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Master Protocol Design With Hybrid Control for Efficient Early-Phase Trial Consolidation
Alexander M Kaizer1, Xiaojiang Zhan2, Eric Baron2
1Department of Biostatistics & Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO.
Purpose:
Master protocols represent transformations, enabling multiple therapies or diseases under a single protocol. These designs streamline therapeutic development by reducing redundancies. Suited for evolving fields such as oncology and global emergencies such as the COVID-19 pandemic, master protocols have been exemplified by studies such as RECOVERY, Solidarity, and I-SPY 2, which accelerated effective treatment identification (with I-SPY 2 focused on molecular subtypes). Recent oncology examples, such as MORPHEUS, evaluate immunotherapy combinations with shared controls. Despite advantages, their application in early-phase oncology remains underutilized amid growing regulatory emphasis on randomization for robust evidence.
Methods:
US Food and Drug Administration (FDA) Oncology Center of Excellence (OCE) initiatives, such as Project Optimus and Project FrontRunner, emphasize randomization in early-phase oncology trials. However, these initiatives pose challenges, including larger sample sizes, patient and physician reluctance to randomization, and high failure rates from poor accrual. To address these, this article adapts master protocol designs to consolidate early-phase trials for novel therapeutics sharing a common backbone therapy, integrating hybrid controls from published standard-of-care data to minimize randomization to the control arm.
Results:
By consolidating trials under a shared standard-of-care control arm, the proposed master protocol design reduces total sample size by as much as 55% when compared with independent trials (with control arm sizes 2.4-2.9 times lower), lowers costs and duration, and enhances enrollment through reduced randomization to controls. Incorporating hybrid controls from prior studies and sharing information among arms with common background standard-of-care further improve efficiency, increasing power (reaching 90% overall) while controlling type I error rates acceptable levels.
Conclusion:
Master protocol designs with hybrid controls and Bayesian information sharing enable the efficient integration of randomization into early-phase oncology trials, enhancing efficiency, cost-effectiveness, and patient-centricity while aligning with FDA OCE initiatives.
Insights
Master protocols streamline early-phase oncology trials by integrating hybrid controls, reducing sample sizes by up to 55%. This approach enhances efficiency and patient-centricity, aligning with regulatory goals for robust evidence.
Area of Science:
- Oncology clinical trial design
- Biostatistics
- Regulatory science
Background:
- Master protocols offer efficient frameworks for evaluating multiple therapies or diseases within a single study.
- Their application in early-phase oncology is underutilized despite regulatory emphasis on randomization.
- Initiatives like FDA's Project Optimus highlight the need for robust, randomized early-phase trials.
Purpose of the Study:
- To adapt master protocol designs for early-phase oncology trials with a common backbone therapy.
- To integrate hybrid controls using existing standard-of-care data to minimize patient randomization to control arms.
- To address challenges posed by FDA initiatives, such as large sample sizes and patient reluctance to randomization.
Main Methods:
- Consolidation of early-phase trials under a shared standard-of-care control arm.
- Integration of hybrid controls derived from published standard-of-care data.
- Application of Bayesian information sharing among arms with a common background therapy.
Main Results:
- Reduction in total sample size by up to 55% compared to independent trials.
- Decrease in control arm size (2.4-2.9 times lower).
- Enhanced trial efficiency, reduced costs and duration, and improved enrollment rates.
- Increased statistical power (up to 90%) and controlled type I error rates through hybrid controls and information sharing.
Conclusions:
- Master protocols with hybrid controls and Bayesian information sharing facilitate efficient randomization in early-phase oncology trials.
- This design enhances cost-effectiveness and patient-centricity.
- The approach aligns with FDA Oncology Center of Excellence initiatives for robust clinical trial evidence.
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