Thanks for the reminder about selection bias. Interesting to note that I’m an extremely compliant person with my recovery from addiction, in fact if I was that compliant with all of my chronic issues I’d probably be able to get off a few meds. Which is kinda my point. I noticed that when I got on a statin, I let my healthy diet go a bit “bc the statin will take care of it.” And lo and behold my A1C got wonky. Back to regular diet and much better again. Took some time! I noticed that, before my recovery, my coincidentally high LFT’s were bc of autoimmune hepatitis, not alcohol and too much Tylenol (Percocet - yep - I combined em like every good addict should). But once the AIH was managed and LFT’s went down, well you know what addict logic dictates! Fortunately the extreme excesses there gave me enough consequences to get help and recover from addiction, a day at a time.
Anyway, I think it’s extremely difficult to do true RCT’s and I applaud all of you who think through and ahead and remind us that although we strive for perfection with rigorous science, it’s never perfect. It’s as complex as each N=1 that we all are.
Given that type 2 diabetes is really a surrogate marker condition I've never understood why if there was a 1% absolute increase in the number of people who just happened to cross an arbitrary A1c threshold this would be of concern. The biggest "risk" for people with T2DM is CVD and statins overall reduce CVD risk. So who cares if a lab value goes up slightly in 1% of people. Am I missing something?
Nicely done. Elegant. Useful. Yet, I am always skeptical of large studies with very low p values. I can't help it. Blame it on my stat's professor. If only a longitudinal trial using this strategy had been started when we first noticed the link between statins and diabetes. Dr. Foy, great work. Glad to see you back.
Nice to see a different approach to looking at a very common issue for most physicians. It is especially appreciated when we need more well done studies in an era where studies conclusions are often pre-determined. Thanks.
Thanks for the reminder about selection bias. Interesting to note that I’m an extremely compliant person with my recovery from addiction, in fact if I was that compliant with all of my chronic issues I’d probably be able to get off a few meds. Which is kinda my point. I noticed that when I got on a statin, I let my healthy diet go a bit “bc the statin will take care of it.” And lo and behold my A1C got wonky. Back to regular diet and much better again. Took some time! I noticed that, before my recovery, my coincidentally high LFT’s were bc of autoimmune hepatitis, not alcohol and too much Tylenol (Percocet - yep - I combined em like every good addict should). But once the AIH was managed and LFT’s went down, well you know what addict logic dictates! Fortunately the extreme excesses there gave me enough consequences to get help and recover from addiction, a day at a time.
Anyway, I think it’s extremely difficult to do true RCT’s and I applaud all of you who think through and ahead and remind us that although we strive for perfection with rigorous science, it’s never perfect. It’s as complex as each N=1 that we all are.
I would love to see Dr. Aseem Malhotra comment on this!
Given that type 2 diabetes is really a surrogate marker condition I've never understood why if there was a 1% absolute increase in the number of people who just happened to cross an arbitrary A1c threshold this would be of concern. The biggest "risk" for people with T2DM is CVD and statins overall reduce CVD risk. So who cares if a lab value goes up slightly in 1% of people. Am I missing something?
Nicely done. Elegant. Useful. Yet, I am always skeptical of large studies with very low p values. I can't help it. Blame it on my stat's professor. If only a longitudinal trial using this strategy had been started when we first noticed the link between statins and diabetes. Dr. Foy, great work. Glad to see you back.
Nice to see a different approach to looking at a very common issue for most physicians. It is especially appreciated when we need more well done studies in an era where studies conclusions are often pre-determined. Thanks.