Can we talk about how SLOW the FDA is

Answering the narrow version, because the broad one does not have a single answer. 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.

Dr.NateNeph said:

Read four things before the headline number.

Bayesian meta-analysis perspective on the trial evidence: traditional frequentist meta-analyses report point estimates and confidence intervals. Bayesian approaches provide probability distributions that are more intuitive for clinical decision-making.

For example: "There is a 98.5% probability that semaglutide 2.4mg produces >10% weight loss vs placebo" is more actionable than "RR 3.4, 95% CI 2.8-4.1, p<0.001."

The the trial evidence evidence is strong under both frameworks, but Bayesian analysis better communicates the degree of certainty for individual patient counseling.

KarenAZ_mom 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…

Can confirm the pattern KarenAZ_mom describes. 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.

From the other side of the consultation, briefly.

KarenAZ_mom 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 statins for secondary prevention. That's a strong clinical argument for this approach.