GLP-1 and inflammatory markers — CRP, IL-6, TNF-α reduction data

Dr.MetabolicMD said:

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

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.

Following on from Dr.SleepRoch — and this may be the naive question:

Did your prescriber agree with that reading, and if not what was their objection?

PharmacoVig_BOS said:

Bayesian meta-analysis perspective on the trial evidence: traditional frequentist meta-analyses report point estimates and confidence intervals.

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 12,000 GLP-1 users vs matched controls showed reduced heart failure hospitalization (HR 0.74) over 3 years of follow-up[1].

These results complement the RCT data and suggest the benefits translate to real-world populations.

Closing the loop on my own question.

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.

NurseAsh_DET said:

Propensity score matching studies and the trial evidence: when RCTs aren't available for a specific question, propensity score-matched observational…

NurseAsh_DET 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.