Predicting responsiveness to GLP-1 pathway drugs using real-world data.

ABSTRACT:

Background

Medications targeting the glucagon-like peptide-1 (GLP-1) pathway are an important therapeutic class currently used for the treatment of Type 2 diabetes (T2D). However, there is not enough known about which subgroups of patients would receive the most benefit from these medications.

Objective

The goal of this study was to develop a predictive model for patient responsiveness to medications, here collectively called GLP-1 M, that include GLP-1 receptor agonists and dipeptidyl peptidase-4 (DPP4) inhibitors (that normally degrade endogenously-produced GLP-1). Such a model could guide clinicians to consider certain patient characteristics when prescribing second line medications for T2D.

Methods

We analyzed de-identified electronic health records of 7856 subjec

SUBMITTER: Zhu X 

PROVIDER: S-EPMC11654408 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature