Let's say you've gone to your doctor for your annual check-up. The Dr. comes in and tells you that he sees something in your bloodwork that is troubling to him, and he'd like to put you on a drug. At this point the vast majority of people will just take the drug, but a few may question the Dr. more, as they should. Let's just assume you are one of those people, and the conversation carries on.
"Well, I'm a little concerned about your bloodwork. You have an elevated risk for cardiovascular disease, I'd like to put you on one of 2 drugs. The first one will reduce your future risk of death from cardiovascular disease by 30%, and the second will only prevent death for 1 out of 30 people."
As the shock sets in, you begin to think about the prospects of having to take a drug for the rest of your life. Of course, cardiovascular disease has always been on your mind. Your father had a heart attack at 55. You've done your best to get regular exercise and eat a healthy diet, and at 45 years of age feel 10 years younger. Despite feeling well and never having had a heart attack, you decide it's likely in your best interest to take a drug.
Which drug would you take? Assuming that you are generally good at math, most people would choose the first one. The problem is, the first and the second drug are the same drug. Of course clinical research studies often have different outcomes depending on how they are designed, but this data is not only for the same drug it's from the same study, I just worded the outcome differently(1). This illustrates an important point; when research results are worded in a way that inflates the results, people are more likely to take a drug.
When you look at the "30% decreased risk", that is something termed
relative risk. This is used often despite the fact that it presents the
data in a deceptive way that makes you more likely to take the drug. Let's say you perform a study with 100 people
in the treatment group and 100 people in the placebo group. Of the
people who received the treatment only 1 person died, while in the group
not receiving the treatment 2 people died. This would seem to be a
very small effect since the absolute difference is only 1. However,
stated in relative risk terms, the treatment reduced the risk of death
by 50%. This is where numbers like the number needed to treat(NNT) come
in handy. In this fake study, the NNT is 100. In other words, you
need to treat 100 people with the drug to prevent one death, the other 99 who are
taking it will not live any longer with or without the drug. Yay!
This is problematic for many reasons, not the least of which being that most pharmaceutical drugs have a laundry list of side effects that could affect the 29 out of 30 people not experiencing a benefit from the drug. For statins, this means an increased risk of neurological problems, muscle pain, an increased risk for Type 2 diabetes, liver damage, and more. Another reason this is problematic is that they have recently revised the guidelines for prescribing statin drugs which would increase the number of people eligible to take the drugs to 56 million. This would potentially prevent 1.87 million deaths over the course of 5-6 years, while 54.13 million would be taking the drug with no benefit from a mortality standpoint. The interesting part is that these numbers are for people who have had a previous heart attack, if you've never had a heart attack, the picture is worse.
For primary prevention, the NNT is a lot worse. Primary prevention essentially means using statins to prevent a heart attack or stroke in someone who has never had one before. The NNT in these people is 1 in 60 to prevent a heart attack and 1 in 268 to prevent a stroke. Side effects, on the other hand were seen in 1 in 50 people(Type 2 diabetes) or 1 in 10(muscle damage)(2). The NNT to prevent 1 death from cardiovascular disease in primary prevention trials fluctuates but is typically around 1 in 120. Taken together, this means that in 600 people you would prevent 10 heart attacks and prevent 5 deaths, while
creating 12 new cases of diabetes, which increases your risk for a heart
attack. In fact, people with Type 2 diabetes have the same risk of experiencing a heart attack as someone who has had a heart attack before and are twice as likely to die from a heart attack than non-diabetics(3). So, of the 600 people who took the drug, 10 will prevent a heart attack and 12 will substantially increase their risk for one. Does that sound like something you would sign up for?
When you look at the data this way, it makes the decision on whether or not to take something like a statin a lot more difficult. I can't tell a person whether or not they should take a drug, that's between that person and their doctor. Looking at the total picture from a numbers standpoint makes the decision a lot more difficult than, "You're the DR, whatever you say". On top of the numbers issue, they are finding new therapeutic effects from these drugs every day and so many of the results conflict with one another. Recent evidence has shown that statins may be protective against cancer when taken for 4 years(4), but they may also double a woman's risk of breast cancer when taken for over 10 years(5).
While many of the researchers who come to positive findings on these drugs hail them, one has to wonder how they know the drugs are totally safe when they are finding new ways to use them every day. If you are looking for therapeutic uses for a drug and are just now finding new ones, how can you get a complete handle on the total range of side effects when they are more of an afterthought and may not pop up until 10 years down the road? The point of this is not to prevent you from taking pharmaceutical drugs, the point is that you should ask more questions, research these drugs, and weigh the pros and cons before you decide that's the route you're going to take. Just for the sake of comparison, 300 minutes of exercise per week for the use of primary prevention of heart disease can reduce your risk by 20%(6) and regular exercise for secondary prevention can reduce the risk of death from heart disease by 27%(7).
