Faculty Collaboration Database

Impacts of Eligibility Criteria on Trial Participants' Age in Alzheimer's Disease Clinical Trials. AMIA Annu Symp Proc 2022;2022:368-376

Date

05/02/2023

Pubmed ID

37128470

Pubmed Central ID

PMC10148327

Abstract

Overly restricted and poorly designed eligibility criteria reduce the generalizability of the results from clinical trials. We conducted a study to identify and quantify the impacts of study traits extracted from eligibility criteria on the age of study populations in Alzheimer's Disease (AD) clinical trials. Using machine learning methods and SHapley Additive exPlanation (SHAP) values, we identified 30 and 34 study traits that excluded older patients from AD trials in our 2 generated target populations respectively. We also found that study traits had different magnitudes of impacts on the age distributions of the generated study populations across racial-ethnic groups. To our best knowledge, this was the first study that quantified the impact of eligibility criteria on the age of AD trial participants. Our research is a first step in addressing the overly restrictive eligibility criteria in AD clinical trials.

Author List

Chen A, Li Q, He X, Jaffee MS, Hogan WR, Wang F, Guo Y, Bian J

Author

William R. Hogan MD Director, Professor in the Data Science Institute department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Alzheimer Disease
Eligibility Determination
Humans
Machine Learning