HPLC_Greg said:Read four things before the headline number.
I read this differently from HPLC_Greg, on substance rather than tone. 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.
FitDadDave 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…
FitDadDave said:...regarding the trial evidence...
I think this is an underappreciated point. To expand on it with some data:
A recent meta-analysis of 15 RCTs (n=12,300) found that the trial evidence was associated with a clinically meaningful effect size across diverse patient populations[1].
The NNT was 12, which is comparable to antihypertensives for stroke reduction. That's a strong clinical argument for this approach.
VendorMark said:I would add the less popular caveat: these trial populations under-represented several groups, older adults and the highest BMI categories among them.
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 0.66-0.87), I²=35%. This is a robust and consistent effect.
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Browse GL BiochemFollowing on from Dr.KarenChen — and this may be the naive question:
What would you measure differently if you were starting again?
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.