kate.chem said:Relative and absolute effects need reading together.
Pushing back on kate.chem 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.
TomFromTexas 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 12,000 GLP-1 users vs matched controls showed reduced MI incidence (HR 0.78) over 3 years of follow-up[1].
These results complement the RCT data and suggest the benefits translate to real-world populations.
pete_manc_UK said:I would add the less popular caveat: these trial populations under-represented several groups, older adults and the highest BMI categories among them.
pete_manc_UK 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 antihypertensives for stroke reduction. That's a strong clinical argument for this approach.
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View ResultsFollowing on from VanRx_Mike — and this may be the naive question:
How would you tell the difference between that and the alternative explanation?
OP back with an update, since a thread like this is useless without one.
Update — my curve sits below the published mean and the explanation is that the trial arm had support I do not have. That was reassuring rather than otherwise.