This gets cited here weekly, usually second-hand, so it is worth setting out what it does and does not establish.
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.
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.
The question I want answered is how to read a result like this without either dismissing it or over-reading it, since the summaries all read like press releases. Tell me what I have not thought of.
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.
MASHdoc_SA said:Read four things before the headline number.
Agreeing with MASHdoc_SA, and the qualification matters more than the agreement. 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.
MASHdoc_SA said:Read four things before the headline number.
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.
That is the short version; the long version is somebody else's post.
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View ResultsShort answer first, then the reasoning. 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.
Dr.PeteFamMed said:Relative and absolute effects need reading together.
Agreed, and ALT falling is not the same as fibrosis improving. Enzymes are a crude proxy; FIB-4 or elastography is what tells you about the thing that matters.