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

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.