Abstract
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 as- signment, we propose a Phase I clinical trial design that extends existing approaches that optimize dose and schedule solely among 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.
Disciplines
Biostatistics
Suggested Citation
Braun, Thomas M. and Zhang, Jin, "A Phase I Bayesian Adaptive Design to Simultaneously Optimize Dose and Schedule Assignments Both Among and Within Patients" (August 2012). The University of Michigan Department of Biostatistics Working Paper Series. Working Paper 93.
https://biostats.bepress.com/umichbiostat/paper93