Comment by twoodfin
14 hours ago
What evidence are you talking about? Do you think industrial scientists collaborating with academics and vice-versa is unusual?
14 hours ago
What evidence are you talking about? Do you think industrial scientists collaborating with academics and vice-versa is unusual?
In addition to the funding bias wikipedia article someone else already cited:
https://www.cochranelibrary.com/cdsr/doi/10.1002/14651858.MR...
> Sponsorship of drug and device studies by the manufacturing company leads to more favorable efficacy results and conclusions than sponsorship by other sources. Our analyses suggest the existence of an industry bias that cannot be explained by standard 'Risk of bias' assessments.
And no! It's not unusual, nor does it mean the results are wrong. It just means there's a known bias towards results that favor the sponsor's interests that needs to be taken into account when evaluating the research. Again, that doesn't make it wrong. But it should make you cautious before thinking that a single study (in a very specific sub-population, at that) is necessarily going to generalize. It might. I hope it does! GLP-1's are awesome. But cautiously.
This is a federally funded study. Says so in the bright yellow “Key takeaways” box at the top of TFA.
But ok, sure, drug companies bad. Man hn is really turning into Reddit these days.
Dude. From the paper itself:
"Competing interests G.A.M. serves as a research consultant for Merck, GlaxoSmithKline/ViiV, and Gilead. M.J.C. serves as a scientific advisor for TruDiagnostic. V.D. and R.S. are employees of TruDiagnostic. All other authors declare no competing interests."
These are known risk factors. I've never said drug companies are bad. I literally take corporate funding for my own research. But you also don't get to stick your head in the sand and ignore the competing interests that all make the research more likely to show favorable results. Again for those in the back: These results probably _are_ correct! But do they generalize? Will they hold up on replication with a larger population? Do they matter, or is the proxy they're measuring not actually relevant for long term things in humans? Dunno. That's the thing about a _statistical likelihood of bias_ -- you have no idea exactly how to apply it to a single paper other than to say "ok, known possibility of bias, interpret accordingly."
2 replies →
https://en.wikipedia.org/wiki/Funding_bias
Academic research is subject to dozens of potentially corrupting biases, named and otherwise. We still do it and get great benefit from it.
Again, what’s the evidence that this research in particular should be suspect? It looks a lot like all the other research that goes on in this space. Experimenting with biological systems & real humans is expensive, even when you’re mostly doing data collection. It needs funding!
All research from people who financially benefit from the outcome that they have reported should be suspect. Being questioned is not a punishment.
If you ask your child who enjoys video games to stop playing video games and do their homework, and they tell you they don't have any homework, you're silly (trying to use a kind word) if you don't apply far more scrutiny than if they told you that they had an enormous amount of homework that would keep them from playing video games for the next few days.
You don't need evidence to question this. That the reply is convenient is itself evidence. The reply is consistent with someone who is lying in order to play video games. It is not proof.