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Bayesian Optimal Designs for Multi-Arm Multi-Stage Phase II Randomized Clinical Trials with Multiple Endpoints
Guillaume Mulier1, Sylvie Chevret1, Ruitao Lin2
1INSERM U1153, Epidemiology and Clinical Statistics for Tumor, Respiratory, and Resuscitation Assessments (ECSTRRA) Team, Paris, France.
Abstract:
There is a growing need to evaluate of multiple competing drugs in phase II trials where the number of patients is often limited, and simultaneous assessment of both efficacy and toxicity is crucial. To avoid the waste of research resources, it is indeed more efficient to screen multiple drugs at once in a platform phase II setting. We aim to adapt the Bayesian optimal phase II (BOP2) design to multi-arm trials for both uncontrolled and controlled settings. The binary efficacy and toxicity endpoints are modeled by a Dirichlet distribution as a vector of four outcomes. Posterior marginal distributions at each analysis are used to derive the monitoring threshold that varies during the trial. We control the family-wise Type I error rate for multiple comparison against a common reference value or a shared control. We conduct simulation studies under both uncontrolled and controlled settings to evaluate the operating characteristics of the proposed design. Our simulations demonstrate that the design exhibits better operating characteristics compared to a design using a constant threshold and is less sensitive to changes in accrual rate relative to what was planned. The design had promising operating characteristics and could be used in phase II oncology clinical trials for evaluating multiple drugs at a time.
Insights
This study adapts the Bayesian optimal phase II (BOP2) design for multi-arm trials, efficiently evaluating multiple drugs simultaneously. The new design shows improved performance in both controlled and uncontrolled settings for phase II oncology trials.
Area of Science:
- Clinical Trials Methodology
- Biostatistics
- Pharmacological Research
Background:
- Phase II clinical trials often face limited patient numbers, necessitating efficient evaluation of multiple drugs.
- Simultaneous assessment of drug efficacy and toxicity is critical to avoid research waste.
- Platform phase II trials offer a more efficient approach to screen multiple candidate drugs concurrently.
Purpose of the Study:
- To adapt the Bayesian optimal phase II (BOP2) design for multi-arm clinical trials.
- To enable simultaneous evaluation of multiple drugs in both uncontrolled and controlled phase II settings.
- To develop a flexible monitoring threshold for adaptive trial designs.
Main Methods:
- The study adapted the BOP2 design for multi-arm trials using a Dirichlet distribution to model binary efficacy and toxicity endpoints.
- Posterior marginal distributions informed a dynamic, varying monitoring threshold throughout the trial.
- Family-wise Type I error rate was controlled for multiple comparisons against a common reference or shared control.
Main Results:
- Simulations demonstrated superior operating characteristics compared to designs with constant thresholds.
- The proposed adaptive design showed reduced sensitivity to variations in patient accrual rates.
- The BOP2 adaptation proved effective in both uncontrolled and controlled trial settings.
Conclusions:
- The adapted BOP2 design offers a promising approach for phase II oncology trials evaluating multiple drugs.
- This adaptive design enhances efficiency and statistical rigor in resource-limited trial settings.
- The flexible thresholding strategy improves trial robustness and reliability.
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