Aims: To evaluate the real-world effectiveness of combination therapy with glucagon-like peptide-1 receptor agonists (GLP-1RAs) and sodium-glucose co-transporter 2 inhibitors (SGLT2-I) on glucose control in type 2 diabetes (T2D) and to identify clinical predictors of treatment response. Methods: We retrospectively analyzed data from 549 subjects with T2D treated with combined GLP-1RA and SGLT2-I therapy. Clinical and biochemical parameters were collected at baseline and after 6-9 months of follow-up. Therapy response was defined according to drug-specific expected glycated hemoglobin (HbA1C) reduction thresholds, based on the known efficacy of each innovative molecule. Logistic regression and receiver operating characteristic analyses were used to identify predictors of response. Decision curve analysis was performed to assess the utility of predictive models. Results: 41.9% of subjects achieved the expected HbA1C reduction. Baseline HbA1C was the strongest predictor of response (odds ratio: 6.60 per 1% [≈11 mmol/mol] increase). Follow-up reductions in fasting plasma glucose and body mass index, and increases in high-density lipoprotein cholesterol, were also associated with response. Decision curve analysis demonstrated that both baseline and extended models provided higher net benefit than treat-all and treat-none strategies. Conclusions: Combination therapy with GLP-1RA and SGLT2-I improves glucose control in a substantial proportion of subjects with T2D. Integrating baseline glycaemic burden with longitudinal metabolic changes may support individualized clinical decision-making.

Effectiveness of GLP-1 Receptor Agonists and SGLT-2 Inhibitors Combination Therapy in Type 2 Diabetes: A Real-World Experience

Di Giacomo Barbagallo, Francesco;
2026-01-01

Abstract

Aims: To evaluate the real-world effectiveness of combination therapy with glucagon-like peptide-1 receptor agonists (GLP-1RAs) and sodium-glucose co-transporter 2 inhibitors (SGLT2-I) on glucose control in type 2 diabetes (T2D) and to identify clinical predictors of treatment response. Methods: We retrospectively analyzed data from 549 subjects with T2D treated with combined GLP-1RA and SGLT2-I therapy. Clinical and biochemical parameters were collected at baseline and after 6-9 months of follow-up. Therapy response was defined according to drug-specific expected glycated hemoglobin (HbA1C) reduction thresholds, based on the known efficacy of each innovative molecule. Logistic regression and receiver operating characteristic analyses were used to identify predictors of response. Decision curve analysis was performed to assess the utility of predictive models. Results: 41.9% of subjects achieved the expected HbA1C reduction. Baseline HbA1C was the strongest predictor of response (odds ratio: 6.60 per 1% [≈11 mmol/mol] increase). Follow-up reductions in fasting plasma glucose and body mass index, and increases in high-density lipoprotein cholesterol, were also associated with response. Decision curve analysis demonstrated that both baseline and extended models provided higher net benefit than treat-all and treat-none strategies. Conclusions: Combination therapy with GLP-1RA and SGLT2-I improves glucose control in a substantial proportion of subjects with T2D. Integrating baseline glycaemic burden with longitudinal metabolic changes may support individualized clinical decision-making.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11387/214613
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