Stratifying cardiovascular benefits from GLP-1RA: a multisource analysis of patient-level CVOT and real-world data using AI-driven methods.

ABSTRACT:

Background

It remains unclear whether certain individuals with type 2 diabetes (T2D) derive greater cardiovascular benefit from GLP-1 receptor agonists (GLP-1RAs). Here, we integrate individual-level data from cardiovascular outcome trials (CVOTs) and electronic health records (EHRs), applying machine learning methods to confirm the cardiovascular benefits of GLP-1RAs in real-world populations and to identify subgroups with enhanced treatment response.

Methods

Data from two CVOTs (LEADER and SUSTAIN-6) and a large real-world study (DARWIN-T2D) were analyzed. We first transposed the hazard ratio (HR) for 3-point major adverse cardiovascular event (3P-MACE) from CVOTs to the real-world population. Then, we used PRISM (Patient Response Identifiers for Stratified Medicine) again

SUBMITTER: Morieri ML 

PROVIDER: S-EPMC12535053 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature