Head-to-head Comparison Using Data Integration of Summary Data via Generalized Entropy Balancing

Music City Center 

In pharmaceutical development, comparisons with existing treatments are important from both clinical practice and cost-effectiveness perspective. Although head-to-head trials can sometimes be conducted for direct comparisons, time and budget constraints often limit their feasibility. When no head-to-head trial exists, indirect comparison methods using published studies are commonly employed. Despite their practicality, these methods aim at published studies as a target population, but this is sometimes questionable.
In this presentation, we propose a trial design and method to address this limitation even when only summary-level data are available. Specifically, a small active-control arm is included within the confirmatory trial whose primary objective is to compare an investigational drug with placebo. We propose a data integration method that employs a generalized entropy balancing approach to efficiently combine data from the trial with external summary-level data. This method not only enhances efficiency but also ensures double robustness, providing reliable and comprehensive results. We will present both the theoretical properties of our method and the simulation results.

Indirect comparison

Summary-level data

Data integration

Generalized entropy balancing 

Biopharmaceutical Section