What question did this study set out to answer?

To evaluate the efficacy of a personalized treatment algorithm in guiding therapy choice between GLP-1 receptor agonists and SGLT2 inhibitors for individuals with type 2 diabetes.

March 27, 2026Open Access

GLP-1 receptor agonists or SGLT2-inhibitors? Evaluation of a personalized treatment algorithm for individuals with type 2 diabetes: a registry-based cohort study

Key Points

To evaluate the efficacy of a personalized treatment algorithm in guiding therapy choice between GLP-1 receptor agonists and SGLT2 inhibitors for individuals with type 2 diabetes.
Utilized data from the Diabetes Prospective Follow-up registry in Germany/Austria.
Analyzed individuals with type 2 diabetes initiating either GLP-1 receptor agonists or SGLT2 inhibitors.
Used dynamic weighted survival modeling to predict non-fatal atherosclerotic cardiovascular disease events.
Compared baseline characteristics such as BMI, eGFR, and history of ASCVD across treatment groups.
The algorithm predicted optimal treatment with GLP-1 RA for 48% and SGLT2i for 52% of individuals.
GLP-1 RA-optimal individuals had a higher average BMI and lower eGFR compared to SGLT2i-optimal individuals.
No statistically significant prolongation of time to non-fatal ASCVD events was observed between optimal and suboptimal treatments.

Abstract

Abstract Guidelines recommend GLP-1 receptor agonists (GLP-1-RA) and SGLT2-inhibitors (SGLT2i) for individuals with type 2 diabetes (T2D) at high risk of atherosclerotic cardiovascular disease (ASCVD). In the context of precision medicine, we evaluated a personalized treatment algorithm to guide the initial decision between these therapies. Using data from the observational Diabetes Prospective Follow-up registry (Germany/Austria) we studied individuals with T2D who initiated GLP-1-RA (n=1433) or SGLT2i (n=2547) in a multicenter, real-world setting. Baseline characteristics included age, sex, body mass index (BMI), estimated glomerular filtration rate (eGFR), HbA1c, diabetes duration, and history of ASCVD. Non-fatal ASCVD events (myocardial infarction, angina, revascularization, stroke, transient ischemic attack, and peripheral artery disease) were analyzed using dynamic weighted survival modeling to predict the optimal treatment for each individual. The algorithm predicted 48% of individuals to have better ASCVD outcomes with GLP-1-RA and 52% with SGLT2i. GLP-1-RA-optimal individuals had on average a higher BMI (37 vs 31 kg/m2), lower eGFR (71 vs 93 ml/min per 1.73 m2) and less history of ASCVD (9 vs 18%) compared to SGLT2i-optimal individuals. However, an internal model validation showed that the predicted optimal treatment did not statistically significantly prolong the average time to a non-fatal ASCVD event compared to the suboptimal treatment (AFT parameter: 1.13; 95% CI: 0.83-1.56; HR: 0.88; 95% CI: 0.64-1.21). The personalized treatment algorithm for GLP-1-RA and SGLT2i did not result in clear individual ASCVD benefits on either drug, a finding consistent with the clinical equipoise reflected in current T2D treatment guidelines.

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