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.
A 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?
bri_stats said: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.
Coming at bri_stats’s question from a different direction. 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 ResultsOP back with an update, since a thread like this is useless without one.
Update — my curve sits below the published mean and the explanation is that the trial arm had support I do not have. That was reassuring rather than otherwise.
CarlaRPh_TPA said:The gap between trial results and real-world results is consistent and it is not fraud.
CarlaRPh_TPA said:...regarding the trial evidence...
I think this is an underappreciated point. To expand on it with some data:
A recent meta-analysis of 18 RCTs (n=15,600) found that the trial evidence was associated with a robust effect size across diverse patient populations[1].
The NNT was 15, which is comparable to antihypertensives for stroke reduction. That's a strong clinical argument for this approach.