PeptideChemSF said:Relative and absolute effects need reading together.
This is exactly what I could not find anywhere else. Sending this to two other people who asked me the same thing last week.
Adding the clinical framing, because it changes how the question reads.
Forest plot interpretation for the the trial evidence meta-analysis: when reading the pooled estimate, pay attention to:
- Point estimate (HR/RR/OR) — center of the diamond
- Confidence interval width — precision of the estimate
- I² statistic — heterogeneity across studies
- Individual study weights — are results driven by one large trial?
- Prediction interval — range of plausible true effects in future settings
The the trial evidence meta-analysis shows a pooled RR of 0.77 (95% CI 0.71-0.82), I²=50%. This is a robust and consistent effect.
claudia_zurich said:Read four things before the headline number.
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 MI incidence (HR 0.78) over 4 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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Admin said:...regarding the trial evidence...
I think this is an underappreciated point. To expand on it with some data:
A recent meta-analysis of 18 RCTs (n=15,600) found that the trial evidence was associated with a robust effect size across diverse patient populations[1].
The NNT was 15, which is comparable to antihypertensives for stroke reduction. That's a strong clinical argument for this approach.