Map of life expectancy at birth from Global Education Project.

Wednesday, December 22, 2004

Pills, damn pills, and statistics

It's been a rough few months for the pharmaceutical industry, what with news about antidepressants increasing the risk of suicidal thoughts and behavior in children, so-called "hormone replacement therapy" and various nasty consequences, most recently news about Cox 2 inhibitors and cardiovascular disease, and now NSAIDs, plus some less publicized problems.

It's also been a rough patch for the people who were taking these drugs, obviously, and now a lot of folks out there are confused and don't know what the heck to do.

At the heart of these problems we have a tangled intersection of epistemology (the theory of knowledge - how we come to believe what we think we know [redundancy intended]), difficult value judgments, politics and yes, industry greed. The latter is to be expected, of course, but the epistemological thicket and the values fog make it difficult to properly contain.

Which thread to pull first in this skein? I pick the field called biostatistics. Medical practice and applied biomedical research depend very much on the language of probability, which is called risk when we care about what happens. But the so-called positivist epistemology which underlies the scientific approach to knowledge has a very hard time with probability. It is not clear in what sense statements about probabilities are verifiable. The blow dried guy comes on TV and tells us that there is a 50% chance of rain tomorrow. Tomorrow comes, and it rains or it doesn't rain. Guess what? He was right!

I tell you that you have a .5% (that's .005 out of 1) chance of having a heart attack in the next year, but if you start taking this pill your chance will be .75%. But that's not actually true any more if we learn more about you. For example, if we test your Low Density Lipoprotein ("bad" cholesterol) and find that it's below a certain number, your risk is less to begin with and is increased even less if you take the pill. Was I wrong when I gave you the figures of .5% and .75%? No, those are the odds when we don't know about the cholesterol, so I was right. And no matter what happens next year, whether you have a heart attack or not, I was still right. And what if I give this news to, say, 100 people? In order for me to be "right," does 1/2 of a person need to have a heart attack? No, I could still be right if nobody has a heart attack, or even if 10 people do, although I would then say that the outcome which ensued was an "unlikely" one. Well, it isn't unlikely any more, it happened! The probability of events which have actually occured is 1, 100%, no matter how unlikely they were before they occurrred.

What if I tell you that the pill increases your risk of attack by 50%. Does that sound scary? It probably isn't worth it. What if I tell you it increases your risk by only .25%, in other words that 2.5 people out of 1,000 will suffer a heart attack because of taking this pill. Maybe you'll take a chance now. But both of those statements are true -- in some sense, but neither of them may be true for you! In the end, you're either going to have a heart attack or you aren't, right?


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