GLP-1 receptor agonists or SGLT2-inhibitors? Evaluation of a personalized treatment algorithm for individuals with...

Area of Science:

• Endocrinology
• Cardiology
• Pharmacology

Background:

• Current guidelines recommend GLP-1 receptor agonists (GLP-1-RA) and SGLT2 inhibitors (SGLT2i) for type 2 diabetes (T2D) patients at high risk of atherosclerotic cardiovascular disease (ASCVD).
• Precision medicine approaches are being explored to personalize treatment decisions between these drug classes.

Purpose of the Study:

• To evaluate a personalized treatment algorithm for guiding initial therapy selection between GLP-1-RA and SGLT2i in T2D patients at high ASCVD risk.
• To assess whether the algorithm could predict differential ASCVD outcomes based on individual patient characteristics.

Main Methods:

• Utilized data from the observational Diabetes Prospective Follow-up registry (Germany/Austria) including 1433 GLP-1-RA initiators and 2547 SGLT2i initiators with T2D.
• Employed dynamic weighted survival modeling to analyze non-fatal ASCVD events and predict optimal treatment assignment.
• Internal model validation was performed to assess the clinical utility of the predicted optimal treatment.

Main Results:

• The algorithm predicted 48% of individuals would benefit more from GLP-1-RA and 52% from SGLT2i.
• Patients predicted to benefit from GLP-1-RA had higher BMI, lower eGFR, and less ASCVD history compared to those predicted for SGLT2i.
• Internal validation showed no statistically significant difference in time to non-fatal ASCVD events between predicted optimal and suboptimal treatments (HR: 0.88; 95% CI: 0.64-1.21).

Conclusions:

• The evaluated personalized treatment algorithm did not demonstrate clear individual benefits for GLP-1-RA or SGLT2i in preventing ASCVD events in T2D patients.
• The findings support the concept of clinical equipoise between these drug classes for ASCVD risk reduction in T2D, as reflected in current treatment guidelines.