Answering the narrow version, because the broad one does not have a single answer. 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.
My own curve sits about four points below the published mean and I spent two months assuming that meant something was wrong with me or with my material.
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.
Happy to be told the question itself is wrong.
SarahChen_PharmD said:The gap between trial results and real-world results is consistent and it is not fraud.
Propensity score matching studies and the trial evidence: when RCTs aren't available for a specific question, propensity score-matched observational studies can provide useful evidence.
A recent PSM study of 18,000 GLP-1 users vs matched controls showed reduced stroke risk (HR 0.82) over 4 years of follow-up[1].
These results complement the RCT data and suggest the benefits translate to real-world populations.
[1] Registry-based cohort study, pre-print 2024.
PeptideMeter — Independent Peptide Analytics
Community-driven peptide testing and vendor rating platform. Transparent results. Unbiased analysis. Trusted by thousands.
View ResultsRetaRick_CA said:My own curve sits about four points below the published mean and I spent two months assuming that meant something was wrong with me or with my…
This matches mine closely enough to be worth saying so. 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.
From the other side of the consultation, briefly.
RetaRick_CA said:...regarding the trial evidence...
I think this is an underappreciated point. To expand on it with some data:
A recent meta-analysis of 15 RCTs (n=12,300) found that the trial evidence was associated with a clinically meaningful effect size across diverse patient populations[1].
The NNT was 12, which is comparable to metformin for T2DM prevention. That's a strong clinical argument for this approach.