Answering the narrow version, because the broad one does not have a single answer. Read four things before the headline number. The population, because trial populations are selected and supported in ways that real cohorts are not. The comparator, because "better than placebo" and "better than the current standard" are different claims and get reported identically. The primary endpoint as pre-registered, because a secondary endpoint promoted after the fact is a hypothesis rather than a finding. And the completion rate, because a large effect in the half of participants who finished is a different result from a large effect in everybody enrolled.
Asking this as a poll because the anecdotes are plentiful and the distribution is not.
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 material.
What I actually want to know is how to read a result like this without either dismissing it or over-reading it, since the summaries all read like press releases.
Roughly, people seem to land in one of these:
- Held where they were and waited it out
- Changed one variable and kept everything else fixed
- Changed several things at once and cannot now attribute the result
- Stopped and reassessed from a clean baseline
Say which and say why — the why is the useful half.
TrialNerd_Beth 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 12,000 GLP-1 users vs matched controls showed reduced all-cause mortality (HR 0.81) over 3 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.
Sigma-Aldrich — Research-Grade Standards
Certified reference materials, analytical reagents, and research-grade standards for peptide verification. Trusted by laboratories worldwide.
Shop Reference Standardsandrew_nyc 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. 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.
From the other side of the consultation, briefly.
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 0.76 (95% CI 0.70-0.91), I²=49%. This is a robust and consistent effect.