A Phase I Bayesian Adaptive Design to Simultaneously Optimize Dose and Schedule Assignments Both Between and Within Patients.
In traditional schedule or dose-schedule finding designs, patients are assumed to receive their assigned dose-schedule combination throughout the trial even though the combination may be found to have an undesirable toxicity profile, which contradicts actual clinical practice. Since no systematic approach exists to optimize intra-patient dose-schedule assignment, we propose a Phase I clinical trial design that extends existing approaches to optimize dose and schedule solely between patients by incorporating adaptive variations to dose-schedule assignments within patients as the study proceeds. Our design is based on a Bayesian non-mixture cure rate model that incorporates multiple administrations each patient receives with the per-administration dose included as a covariate. Simulations demonstrate that our design identifies safe dose and schedule combinations as well as the traditional method that does not allow for intra-patient dose-schedule reassignments, but with a larger number of patients assigned to safe combinations. Supplementary materials for this article are available online.
Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, 48109.
Jin
J
Zhang
Thomas M
TM
Braun
Bayesian statistics; Clinical trial; Dose-escalation study; Dynamic treatment regime; Non-mixture cure model