Dose Finding Studies for Therapies with Late-Onset Toxicities: A Comparison Study of Designs

TL;DR

This study compares eight methods for phase I dose-finding trials that incorporate late-onset toxicities without significantly extending trial duration, highlighting the superior performance of model-based approaches like Interval Censored and Time-to-Event CRM.

Contribution

It introduces and evaluates methods that include late-onset toxicity data in dose-finding trials without prolonging the trial, providing practical recommendations.

Findings

Model-based approaches outperform model-assisted methods.

Interval Censored and Time-to-Event CRM are most effective.

Recommended methods balance accuracy and trial duration.

Abstract

An objective of phase I dose-finding trials is to find the maximum tolerated dose; the dose with a particular risk of toxicity. Frequently, this risk is assessed across the first cycle of therapy. However, in oncology, a course of treatment frequently consists of multiple cycles of therapy. In many cases, the overall risk of toxicity for a given treatment is not fully encapsulated by observations from the first cycle, and hence it is advantageous to include toxicity outcomes from later cycles in phase I trials. Extending the follow up period in a trial naturally extends the total length of the trial which is undesirable. We present a comparison of eight methods that incorporate late onset toxicities whilst not extensively extending the trial length. We conduct simulation studies over a number of scenarios and in two settings; the first setting with minimal stopping rules and the second setting with a full set of standard stopping rules expected in such a dose finding study. We find that the model-based approaches in general outperform the model-assisted approaches, with an Interval Censored approach and a modified version of the Time-to-Event Continual Reassessment Method giving the most promising overall performance in terms of correct selections and trial length. Further recommendations are made for the implementation of such methods.