- Design
- Mediation analysis of a double-blind, placebo-controlled randomised trial
- Population
- SELECT participants: adults with cardiovascular disease, BMI ≥27, no diabetes
- Primary outcome
- Proportion of MACE reduction mediated by 24-month risk-factor changes
- Effect
- Joint mediation 31.4% (95% CI −30.1 to 143.6); waist 64.0%, hsCRP 42.1%, all wide CIs
SELECT showed that weekly semaglutide 2.4 mg reduced major adverse cardiovascular events by 20% in adults with established cardiovascular disease and a BMI of 27 or more without diabetes. This analysis asked how much of that benefit could be explained by changes over 24 months in weight, waist, high-sensitivity CRP, HbA1c, lipids, blood pressure, eGFR and albuminuria, using a counterfactual regression method.
Semaglutide improved every one of these. The largest point estimates of mediation were for waist circumference (64%), CRP (42%), HbA1c (29%) and weight (19.5%), but every interval was very wide, and the authors judged the weight and waist estimates unreliable. All mediators together explained an estimated 31.4% (95% CI −30.1 to 143.6).
The honest reading is that the analysis cannot say how semaglutide protects. The benefit in SELECT is real; its mechanism is not established, and it may not depend on the amount of weight a patient loses.
- The SELECT benefit applies to the trial population — established cardiovascular disease, BMI of 27 or more, no diabetes.
- Do not judge whether semaglutide is 'working' for cardiovascular protection by weight loss alone.
- CRP fell with treatment, but this analysis does not show inflammation is the mechanism.
- Weight loss from semaglutide does not replace statins, antiplatelets or blood pressure control in secondary prevention.
Why it matters
Patients who lose little weight on semaglutide may still be getting the cardiovascular benefit.
Don't overread it
None of the mediation estimates is precise enough to say CRP, waist or weight explains the effect.
The statistics, in plain English
Mediation intervals that run below 0% and above 100% mean the data are consistent with a factor explaining none of the effect or all of it. The point estimates should not be quoted as fractions of the benefit.
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