A Hybrid Design Incorporating External Data to Evaluate Dexamethasone Intracameral Drug Delivery Suspension for Post-Cataract Surgery Inflammation.

Traditional randomized controlled trials (RCTs) face increasing challenges due to lengthy recruitment and high costs. Regulators have encouraged the use of external data and real-world evidence (RWE) to improve efficiency, yet adoption in confirmatory settings remains limited by concerns over heterogeneity and bias. We conducted a proof-of-concept study to assess the feasibility and regulatory value of a hybrid Bayesian borrowing design to support a Phase III RCT of Dexamethasone Intracameral Drug-Delivery Suspension (DEXYCU) in China. Using the Equivalence Probability Propensity Score Meta-Analytic-Predictive (EQPSMAP) approach, we integrated three data sources-a global RCT, a regional Phase III RCT in China, and a real-world data (RWD) in China. The method's performance was evaluated via point estimates and 95% credible intervals for the primary efficacy endpoint. The hybrid design based on EQPSMAP demonstrated greater robustness and accuracy in the presence of baseline imbalances and heterogeneous data. Compared to a traditional RCT, the hybrid design reduced the required sample size by 41 to 158 patients and shortened trial duration by approximately 2 to 5 months while preserving internal validity. This study demonstrated the feasibility and regulatory value of hybrid Bayesian designs in late-phase trials. The approach offers a practical, bias-controlled framework for integrating external data into regional drug development and regulatory decision making.

Duke Scholars

Author Shein-Chung Chow Biostatistics & Bioinformatics, Division of Biostatistics