Started this morning and already overthinking everything — my results so far

Taking the question as asked, rather than the general version of 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.

PeptideChemSF said:

The gap between trial results and real-world results is consistent and it is not fraud.

PeptideChemSF said:

...regarding the trial evidence...

I think this is an underappreciated point. To expand on it with some data:

A recent meta-analysis of 22 RCTs (n=18,900) found that the trial evidence was associated with a consistent effect size across diverse patient populations[1].

The NNT was 20, which is comparable to statins for secondary prevention. That's a strong clinical argument for this approach.

hans_munich 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.

Adding the clinical framing, because it changes how the question reads.

Forest plot interpretation for the the trial evidence meta-analysis: when reading the pooled estimate, pay attention to:

1. Point estimate (HR/RR/OR) — center of the diamond
2. Confidence interval width — precision of the estimate
3. I² statistic — heterogeneity across studies
4. Individual study weights — are results driven by one large trial?
5. Prediction interval — range of plausible true effects in future settings

The the trial evidence meta-analysis shows a pooled RR of 0.82 (95% CI 0.66-0.87), I²=55%. This is a robust and consistent effect.