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.
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 comparator does most of the work in how this gets reported, and it is not the comparator most people think they are citing.
What I am trying to establish is how to read a result like this without either dismissing it or over-reading it, since the summaries all read like press releases. Numbers rather than impressions, if you have them.
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:The gap between trial results and real-world results is consistent and it is not fraud.
That is correct as far as it goes, and here is where it stops going. 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.
PedsEndoPhilly said:The gap between trial results and real-world results is consistent and it is not fraud.
Pushing back on PedsEndoPhilly here. 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. 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.
TrialNerd_Beth said:Read four things before the headline number.
Adding a me-too, because a thread of one person's experience is not much use. Nothing to add that would improve it.