A Matching Design for Augmenting a Randomized Clinical Trial with External Control

• Activity Number: 145 - Leveraging External Data in Clinical Trials
• Type: Contributed
• Date/Time: Monday, August 8, 2022 : 10:30 AM to 12:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Jianghao Li* and Yu Du and Yanyao Yi and Huayu Liu
• Companies: Eli Lilly and Company and Eli Lilly and Company and Eli Lilly and Company and Eli Lilly and Company
• Keywords: external control; matching without replacement; propensity score; real-world data

Abstract

The use of information from real world to assess the effectiveness of medicines is becoming increasingly popular and more acceptable by regulatory agencies. According to a strategic real-world evidence framework published by U.S. Food and Drug Administration, a hybrid randomized controlled trial that augments the internal control arm with real-world data is a pragmatic approach that worth more attention. In this paper, we aim to improve the existing matching methods on designing such a hybrid randomized controlled trial. In particular, we propose to match the entire population from the concurrent randomized clinical trial (RCT) such that (1) the matched external control subjects used to augment the internal control arm are as comparable as possible to the RCT population, (2) every active treatment arm in an RCT with multiple treatments is compared with the same control group, and (3) matching can be conducted and locked before treatment unblinding to better maintain data integrity. Besides a weighted estimator, we also introduce a bootstrap method to obtain the variance estimation for our proposed method. The finite sample performance is evaluated by real data based simulations.