CONGRESS ABSTRACT

Background Objective: deliver a 12-month, harmonized comparison of Semaglutide and Tirzepatide across three shared clinical domains: weight reduction, glycemic improvement, and cardiovascular risk reduction. Because individual patient data from original trials are not available, a synthetic cohort and propensity-score matching framework were used to approximate balanced treatment groups. Methods A simulated cohort (N=8000) was built using clinical variables aligned with SELECT (Semaglutide) and SUMMIT (Tirzepatide) populations: age, sex, BMI, type 2 diabetes status, cardiovascular disease history, HFpEF, eGFR, and systolic blood pressure. Treatment assignment followed a logistic model reflecting real-world prescribing patterns. Twelve-month cardiovascular events were generated using clinical predictors and a predefined treatment effect. Propensity scores were estimated via logistic regression and matched 1:1 using a caliper of 0.05. Standardized mean differences assessed balance. Outcomes included 12-month indexed reductions in weight, HbA1c, and composite cardiovascular risk. Results Matching produced acceptable balance (post-match SMD <0.1 for all covariates). In the matched cohorts, 12-month indexed outcomes showed: – Weight reduction: Semaglutide 10%, Tirzepatide 15% – HbA1c reduction: Semaglutide −1.6%, Tirzepatide −2.2% – Cardiovascular risk reduction (composite events): Semaglutide 16.8%, Tirzepatide 12.5% The simulation replicated expected patterns: stronger metabolic effects with Tirzepatide, more pronounced cardiovascular protection with Semaglutide. Conclusions A synthetic propensity-matched approach enables a unified 12-month comparison between the two agents, overcoming structural differences in the original trials. Results mirror broader clinical evidence: Tirzepatide delivers higher metabolic impact, while Semaglutide demonstrates stronger cardiovascular risk attenuation. The model is illustrative and not a substitute for analyses based on true patient-level data.