A randomized Bayesian phase I-II dose optimization design for combination cancer therapies with progression-free
Yingjie Qiu1,2, Mingyue Li3
1Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390, USA. yingjie.qiu@utsouthwestern.edu.
Background:
Combination therapies involving novel agents, such as immunotherapies and targeted therapies, offer significant antitumor benefits by increasing dose intensity, targeting multiple pathways, and benefiting a broader patient population. To further explore these advantages, the National Cancer Institute (NCI) has initiated Combination Therapy Platform Trial with Molecular Analysis for Therapy Choice (ComboMATCH) to evaluate the effectiveness of new drug combinations in treating both adults and children. However, designing dose optimization trials for these combination therapies presents substantial challenges due to the complex interactions and unique mechanisms of action.
Methods:
To address these challenges, we propose COMPACT, a Bayesian phase I-II randomized design for combination cancer therapies that uses progression-free survival (PFS) as the primary efficacy endpoint to identify the optimal dose combination (ODC) based on restricted mean survival time (RMST). The COMPACT design jointly evaluates both toxicity and PFS, with continuous toxicity monitoring throughout the trial. Toxicity probabilities are modeled using a partial ordering assumption without relying on complex parametric models, while PFS is modeled through a Bayesian Pareto proportional hazards model with gamma-shared frailty. The trial consists of two seamlessly connected stages. In the first stage, the dose space is explored primarily based on toxicity, while PFS data are concurrently collected. In the second stage, patients are adaptively randomized to safe and potentially promising dose combinations based on PFS, and the dose combination with the highest RMST among those deemed safe is selected as the ODC.
Results:
Simulation studies demonstrate that COMPACT has desirable operating characteristics and outperforms conventional designs in identifying the ODC, allocating more patients to ODC, while maintaining patient safety. Sensitivity analysis is performed to examine the robustness of the proposed design. A trial example is provided to facilitate the practical implementation of the proposed COMPACT design.
Conclusions:
The proposed COMPACT design offers a novel and robust framework for combination cancer therapies with progression-free survival end point.
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