Abstract: TH-OR077
Cardiovascular Risk Prediction Modelling with Sotagliflozin in Type 1 Diabetes: Analysis of inTandem 1-3 Trials
Session Information
- Precision Medicine in Diabetic Kidney Disease: Biomarkers, Combination Therapies, and Treatment Response Prediction
November 06, 2025 | Location: Room 372A, Convention Center
Abstract Time: 05:10 PM - 05:20 PM
Category: Diabetic Kidney Disease
- 702 Diabetic Kidney Disease: Clinical
Authors
- Sridhar, Vikas, The University of British Columbia Faculty of Medicine, Vancouver, British Columbia, Canada
- Kugathasan, Luxcia, University of Toronto Temerty Faculty of Medicine, Toronto, Ontario, Canada
- Nardone, Massimo, University Health Network, Toronto, Ontario, Canada
- Davies, Michael J., Lexicon Pharmaceuticals Inc, The Woodlands, Texas, United States
- Girard, Manon, Lexicon Pharmaceuticals Inc, The Woodlands, Texas, United States
- Cherney, David, University of Toronto Temerty Faculty of Medicine, Toronto, Ontario, Canada
Background
Sodium-glucose cotransporter (SGLT) inhibitors reduce cardiovascular risk in people with type 2 diabetes. It is unknown if this extends to individuals with type 1 diabetes (T1D). To understand the potential benefits of SGLT inhibition in T1D, we applied the Scottish Diabetes Research Network (SDRN) risk prediction models to estimate cardiovascular disease (CVD) risk in people with T1D treated with sotagliflozin, a dual SGLT1&2 inhibitor.
Methods
In a patient-level analysis, medical history, demographic and biochemical data were extracted from 2829 participants with T1D pooled from the inTandem1-3 trials. The SDRN risk prediction model was employed at baseline and week 24 to estimate the 10-year CVD. Risk reduction was calculated as the percent and absolute change in estimated CVD risk from baseline and compared between sotagliflozin (pooled 200 and 400mg) and placebo groups using a two-way repeated measures ANOVA. The log-transformed change in relative (absolute) risk from baseline was the dependent variable, treatment and visit as fixed effect, and log-transformed baseline value as covariate. Subgroup analyses were based on baseline CVD risk (<10%, 10 to 20%, ≥20%) and baseline chronic kidney disease (CKD) risk defined by KDIGO.
Results
Baseline SDRN risk score was approximately 11%. Sotagliflozin significantly reduced the estimated 10-year CVD risk following 24 weeks of treatment compared with placebo. Placebo adjusted relative change from baseline was -7.0% (95% CI -8.4, -5.5; p<0.0001). Placebo adjusted absolute change from baseline was -0.9% (95% CI -1.2, -0.7; p<0.0001). Results were consistent across subgroups based on baseline CVD and CKD risk, with evidence of greater risk reduction in those at higher CVD and CKD risk.
Conclusion
Sotagliflozin improves predicted CVD risk in T1D participants at low cardiorenal risk. By highlighting the predicted cardiovascular risk benefit in a large low-risk T1D cohort, our findings underline the need to investigate the effect of SGLT inhibitors on hard cardiovascular endpoints in T1D, especially in high-risk cohorts.
Funding
- Commercial Support – Lexicon pharmaceuticals