Network and pairwise meta-analysis of the effects of novel hypoglycemic agents on cardiorenal outcomes in patients with type 2 diabetes and heart failure
In brief
Sodium-glucose cotransporter 2 drugs cut heart-failure composite risk 25%
In a meta-analysis of 13,886 people with type 2 diabetes and heart failure, sodium-glucose cotransporter 2 inhibitors reduced the risk of heart-failure composite outcomes by 25% versus placebo; they also lowered heart-failure hospitalization and cardiovascular death. GLP-1 receptor agonists showed a similar reduction in the composite outcome, but kidney benefits were not statistically clear, and the analysis did not establish one drug class as superior.
- Journal
- Frontiers in endocrinology (Q1)
- Published
- 14 October 2026
- Study design
- Systematic review / meta-analysis of RCTs
- Evidence level
- Level 1, High (CEBM 1a)
- Authors
- Xuejiao Ye, Qian Wu, Leyang Li, Mingyu Huang, Shihan Wang
- PMID
- 42952754
- DOI
- 10.3389/fendo.2026.1955431
Why clinicians should know about it
- Picked for Cardiology and Cardiovascular Medicine (top studies of the week, 1 November 2026): Cardiorenal drug outcomes in patients with diabetes and heart failure
- Picked for Nephrology (top studies of the week, 1 November 2026): Meta-analysis evaluates renal outcomes of diabetes therapies in heart failure
Abstract
OBJECTIVE: This study aims to evaluate the cardiovascular and renal benefits of novel hypoglycemic agents, including glucagon-like peptide-1 receptor agonists (GLP-1RAs), dipeptidyl peptidase-4 inhibitors (DPP-4is), sodium-glucose cotransporter-2 inhibitors (SGLT-2is), and glucose-dependent insulinotropic polypeptide/glucagon-like peptide-1 dual receptor agonists (GIP/GLP-1RAs) in patients with type 2 diabetes mellitus (T2DM) and heart failure (HF). METHODS: Systematic literature searches were conducted in MEDLINE, Embase, ClinicalTrials.gov, and Cochrane Central Register of Controlled Trials (CENTRAL) from inception to 30 April 2026. Randomized controlled trials (RCTs) for cardiovascular outcomes (CVOTs) or post hoc analyses of CVOTs comparing SGLT-2is, DPP-4is, GLP-1RAs, or GIP/GLP-1RAs in patients with T2DM and HF were selected. Network meta-analysis was used for indirect comparisons, with results presented as hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: A total of 10 RCTs and two post hoc analyses of CVOTs involving 13,886 patients were included. Compared with placebo, SGLT-2is (HR [95% CI]: 0.75 [0.68, 0.82]) and GLP-1RAs (HR [95% CI]: 0.77 [0.61, 0.97]) both significantly reduced the risk of HF-related composite endpoints in patients with T2DM and HF. No statistically significant difference was observed between SGLT-2is and GLP-1RAs (HR [95% CI]: 0.98 [0.76, 1.25]). SGLT-2is also reduced the risk of HF worsening (HR [95% CI]: 0.72 [0.53, 0.96]), HF hospitalization (HR [95% CI]: 0.74 [0.66, 0.83]), and cardiovascular (CV) death (HR [95% CI]: 0.87 [0.77, 0.98]). For all-cause death, SGLT-2is showed a trend toward reduced risk compared to placebo, but this difference did not reach statistical significance (HR [95% CI]: 0.83 [0.67, 1.02]). For the renal composite outcome, SGLT-2is did not demonstrate a statistically significant benefit (HR [95% CI]: 0.76 [0.51, 1.14]). CONCLUSION: Optimal clinical management of T2DM requires a comprehensive assessment of cardiovascular and renal comorbidities. This network meta-analysis indicates that SGLT-2is significantly reduce the risk of HF-related composite endpoints and CV death in T2DM patients with HF, although their renoprotective effect does not reach statistical significance. GLP-1RAs also demonstrate beneficial effects on HF-related composite endpoints. These findings suggest that both SGLT-2is and GLP-1RAs are preferred glycemic control strategies for improving cardiovascular outcomes in T2DM patients with HF, while further evidence is needed to confirm their definitive renal benefits. SYSTEMATIC REVIEW REGISTRATION: https://www.crd.york.ac.uk/PROSPERO/view/CRD42026142123, identifier: CRD420261421235.
Abstract as published, via PubMed.
For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.