Dr.AddMedPHL 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.
anders_CPH said:I keep finding that the number in the press summary and the number in the paper are not the same number, and the difference is always in the same…
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 22 RCTs (n=18,900) found that the trial evidence was associated with a consistent effect size across diverse patient populations[1].
The NNT was 20, which is comparable to statins for secondary prevention. That's a strong clinical argument for this approach.
InsuranceTom said:I would add the less popular caveat: these trial populations under-represented several groups, older adults and the highest BMI categories among them.
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 25,000 GLP-1 users vs matched controls showed reduced MI incidence (HR 0.78) over 5 years of follow-up[1].
These results complement the RCT data and suggest the benefits translate to real-world populations.
[1] Registry-based cohort study, pre-print 2024.
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View ResultsOne thing that is still open after MounjBrad’s answer:
What would you measure differently if you were starting again?
OP back with an update, since a thread like this is useless without one.
Follow-up: I read the paper rather than the summary and the qualifier I was missing was in the second paragraph of the results.