Statistical pitfalls of personalized medicine
This is from an article by Stephen Senn in Nature. He keeps making this point — for the very good reason that people want to pretend there is no problem. But there is.
Personalized medicine aims to match individuals with the therapy that is best suited to them and their condition. Advocates proclaim the potential of this approach to improve treatment outcomes by pointing to statistics about how most drugs — for conditions ranging from arthritis to heartburn — do not work for most people. That might or might not be true, but the statistics are being misinterpreted. There is no reason to think that a drug that shows itself to be marginally effective in a general population is simply in want of an appropriate subpopulation in which it will perform spectacularly.
When you treat patients with chronic diseases such as psoriasis, it quickly becomes clear that there is considerable within person variation is response to treatments. We do not understand what this variation is due to. What we do know however, is that assuming variation in response between people at single time points may be misleading in that we have no measure of within person variance. This is only one of the problems. But hey, precision, personalised.. whatever: it shifts units (as Frank Zappa once said of Michael Jackson).