Type 2 & other diabetes

Cardiovascular risk reduction with glucagon‐like peptide‐1 receptor agonists is proportional to HbA1c lowering in type 2 diabetes: An updated meta‐regression analysis incorporating FLOW and SOUL trials

Diabetes Obes MetabPublished Systematic review and meta-analysis with meta-regression of randomised placebo-controlled trials

Pooled result · MACEResult — go to the resultHazard ratio 0.86 95% CI 0.82–0.91

Authors' conclusion

HbA1c reduction, not bodyweight change, was significantly and proportionally associated with MACE risk reduction. HbA1c lowering may serve as a useful surrogate for the cardiovascular improvements associated with GLP-1RAs in type 2 diabetes.

Study context

Population
Adults with T2D in placebo-controlled RCTs of GLP-1 RA reporting major adverse cardiovascular events (MACE) (PubMed and EMBASE to 22 August 2025)
Participants
73,263 adults10 trials
Comparison
GLP-1 RA vs placebo
Outcome
MACE
Methodological detailsrandom-effects meta-analysis
  • Random-effects meta-analysis

Pooled result

As reported in the abstract

Hazard ratio

0.86

95% CI 0.82–0.91

P < 0.001

GLP-1RAsvs Placebo
HR 0.86 (95% CI 0.82–0.91); P < 0.001
Meta-regression: every 1% extra HbA1c reduction corresponded to a 27% lower HR for MACE (p = 0.015)
R2 = 0.61
Meta-regression: bodyweight change not associated with MACE (p = 0.13)
R2 = 0.21

Further pooled results

OutcomeP value
Hospitalisation for HF and composite kidney outcomeReduced with GLP-1RAsboth p <0.001

Hospitalisation for heart failure (HF) and composite kidney outcome

HbA1c reduction not significantly associated with secondary outcomes; directionality consistent with MACE
Bodyweight change not associated with any analysed endpoint

Original publication

Cardiovascular risk reduction with glucagon‐like peptide‐1 receptor agonists is proportional to HbA1c lowering in type 2 diabetes: An updated meta‐regression analysis incorporating FLOW and SOUL trials. Diabetes Obes Metab. Published 9 September 2025. doi:10.1111/dom.70121

Composed by AI from the published abstract and checked against it. How Briefs are made →

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