Risk–Benefit Trade-offs of GLP-1RAs and SGLT-2is in Type 2 Diabetes Mellitus (T2D): Systematic Review, Meta-Analysis, and Net Benefit Modeling.

Introduction: While glucagon-like peptide-1 receptor agonists (GLP-1RAs) and sodium-glucose cotransporter-2 inhibitors (SGLT-2is) are established for cardiorenal benefits in type 2 diabetes mellitus (T2DM), prior meta-analyses have not fully integrated cross-class comparisons or net benefit analyses...

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Publicado en:Diabetes Therapy Vol. 17; no. 1; pp. 55 - 73
Autores principales: Ghosal, Samit, Ghosal, Anuradha
Formato: meta analysis research systematic review tables/charts Journal Article
Publicado: Springer Nature Jan2026
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jan2026
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s13300-025-01817-5
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        atl: Risk–Benefit Trade-offs of GLP-1RAs and SGLT-2is in Type 2 Diabetes Mellitus (T2D): Systematic Review, Meta-Analysis, and Net Benefit Modeling.
      aug:
        au:
          Ghosal, Samit
          Ghosal, Anuradha
        affil: https://ror.org/05r0sm904 Nightingale Hospital, 11 Shakespeare Sarani, 700071, Kolkata, West Bengal, India
      sug:
        subj:
          Glucagon-Like Peptide-1 Receptor Agonists Therapeutic Use
          Sodium-Glucose Co-Transporter 2 Inhibitors Therapeutic Use
          Diabetes Mellitus, Type 2 Drug Therapy
          Treatment Outcomes
          Risk Assessment
          Cardiovascular Risk Factors
          Patient Safety
          Human
          Systematic Review
          Meta Analysis
          Confidence Intervals
          Sensitivity and Specificity
          Major Adverse Cardiac Events
          Heart Failure
          Hospitalization
          Retinal Diseases
          Amputation
      ab: Introduction: While glucagon-like peptide-1 receptor agonists (GLP-1RAs) and sodium-glucose cotransporter-2 inhibitors (SGLT-2is) are established for cardiorenal benefits in type 2 diabetes mellitus (T2DM), prior meta-analyses have not fully integrated cross-class comparisons or net benefit analyses with updated cardiovascular outcome trials (CVOTs). Methods: We conducted a systematic review and meta-analysis of 17 CVOTs (N = 132,038; GLP-1RA: N = 73,263; SGLT-2i: N = 58,775) using PubMed and Cochrane CENTRAL. We uniquely synthesized major adverse cardiovascular events (MACE), hospitalization for heart failure (hHF), renal composites, and safety outcomes (e.g., retinopathy, genitourinary infections) with random-effects models for hazard ratios (HRs) and relative risks (RRs). Innovative graphical syntheses (tornado/scatter plots, risk curves) and net benefit calculations (absolute risk reductions [ARRs] minus absolute excess risks [AERs]) were employed. Risk of bias (RoB 2) and GRADE certainty were assessed. Results: Both classes reduced MACE (HR 0.87, 95% CI 0.84–0.90; p = 0.73 for class difference). SGLT-2is were superior for hHF (HR 0.69 vs. 0.88, p < 0.0001) and renal outcomes (HR 0.68 vs. 0.79, p = 0.026). GLP-1RAs increased retinopathy (RR 1.18, AER + 6.5/1000); SGLT-2is increased genitourinary infections (RR 3.34, AER + 19.9/1000) and DKA (RR 2.67, AER + 1.2/1000). Amputation signals attenuated post-sensitivity analysis. Net benefits favored GLP-1RAs for MACE (+ 2.5/1000). For SGLT-2is, base-case estimates using genital-mycotic infections as the sentinel harm were marginal (hHF: − 4.9/1000; renal: − 1.9/1000), whereas sensitivity scenarios with alternative harms (e.g., volume depletion, amputation, DKA) yielded positive net benefits. GRADE certainty was high for efficacy, moderate for harms. Conclusions: Our innovative integration of updated CVOTs, cross-class comparisons, and graphical risk–benefit tools refines therapeutic decision-making, highlighting tailored T2DM management based on patient-specific cardiorenal risks. Trial Registration: PROSPERO (CRD420251146788).
      pubtype: Academic Journal
      doctype:
        meta analysis
        research
        systematic review
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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