Pretty scary stuff, isn't it?
But are the ads true?
There was a big study of CHD (Coronary Heart Disease) AMI events (heart attacks or Acute Myocardial Infarction (AMI)) called INTERHEART. It followed some tens of thousands of cases and people over many years. The results identify risks associated with activities and tests.
Now this is where things become interesting.
The study identifies risk factors - now its very important to understand that a risk factor is not a predictor of something and not cause something. A prediction says that if I hold a hammer over my foot that it will hit my foot if I let go - I predict the result based on some information. A cause is different. For example, if I jump off the roof and break my leg the jump from the roof caused the broken leg (you can argue that the impact of my body on the ground and the fact that my leg took up all the force was really the cause, but at a macro level my leg broke because of the jump).
A risk factor merely represents the numerical chance something might happen based on examination of a large group. (Chance here is a number between zero and one, commonly shown as a percentage, i.e., .1 = 10%.) Sort of like saying 10% of the people at a baseball game buy hot dogs. We don't know which people will buy hot dogs but we can generally assume that for any given baseball game about 10% will buy hot dogs - everything else being equal (for example, there are no sales of hamburgers that day). This is why stadium vendors can buy just about the right amount of food so none is wasted and they don't run out.
In epidemiology risk factors are calculated as follows:
We take a statistically significant group of people (you can use common sense here - for something like heart disease you wouldn't study just five people - you'd study a large number). Just how large a number is not really important here, all we need to know is the number is large enough for statistical purposes.
We'll pretend in this post that 100 people are subjects in the study because math with 100 is relatively easy.
So let's say (we are making this up) that 20 people have AMI events of our 100 subjects. That's 20 / 100 = .20 = 20%. So we say that in general you have a 20% risk of an AMI event - based on our population (more on this in a bit).
Let's also say that 25 people in our example smoke (about like the percentage in the real world) and we'll pretend that 15 people in this smoking group have AMI events.
So the number of people that smoke and have an AMI event is 15, or 15 / 100 or .15 or 15% of the population.
If we divide the 15% (people who smoke and have an AMI event) by the 20% that just have an AMI event we get .75 or 75% risk factor that if I smoke I will have an AMI event.
Now, based on this, the billion (or trillion) dollar questions is this: Does our study show that smoking causes an AMI event?
The answer is clearly no. Our study does not determine the cause of anything. It merely multiplies some observed numbers together and computes something we call a risk factor.
And, in this case, was does that mean?
Actually nothing. I could now tell you, for example, that our 100 subjects all were born with serious congenital heart problems known to cause AMI events.
What would you think of my study example now?
What you are seeing is correlation. Correlation means, in this case, that when one thing happens there is an observed relationship with some other thing happening. A correlation is an observation.
Dogs make correlations: If I walk to the container holding the dog food they think I am going to feed them - so they stick close by. The dog mind predicts that I will feed them when I do this. But walking to the dog food container does not cause me to feed them. Similarly if I walk by the dog food container all the time and don't feed them the dogs will soon realize that their correlation is not useful and abandon it.
The INTERHEART study shows cholesterol is a risk factor in AMI events. (The ratio of HDL/LDL is used as well as another kind of cholesterol ratio - both provide about the same risk factor.)
Does this mean that cholesterol causes AMI events?
No, it does not. In fact, emphatically NO.
For all we know based on this study bad cholesterol ratios may also be a symptom of the same thing that actually causes AMI events.
And that's the problem.
Unfortunately, big pharma latches on to things like this study and makes the assumption that reducing the risk factor will make you healthier. Actually, they probably know its not true, but since making you think its true is not a crime...
That's why things like Lipitor make your good cholesterol go up and you bad cholesterol go down. The thinking is that reducing a risk factor for an AMI event makes your chance of having an AMI event smaller.
But that's nonsense because there is no causal relationship between the cholesterol ratios and AMI events.
And since there is no causal relationship its just what we might call "magical thinking" on your part, the part of your doctor, the part of big pharma. Magical thinking (according to the link) is "causal reasoning that looks for correlation between acts or utterances and certain events. In religion, folk religion and superstition, the correlation posited is between religious ritual, such as prayer, sacrifice or the observance of a taboo, and an expected benefit or recompense. "
Wikipedia associates magical thinking with witch doctors and voodoo - but isn't it apropo here?
So there you are. Taking a medication linked to a problem you probably don't already have. Linked by magical thinking, and magical thinking alone to a drug that makes them big money.
And to top it all off - things like Liptor has nasty side effects!
Now one imagines that the maker of Liptor does not like to see things on this list in general nor does it like to see a long list. So my guess is that the manufacturer worked very hard to remove everything that's on the list due to magical thinking on the part of the consumer taking the drug.
Sadly the list is too long to put into this post - look here to see it.
So, at least as far as I can see, there is a real cause and effect related to these side effects: If you don't take Lipitor you wouldn't report them - just like if I didn't jump off the roof I wouldn't have a broken leg.
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