tyler_CSCS said:

Relative and absolute effects need reading together.

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 stroke risk (HR 0.82) over 4 years of follow-up[1].

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

Following on from Dr.GastroMayo — and this may be the naive question:

How long did you give it before you decided it was working?

LabKate said:

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

LabKate 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 metformin for T2DM prevention. That's a strong clinical argument for this approach.

Reporting back.

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.

jim_asheville said:

LabKate said: ...regarding the trial evidence...

Forest plot interpretation for the the trial evidence meta-analysis: when reading the pooled estimate, pay attention to:

1. Point estimate (HR/RR/OR) — center of the diamond
2. Confidence interval width — precision of the estimate
3. I² statistic — heterogeneity across studies
4. Individual study weights — are results driven by one large trial?
5. Prediction interval — range of plausible true effects in future settings

The the trial evidence meta-analysis shows a pooled RR of 0.86 (95% CI 0.69-0.86), I²=44%. This is a robust and consistent effect.