Cardiovascular and Renal Benefits of Novel Diabetes Drugs by Baseline Cardiovascular Risk: A Systematic Review, Meta-analysis, and Meta-regression

Abstract

BACKGROUND Eligibility for glucagon-like peptide 1 receptor agonists (GLP-1RA) and sodium–glucose cotransporter 2 inhibitors (SGLT2i) has been expanded to patients with diabetes at lower cardiovascular risk, but whether treatment benefits differ by risk levels is not clear. PURPOSE To investigate whether patients with varying risks differ in cardiovascular and renal benefits from GLP-1RA and SGLT2i with use of meta-analysis and meta-regression. DATA SOURCES We performed a systematic review using PubMed through 7 November 2022. STUDY SELECTION We included reports of GLP-1RA and SGLT2i confirmatory randomized trials in adult patients with safety or efficacy end point data. DATA EXTRACTION Hazard ratio (HR) and event rate data were extracted for mortality, cardiovascular, and renal outcomes. DATA SYNTHESIS We analyzed 9 GLP-1RA and 13 SGLT2i trials comprising 154,649 patients. Summary HRs were significant for cardiovascular mortality (GLP-1RA 0.87 and SGLT2i 0.86), major adverse cardiovascular events (0.87 and 0.88), heart failure (0.89 and 0.70), and renal (0.84 and 0.65) outcomes. For stroke, efficacy was significant for GLP-1RA (0.84) but not for SGLT2i (0.92). Associations between control arm cardiovascular mortality rates and HRs were nonsignificant. Five-year absolute risk reductions (0.80–4.25%) increased to 11.6% for heart failure in SGLT2i trials in patients with high risk (Pslope < 0.001). For GLP1-RAs, associations were nonsignificant. LIMITATIONS Analyses were limited by lack of patient-level data, consistency in end point definitions, and variation in cardiovascular mortality rates for GLP-1RA trials. CONCLUSIONS Relative effects of novel diabetes drugs are preserved across baseline cardiovascular risk, whereas absolute benefits increase at higher risks, particularly regarding heart failure. Our findings suggest a need for baseline risk assessment tools to identify variation in absolute treatment benefits and improve decision-making.