Characterize Disease Progression Subphenotypes in Real World Populations with Overweight and Obesity using a Graph-based Neural Network Framework.

ABSTRACT:

Background

Obesity is a chronic, heterogeneous condition, with risks, trajectories, and treatment responses that vary widely among individuals. However, research characterizing the heterogeneity of long-term obesity progression-and its impact on the development of obesity-associated outcomes and treatment responses-is scarce.

Objectives

We aimed to identify progression subphenotypes in a real-world population with overweight or obesity over a period of up to 10 years using electronic health records (EHRs) and evaluate the heterogeneity of treatment effects (HTE) of glucagon-like peptide-1 receptor agonists (GLP-1RAs) across these subphenotypes for major obesity-related disease outcomes.

Methods

We conducted a retrospective cohort study of adults from OneFlorida+ who w

SUBMITTER: Lee YA 

PROVIDER: S-EPMC12642739 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature