PeptideChemSF said:

Relative and absolute effects need reading together.

Pushing back on PeptideChemSF here. 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.

TrialNerd_Beth 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…

Propensity score matching studies and the trial evidence: when RCTs aren't available for a specific question, propensity score-matched observational studies can provide useful evidence.

A recent PSM study of 18,000 GLP-1 users vs matched controls showed reduced all-cause mortality (HR 0.81) over 4 years of follow-up[1].

These results complement the RCT data and suggest the benefits translate to real-world populations.

anders_CPH said:

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

anders_CPH 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:

What did you change at the same time, and can you separate the two now?

Closing the loop on my own question.

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