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 population was selected and supported in ways a real cohort is not, so I would read the effect size as a ceiling rather than an expectation.
What I am after is how to read a result like this without either dismissing it or over-reading it, since the summaries all read like press releases. I have searched first, so if this is covered somewhere point me at it and I will read it.
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.
PedsEndoPhilly said:Relative and absolute effects need reading together.
That is correct as far as it goes, and here is where it stops going. 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.
I would rather be corrected than agreed with, if it comes to it.
PedsEndoPhilly 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.
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View ResultsThis one has a reasonably settled answer, so here it is. 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.
VendorMark said:The gap between trial results and real-world results is consistent and it is not fraud.
Can confirm. Same sequence, different timescale. The detail I would add is minor and it is already implied above.