Evaluating eligibility criteria of oncology trials using real-world data and AI.

ABSTRACT: There is a growing focus on making clinical trials more inclusive but the design of trial eligibility criteria remains challenging^1-3. Here we systematically evaluate the effect of different eligibility criteria on cancer trial populations and outcomes with real-world data using the computational framework of Trial Pathfinder. We apply Trial Pathfinder to emulate completed trials of advanced non-small-cell lung cancer using data from a nationwide database of electronic health records comprising 61,094 patients with advanced non-small-cell lung cancer. Our analyses reveal that many common criteria, including exclusions based on several laboratory values, had a minimal effect on the trial hazard ratios. When we used a data-driven approach to broaden restrictive criteria, the pool

SUBMITTER: Liu R 

PROVIDER: S-EPMC9007176 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature