Improving Safety of the Continual Reassessment Method via a Modified Allocation Rule

TL;DR

This paper introduces a new allocation criterion for Phase I dose-escalation trials that improves safety and ethics by accounting for uncertainty and reducing toxic responses without sacrificing accuracy.

Contribution

It proposes a novel criterion integrated into the Bayesian CRM, enhancing safety and ethical standards in dose-escalation designs while maintaining accuracy.

Findings

Fewer toxic responses with the new criterion.

Maintains same accuracy as traditional methods.

Improves ethical safety in dose escalation.

Abstract

This paper proposes a novel criterion for the allocation of patients in Phase~I dose-escalation clinical trials aiming to find the maximum tolerated dose (MTD). Conventionally, using a model-based approach the next patient is allocated to the dose with the toxicity estimate closest (in terms of the absolute or squared distance) to the maximum acceptable toxicity. This approach, however, ignores the uncertainty in point estimates and ethical concerns of assigning a lot of patients to overly toxic doses. Motivated by recent discussions in the theory of estimation in restricted parameter spaces, we propose a criterion which accounts for both of these issues. The criterion requires a specification of one additional parameter only which has a simple and intuitive interpretation. We incorporate the proposed criterion into the one-parameter Bayesian continual reassessment method (CRM) and show, using simulations, that it results in the same proportion of correct selections on average as the original design, but in fewer mean number of toxic responses. A comparison to other model-based dose-escalation designs demonstrates that the proposed design can result in either the same mean accuracy as alternatives but fewer number of toxic responses, or in a higher mean accuracy but the same number of toxic responses. We conclude that the new criterion makes the existing model-based designs more ethical without losing efficiency in the context of Phase I clinical trials.