Taking the question as asked, rather than the general version of it. Relative and absolute effects need reading together. A 20% relative reduction on a high baseline risk is a large absolute benefit; the same relative figure on a low baseline risk is a small one, and press summaries almost always quote the relative number because it is bigger.

Ask again with the specifics and you will get a better answer than this one.

Dr.RaviCardio said:

Relative and absolute effects need reading together.

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 0.74 (95% CI 0.67-0.84), I²=32%. This is a robust and consistent effect.

Dr.GastroMayo 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…

Same position here, arrived at the long way round. The gap between trial results and real-world results is consistent and it is not fraud. Trial participants get titration by protocol, scheduled contact, free drug and dietetic support; removing that infrastructure costs a few percentage points every time it has been measured. When your own curve sits below the published mean, that is the likeliest explanation before anything about you or your material.

Adding the clinical framing, because it changes how the question reads.

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 stroke risk (HR 0.82) over 3 years of follow-up[1].

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