolerated dose (MTD). Typically, the MTD is identified using a dose-escalation study, where initial subjects are treated at the lowest dose level and subsequent subjects are treated at progressively higher dose levels until the MTD is identified. The continual reassessment method (CRM) is a popular model-based dose-escalation design, which utilizes a formal model for the relationship between dose and toxicity to guide dose-finding. Recently, it was shown that the CRM has a tendency to get “stuck” on a dose-level, with little escalation or de-escalation in the late stages of the trial, due to the long-memory property of the CRM. We propose the randomized CRM (rCRM), which introduces random escalation and de-escalation into the standard CRM dose-finding algorithm, as well as a hybrid approach that incorporates escalation and de-escalation only when certain criteria are met. Our simulation results show that both the rCRM and the hybrid approach reduce the trial-to-trial variability in the number of cohorts treated at the MTD but that the hybrid approach has a more favorable trade-off with respect to the average number treated at the MTD.