Targeted-Agent Continual Reassessment Method: A Novel Bayesian Enrichment Design for Phase I Trials of Molecularly Targeted Therapies.

Abstract

Purpose: Novel therapies targeting specific genomic alterations are a promising treatment approach for relapsed/refractory cancer. Patients with specific alterations may be more likely to respond. Trial designs should maximize opportunities for such patients to enroll on these trials. Existing designs do not enrich for patients with specific alterations. We developed the adaptive Targeted Agent-Continual Reassessment Method (TARGET-CRM) to optimize dose finding and enrich for patients with specific alterations, and applied it in a pediatric phase I trial.

Methods: Patients were stratified to cohort A (unspecified tumors) or cohort B (rare genomic alterations). The TARGET-CRM design permits cohort B patients to immediately enroll at one dose level below the currently evaluated dose level instead of waiting for an open slot at the current dose level. Using simulations, we compared the operating characteristics (accuracy-the proportion of trials in which the true maximum tolerated dose [MTD] was identified/recommended; safety-the dose-limiting toxicity [DLT] rate; the proportion of cohort B patients enrolled) of the TARGET-CRM, standard CRM, and 3 + 3 designs across various scenarios.

Results: The proportion of enrolled patients who were cohort B was higher for TARGET-CRM (90%-100%) compared with CRM (approximately 85%) and 3 + 3 (approximately 79%). The DLT rate and rate the true MTD was recommended were similar for TARGET-CRM and CRM, differing by only 0%-4% and 0%-4%, respectively. Results were similar regardless of trial sample size and proportion of cohort B patients in the population.

Conclusion: In phase I dose-finding trials of targeted agents, the Bayesian adaptive TARGET-CRM design maximizes enrollment of patients hypothesized as most likely to benefit from the targeted agent, while maintaining similar or superior accuracy and safety as the CRM and 3 + 3 designs.