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If conducted properly, those studies count for a lot.
If conducted by people with conflicts of interest using arbitrary stopping parameters and endpoints, etc., then not so much.
http://www.ncbi.nlm.nih.gov/pubmed/20585067
low sodium -> food taste bad -> my fat a** patients stop eating -> their glucose and BP drops. i support low sodium diets.
low sodium -> food taste bad -> my fat a** patients stop eating -> their glucose and BP drops. i support low sodium diets.
It's not that the study had that much more statistical power, it's that they used different inclusion criteria.
The trial I linked to included only people with NO evidence of cardiovascular disease. The study you linked to included some people WITH cardiovascular disease: "Data from trials in which some, but not all, participants had known cardiovascular disease were included if the control group had a low cardiovascular risk (as defined above)."
Look, very few people deny that statins positively affect mortality in people with sufficient cardiovascular disease. So yes, if you include sicker people then you will see a greater effect. This is a fairly simple concept. By using such a scheme, the authors miss the point entirely. The problem with many trials is that sick people are grouped together with healthy people and the effect on this combined group is reported. The purpose of these newer analyses is to see what effect statins have on healthy people. To achieve fine resolution and prove that healthy people should get statins, you can't include people with CVD. Conclusion: the study you linked cannot be used to argue that people with no CVD should get statins because they included people with CVD! The whole idea is to exclude people with CVD!
Now, with further analysis perhaps we can posit some criteria that can be used to categorize CVD-free people into "should treat" and "shouldn't treat" groups. We're not there yet but you still want to treat all of them! This is not good medicine. First do no harm, right?
I'm happy that my peers throughout the country are being taught to adequately evaluate evidence based medicine and not take the first thing they read to be gospel.
You left out the rest of the paragraph:"Trials were considered to have enrolled participants at low cardiovascular risk if the 10-year risk of cardiovascular-related death or nonfatal myocardial infarction among participants was less than 20%, as assessed by extrapolation of observed risk in the control group of each trial. In general, this corresponded to participants who were free from cardiovascular disease (i.e., no prior acute coronary syndrome or coronary revascularization, no prior ischemic stroke and no prior revascularization or loss of limb owing to peripheral arterial disease) and diabetes. Data from trials in which some, but not all, participants had known cardiovascular disease were included if the control group had a low cardiovascular risk (as defined above)."
The larger sample size equaled more statistical power. You can argue about their inclusion criteria if you'd like. The reasoning is certainly debatable, and there have been plenty of responses both ways in the scientific literature regarding primary prevention in lower risk groups. There's problems with some of the studies included in your paper and there's debate on inclusion of other ones.
You most certainly have no leg to stand on when it comes to secondary prevention though, which makes your "Wait until you folks start re-thinking statins and cholesterol." that started this discussion even sillier.
Now, do I think every single person on the planet should be started on a statin? Of course not. Do I think they have robust evidence at being effective (and cost effective!) for primary prevention of morbidity and mortality? Yes. The absolute benefits of statins are smaller in primary prevention than in secondary prevention, but the effects are real. And I definitely think everyone with mid-high risk or a history of CAD should be on a statin, except in the rare circumstances they can't tolerate it.
I think I'm done posting in this thread, simply because the evidence is there for people who want to look it up and I don't have the time, especially this close to the end of a clerkship. A quick summary for those of you actually here with an open mind:
You're medical students (or people who want to be medical students), so presumably you trust in (at least some parts of) medicine. You're paying schools tens of thousands of dollars to learn medicine, and I would assume you trust the experienced clinicians teaching you. When you come across claims, in person or on the internet, that are the exact opposite of what you're being taught, there are two possibilities: Your preceptors are wrong/out of date, or the source of conflict is wrong/out of date. Is the former possible? Yes, though most academic clinicians are better than others on keeping up with the evidence. For minor things especially, they can be wrong. (Ex: I've had people tell me to never use lidocaine w/ epi on fingers/toes/nose/penis b/c of the necrosis risk. There's been papers that have examined this medical fact and found there to be no evidence behind it, just a case report or two from before the 1950s when there was no such thing as lidocaine and epi doses in locals were far from standardized)
But the simpler explanation if you see something that disagrees with a major medical fact you were taught is that there's something wrong with the claim. Do the research. Go to uptodate or look at the actual trials. You might find conflicting trials, look at the further papers that are replies to them. Keep in mind levels of evidence and things like statistical power. Or you might find the claims are made based on misinterpretations or they're made based on old data that has since been debunked. Lots of things are up for debate, but extraordinary claims (such as "the entire medical establishment is wrong and has been wrong for 50 years about xyz that has been researched to death but there's a conspiracy to tell people otherwise") require extraordinary evidence.
Edit: I just looked at that homeopathy thread one of you linked above and see Rothbard arguing against not just statins but chemotherapy and for God's sake *vaccines*! Anyone who would even think to say "allopathy is a joke" is someone that should be laughed out of this forum, not taken seriously. A "practicing homeopath" is a woo-woo idiot taking advantage of poor naive people. Either way, I'm done.
Why is this true? This is an appeal to authority: if my professors say it, then it must be true. Is it so hard to believe that bad ideas sometimes persist, supported (consciously or subconsciously) by financial motives? (<- here is your conspiracy theory)
What is this bullsh*t? Not once in any of my posts have I alluded to a "conspiracy". Stop putting words in my mouth. I don't believe in any conspiracies regarding medicine, apart from those that are already well accepted. Ie, that pharma will occasionally cover up negative research, something I think we're all familiar with.
Statins do work if you don't do anything else. There are, however, other options that can be pursued that render statins nearly useless. Detoxification, avoidance of pro-inflammatory foods, supplementation with antioxidants, stress reduction, etc. Doctors are not familiar with any of these and jump straight to statins.
ya! if you give statins you will automatically give someone diabetes. listen to this guy hes 101% correct
did you see the homeopathy thread? the guy has gone into more than 1 thread now and derailed based on statin bullcrap (and in that one, the argument was statins cause diabetes so we shouldnt use them for cholesterol control)
you can also be critical of someone's actions without being a presumptuous douche.... my issue with Roth has much more to do with the insistence on this topic and poorly supported and sometimes directly self-contradicting evidence which he uses to spread bad information. I think venting that in a little harmless sarcasm is passable
Fair enough
There was obviously some history here I didn't understand
It's true. The study you linked there is barely statistically non-significant, with a risk ratio of .91 but a 95% confidence interval of 0.83-1.01. It's too bad that PubMed doesn't have a way to see the list of studies that cited that one to see if there was any more recent followup that might have a higher statistical power to better suss out the real result.
It's also too bad that none of those many followups give you the exact opposite result in a much more comprehensive fashion. (to just pick two. the first link supports the lowering of all-cause mortality. The second supports the $/QALY I mentioned in my post above.)
I'm happy that my peers throughout the country are being taught to adequately evaluate evidence based medicine and not take the first thing they read to be gospel.
A number of studies have shown a causative link between statins and diabetes. This isn't really debatable, the only question is how this changes the risk:benefit analysis.
lol they are trying their darndest to salvage statin's rep. and a bigger lol @ the HYOOGE financial conflicts of interest involved with the key authors of both the papers you linked.
Ah, on the run right now so no time to give an in-depth comment. But to anyone whose interested in the various sides, this site might be helpful ~~> http://www.thennt.com/statins-for-heart-disease-prevention-without-prior-heart-disease/
(oh, and http://www.thennt.com/statins-for-acute-coronary-syndrome/ is a fun read as well)
We aren't really debating the usage of statins for primary prevention. I think it's very easy to say either way if they should be used for primary prevention.
I think we, well myself anyway, are arguing about its usage as a secondary event prophylaxis. The literature clearly says it helps after a primary event and Rothbard isn't buying it.
lol they are trying their darndest to salvage statin's rep. and a bigger lol @ the HYOOGE financial conflicts of interest involved with the key authors of both the papers you linked.
Ah, on the run right now so no time to give an in-depth comment. But to anyone whose interested in the various sides, this site might be helpful ~~> http://www.thennt.com/statins-for-heart-disease-prevention-without-prior-heart-disease/
(oh, and http://www.thennt.com/statins-for-acute-coronary-syndrome/ is a fun read as well)
Did you mean it's not very easy? My understanding has been that the evidence for primary prevention is much weaker than that for secondary prevention.
FDA issues warning on statin side effects today:
http://www.nytimes.com/2012/02/29/health/fda-warns-of-cholesterol-drugs-side-effects.html?_r=1
I spent a dozen posts explaining this to you in the other thread. The studies/analyses I linked to involved randomized interventions; "confounding factors" is not a valid criticism, since the two groups were presumably similar at baseline. Do you know what randomized means? I could just as well level the same criticism at any study that shows statins reduce cholesterol.
Are you an MS1 or 2? Have you taken any statistics classes?
My bad, I meant to say it's easy to spin it however you want it for primary prevention, meaning the evidence is as you say, somewhat shaky. I am not saying it's wrong for either stance, I am just saying you have evidence coming from both sides and it's hard to tell what is really going on. If you take all the research at face value, it appears statins have a large role in primary prevention. If you assume some kind of hidden agenda, then I guess you can say whatever you want.
It is pretty strong for secondary, however.
you are doing the EXACT same thing but don't seem to be aware of it. you forget that the point I have been debating is not some weak correlation, but YOUR assertion that statins should not be prescribed "except in the most extreme cases". (a point ive had to make multiple times.....) and you simply have not shown effective evidence of this.This post will be my last response to you, as I simply don't have the time to rehash simple concepts over and over.
It's funny how a study is either "barely statistically significant" or "barely statistically non-significant" depending on how much you (dis)like its conclusion.
see, this is the problem we had in the other thread..... you mix and match your points an again... I just think keeping along with this is a little beyond you. I shall break it down for youYea, like you said in the other thread, marathoners aren't going to come in for statin treatment. Like I said in the other thread, these points are not relevant, since we want to know the effect of statins on people with hypercholesterolemia, not people who run marathons!
Similarly, these trials cannot be used to judge the effect of statins on rabbits - who cares, we're not trying to treat rabbits!
This study would be useless if it looked at rabbits and marathoners, since we're not going to be giving them statins!
and here it is. you have made my point for me.Again - we're trying to treat neither rabbits nor skinny healthy people. Of course the effect will be more pronounced on people who are fatter and have more risk factors. That's ok, since these are the people we're trying to treat with statins!
The effect will be less on skinny/healthy people, but they will also benefit less from statins (skinny/healthy people don't have a lot of heart attacks for us to prevent)! (That's assuming we even give them statins, which we probably will not!)
the NNTs differ by a factor of 3, but hey maybe we should only accept treatments that have an offset impact of orders of magnitute...Of course, a valid criticism of any randomized trial. Why this suddenly becomes a focal point of studies you don't like, I'm not sure.
Watch me do the same thing with CVD: basically what these numbers are saying is "if you are already predisposed to CVD, administration of this drug which has a small chance of messing with your cholesterol metabolism may increase chance of messing with your cholesterol metabolism"
Uh, no kidding. The point is to quantify these effects. That's the point of EBM. The pro-diabetic effect is quite significant relative to the beneficial effect of statins. The NNT's are of similar magnitude.
What does it matter? Although some (most) on this forum will question my judgement and intelligence, it's obvious to anyone reading these threads that I understand the basic statistical concepts. It's obvious to me that you don't, regardless of how much "research" experience you have. I encourage you to revisit this thread after finishing up MS2, you will better understand some of the points I'm making.
The incidence of childhood type 1 diabetes increased worldwide in the closing decades of the 20th century, but the origins of this increase are poorly documented. A search through the early literature revealed a number of useful but neglected sources, particularly in Scandinavia. While these do not meet the exacting standards of more recent surveys, tentative conclusions can be drawn concerning long-term changes in the demography of the disease. Childhood type 1 diabetes was rare but well recognized before the introduction of insulin. Low incidence and prevalence rates were recorded in several countries over the period 19201950, and one carefully performed study showed no change in childhood incidence over the period 19251955. An almost simultaneous upturn was documented in several countries around the mid-century. The overall pattern since then is one of linear increase, with evidence of a plateau in some high-incidence populations and of a catch-up phenomenon in some low-incidence areas. Steep rises in the age-group under 5 years have been recorded recently.
If you just break it down to its most fundamental level--evolution--it just makes no sense that fat is the culprit in our diet. For hundreds of thousands of years we weren't eating pasta and bread, we were by and large eating meat. Think about all the problems we have today-almost EVERYONE has to have braces--why is that? It can't be normal, nature would NEVER select for crooked teeth. So what's going on? Why is Type 1 diabetes so prevalent? These questions are answerable. Anyway, I'll leave this alone for now, because a single paragraph is not going to convince anyone. This summer, though...
If you just break it down to its most fundamental level--evolution--it just makes no sense that fat is the culprit in our diet. For hundreds of thousands of years we weren't eating pasta and bread, we were by and large eating meat. Think about all the problems we have today-almost EVERYONE has to have braces--why is that? It can't be normal, nature would NEVER select for crooked teeth. So what's going on? Why is Type 1 diabetes so prevalent? These questions are answerable. Anyway, I'll leave this alone for now, because a single paragraph is not going to convince anyone. This summer, though...
"Nothing in biology makes sense except in the light of evolution."
Sugar, anyone?
http://diabetes.diabetesjournals.org/content/51/12/3353.full
The fact that SGLT inhibitors exist speaks to the size of the blinders we wear. There is a much, much more obvious solution.
in addition (and I think this is the more important part) we were never supposed to live this long in the first place. our life expectancies have doubled since then. For most of human existence you were lucky to hit 40. A good deal of our diseases are a result of modern medicine WORKING. The human body was simply not made to last this long but we said "F YOU MOTHERNATURE!" and decided to push it up towards 80. non-familial cancers are a good example of this. You just don't see cancers in wild animals. Typically they don't live long enough. Dogs are getting cancers now - likely a result of also living longer than normal. (this isnt including genetic cancers or anything really weird like the Tasmanian Devil's lack of alloimmunity causing STD cancer)
When you say "most of human history", you appear to mean "most of human history since the advent of agriculture", which was actually pretty recent on an evolutionary timescale. Either that, or you're talking out of your ass. The modal age of adult deaths for hunter gatherers is upwards of 65 years. <Source>.
When you say "most of human history", you appear to mean "most of human history since the advent of agriculture", which was actually pretty recent on an evolutionary timescale. Either that, or you're talking out of your ass. The modal age of adult deaths for hunter gatherers is upwards of 65 years. <Source>.
There is some variability among groups. Among traditional huntergatherers,
the average life expectancy at birth (e0) varies from 21 to 37 years,
the proportion surviving to age 45 varies between 26 percent and 43 percent,
and life expectancy at age 45 varies from 14 to 24 years (Figure 1; Table 2 and
Figure 3). Ache show higher infant and child survivorship than the other
groups, and Agta mortality is high at all ages. These patterns are verified in
the parameter estimates of the Siler model (Table 2). Initial immature mortality
(a1) for the Ache is about half that of other foragers, while for the Agta
it is two to three times greater.1
Forager-horticulturalists also vary significantly in infant mortality,
with a threefold difference between Neel and Weiss's Yanomamo sample
and the Tsimane. Survival to age 45 varies between 19 and 54 percent, and
those aged 45 live an average of 12–24 additional years. The Tsimane show
earlier accelerations in adult mortality than the Yanomamo and the forager
populations. The raw and simulated Gainj population shows earlier mortality
accelerations, although the raw data do not permit a strong inference about
ages greater than 55.
Acculturated foragers vary most in their likelihood of reaching age 45
(ranging from 26 percent among the peasant Agta population to about 67
percent among sedentary !Kung, Aborigines, and Ache), but show a range
of 13–27 additional years of life upon reaching age 45, similar to the range
for less acculturated foragers and forager-horticulturalists. Adult mortality
is also highly variable. For example, life expectancy at age 15 is 48 years for
Aborigines, 52 and 51 for settled Ache and !Kung, yet 31 and 36 for peasant
and transitional Agta. Hiwi show similarly low life expectancy. The acculturated
category shows a range of mortality experiences associated with
acculturation.
PDR