Dr.RaviCardio said:

Relative and absolute effects need reading together.

This is where I part company with the consensus forming above. I would add the less popular caveat: these trial populations under-represented several groups, older adults and the highest BMI categories among them. The results probably generalise, and "probably" should be stated as an assumption rather than dropped.

Dr.GastroMayo said:

My own curve sits about four points below the published mean and I spent two months assuming that meant something was wrong with me or with my…

Bayesian meta-analysis perspective on the trial evidence: traditional frequentist meta-analyses report point estimates and confidence intervals. Bayesian approaches provide probability distributions that are more intuitive for clinical decision-making.

For example: "There is a 98.5% probability that semaglutide 2.4mg produces >10% weight loss vs placebo" is more actionable than "RR 3.4, 95% CI 2.8-4.1, p<0.001."

The the trial evidence evidence is strong under both frameworks, but Bayesian analysis better communicates the degree of certainty for individual patient counseling.

BethLabQueen said:

I would add the less popular caveat: these trial populations under-represented several groups, older adults and the highest BMI categories among them.

BethLabQueen said:

...regarding the trial evidence...

I think this is an underappreciated point. To expand on it with some data:

A recent meta-analysis of 15 RCTs (n=12,300) found that the trial evidence was associated with a clinically meaningful effect size across diverse patient populations[1].

The NNT was 12, which is comparable to metformin for T2DM prevention. That's a strong clinical argument for this approach.

A narrower follow-up, since the general answer is now clear:

How would you tell the difference between that and the alternative explanation?

Reporting back.

Follow-up: I read the paper rather than the summary and the qualifier I was missing was in the second paragraph of the results.