Putting this up for argument rather than for agreement. I have read it twice and I am still not certain what it supports.
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.
Where I think it is weakest: the subgroup findings are the part I trust least — with enough subgroups something is always significant, and these were not all pre-registered.
The bit I cannot resolve on my own is how to read a result like this without either dismissing it or over-reading it, since the summaries all read like press releases. Not looking for reassurance. Looking for the part I have got wrong.
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:The gap between trial results and real-world results is consistent and it is not fraud.
Agreeing with GenomicsKate, and the qualification matters more than the agreement. 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.
GenomicsKate said:The gap between trial results and real-world results is consistent and it is not fraud.
This is where I part company with the consensus forming above. 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 ResultsTaking the question as asked, rather than the general version of 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.
PurityPaulOR said:Read four things before the headline number.
Can confirm. Same sequence, different timescale. Nothing to add that would improve it.