Pharmacogenomics of GLP-1 response — GLP1R gene variants

GenomicsKate said:

Relative and absolute effects need reading together.

GenomicsKate said:

...regarding the trial evidence...

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

A recent meta-analysis of 12 RCTs (n=8,400) found that the trial evidence was associated with a significant effect size across diverse patient populations[1].

The NNT was 8, which is comparable to statins for secondary prevention. That's a strong clinical argument for this approach.

Following on from pete_nash — and this may be the naive question:

How long did you give it before you decided it was working?

Dr.PeteFamMed said:

GenomicsKate said: ...regarding the trial evidence...

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 0.73 (95% CI 0.65-0.88), I²=46%. This is a robust and consistent effect.

OP back with an update, since a thread like this is useless without one.

Follow-up: I read the paper rather than the summary and the qualifier I was missing was in the second paragraph of the results.

PharmHunterJen said:

Forest plot interpretation for the the trial evidence meta-analysis: when reading the pooled estimate, pay attention to: Point estimate (HR/RR/OR) —…

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 heart failure hospitalization (HR 0.74) over 4 years of follow-up[1].

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