Associations of Early Add-On GLP-1 Receptor Agonist and SGLT2 Inhibitor Therapy With Mortality and Kidney Outcomes in Adults With Obesity and Type 2 Diabetes Across Cardiovascular-Kidney-Metabolic Stages 2-3: A Target-Trial Emulation
Associations of Early Add-On GLP-1 Receptor Agonist and SGLT2 Inhibitor Therapy With Mortality and Kidney Outcomes in Adults With Obesity and Type 2 Diabetes Across Cardiovascular-Kidney-Metabolic Stages 2-3: A Target-Trial Emulation
This retrospective observational target-trial emulation uses electronic health record data from the TriNetX US Collaborative Network to compare early treatment intensification strategies in adults with obesity, type 2 diabetes, and cardiovascular-kidney-metabolic stage 2-3 who initiate a GLP-1 receptor agonist or an SGLT2 inhibitor. The study compares patients who, within 90 days of starting background therapy, add the alternate agent, add a DPP-4 inhibitor or sulfonylurea, or do not receive early add-on therapy. The primary outcome is all-cause mortality over 36 months, with secondary cardiorenal outcomes also evaluated. Propensity-score methods are used to reduce bias from nonrandom treatment selection.
This study is a retrospective observational target-trial emulation using electronic health record data from the TriNetX US Collaborative Network. It evaluates early treatment intensification strategies after initiation of a GLP-1 receptor agonist or an SGLT2 inhibitor in adults with obesity, type 2 diabetes, and cardiovascular-kidney-metabolic stage 2-3.
Patients are grouped according to treatment changes made within 90 days after treatment initiation, including addition of the alternate drug class, addition of a DPP-4 inhibitor or sulfonylurea, or no early add-on treatment. Follow-up is aligned across comparison groups after this initial treatment assessment period.
The study uses routinely collected clinical data to assess the comparative effectiveness of these strategies on mortality and cardiorenal outcomes in real-world practice. Propensity-score-based methods are used to reduce confounding associated with nonrandom treatment selection.
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