Identifying Predictors of Early Treatment Intensification in Individuals With Type 2 Diabetes Treated With GLP ‐1 Receptor Agonists: A Machine Learning–Based Analysis of a Large Real World Cohort

Key Points

• This research aims to identify factors that predict early treatment intensification in individuals with Type 2 diabetes treated with GLP-1 receptor agonists.
• Utilized explainable AI approaches for analysis
• Focus on a large real-world cohort of individuals with Type 2 diabetes
• Developed machine learning models to identify patient phenotypes
• Identified distinct patient phenotypes associated with early treatment intensification
• Models demonstrated reproducibility in predicting treatment adjustments
• Findings suggest potential for more personalized treatment decisions in diabetes care