InsuranceTom 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.
One concrete data point for the thread. A quick sanity check on any figure quoted here: is it mean or median, is it intention-to-treat or completers, and what was the comparator. Three questions, and they resolve most disagreements in these threads.
I would rather be corrected than agreed with, if it comes to it.
COA_Karl said:I would add the less popular caveat: these trial populations under-represented several groups, older adults and the highest BMI categories among them.
There is a second half to this that has not been said yet. 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.
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View ResultsA narrower follow-up, since the general answer is now clear:
How to read a result like this without either dismissing it or over-reading it, since the summaries all read like press releases?
OP back with an update, since a thread like this is useless without one.
Follow-up: I read the paper rather than the summary and the qualifier I was missing was in the second paragraph of the results.