labquiet_amy said:Relative and absolute effects need reading together.
Filing a mild objection. Mild because I might be wrong; an objection because nobody has addressed the case that does not fit. 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.
SteveThurs said:I keep finding that the number in the press summary and the number in the paper are not the same number, and the difference is always in the same…
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 0.80 (95% CI 0.71-0.90), I²=38%. This is a robust and consistent effect.
PharmacoVig_BOS said:I would add the less popular caveat: these trial populations under-represented several groups, older adults and the highest BMI categories among them.
Bayesian meta-analysis perspective on the trial evidence: traditional frequentist meta-analyses report point estimates and confidence intervals. Bayesian approaches provide probability distributions that are more intuitive for clinical decision-making.
For example: "There is a 98.5% probability that semaglutide 2.4mg produces >10% weight loss vs placebo" is more actionable than "RR 3.4, 95% CI 2.8-4.1, p<0.001."
The the trial evidence evidence is strong under both frameworks, but Bayesian analysis better communicates the degree of certainty for individual patient counseling.
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View ResultsA narrower follow-up, since the general answer is now clear:
Was that from a primary source or from a summary of one?
Closing the loop on my own question.
Follow-up: I read the paper rather than the summary and the qualifier I was missing was in the second paragraph of the results.