Optimising GLP-1RA Efficacy: A Meta-Analysis of Baseline Age and HbA1c as Predictors of MACE Reduction in T2DM

优化GLP-1RA疗效:基线年龄和HbA1c作为2型糖尿病患者主要不良心血管事件(MACE)降低预测因子的荟萃分析

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Abstract

BACKGROUND: Type 2 diabetes mellitus (T2DM) increases major adverse cardiovascular event (MACE) risk, requiring effective interventions. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) reduce MACE, but the impact of baseline characteristics on their efficacy is unclear from previous analyses. METHODS: This PRISMA-guided systematic review and meta-analysis included randomised controlled trials (RCTs) comparing GLP-1RAs with placebo in patients with T2DM, sourced from PubMed and Google Scholar. We extracted MACE hazard ratios (HR), 95% confidence intervals (CI), and baseline characteristics (age, BMI, SBP, HbA1c, eGFR, male proportion, diabetes duration, CVD prevalence). A random-effects model estimated pooled HR, with heterogeneity assessed via prediction intervals. Meta-regression identified moderators. Sensitivity analyses and the RoB 2 Tool assessed bias; GRADE evaluated the certainty of evidence. RESULTS: Across 11 RCTs (83,536 participants), the pooled HR for MACE was 0.87 (95% CI: 0.81-0.93), indicating a 13% risk reduction with moderate heterogeneity (prediction interval: 0.79-0.96). After excluding T2DM duration due to multicollinearity, multivariate meta-regression identified age (p = 0.02) and HbA1c (p = 0.03) as significant moderators, which persisted after excluding FREEDOM-CVO (age, p = 0.03; HbA1c, p = 0.04). Baseline CVD prevalence did not moderate outcomes (p = 0.892). Bias was low; evidence certainty was moderate. CONCLUSION: GLP-1RAs reduce MACE in T2DM, particularly in older patients with lower baseline HbA1c. This fills a critical gap in prior meta-analyses by identifying actionable pre-treatment predictors that support personalised therapy. PROTOCOL REGISTRATION: Ghosal et al INPLASY protocol 202580045. doi:10.37766/inplasy2025.8.0045 INPLASY202580045.

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