Posting this because the summary going around does not say what the paper says, and the difference matters for how people here are using 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.
Where I think it is weakest: the follow-up is short relative to how long people actually take these drugs, so durability is an assumption here rather than a finding.
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. Practical detail welcome, however dull — the duller the better.
Figures above are from the primary publication rather than the press summary. If a number here disagrees with one you have, post yours and we will work out which of us is reading a secondary source.
GenomicsKate said:Relative and absolute effects need reading together.
No disagreement with GenomicsKate. One condition attached. 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.
GenomicsKate said:Relative and absolute effects need reading together.
I read this differently from GenomicsKate, 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.
That is the short version; the long version is somebody else's post.
PeptideDetective — Independent Peptide Analytics
Community-driven peptide testing and vendor rating platform. Transparent results. Unbiased analysis. Trusted by thousands.
View ResultsTaking the question as asked, rather than the general version of it. 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.
HPLC_Greg said:The gap between trial results and real-world results is consistent and it is not fraud.
Can confirm. Same sequence, different timescale.