Nov 21 2011
Every so often, I come across studies that leave me scratching my head. Sometimes, these studies are legitimate scientific studies that have huge flaws or come from an assumption that is very off-base. Other times, they involve what Harriet Hall has termed “tooth fairy science,” wherein the tools of science are used to study a phenomenon that is fantastical, whose very existence hasn’t been demonstrated. Many such studies, not surprisingly, are studies of “complementary and alternative medicine” (CAM) or “integrative medicine” (IM). Modalities like reiki (which is faith healing that substitutes Eastern mysticism for Christian beliefs) and homeopathy (which is, when you boil it down to its essence, sympathetic magic) fall into the category of therapeutic modalities that are based on fantasy but are studied as with the latest tools of science, producing no end to confusing noise. This “tooth fairy science” has, over the last few years, reached its epitome in the application of the latest genomics technology to, in essence, magic, and I’ve recently come across an incredible example of just such a thing. But, first, let’s take a step back to what is going on in medical science now before I introduce a concept that I’ve dubbed “woo-omics.”
A prelude to woo-omics: Genomics, proteomics, everywhere an “omics”
One of the most difficult problems in science-based medicine is how to do a better job identifying which patients will respond to which treatments. Clinical trials, by their very design, have to look at average responses in populations. In essence, a treatment is compared to either placebo or standard-of-care, a choice mainly driven by ethics and whether effective treatments exist for the condition being studied. It is then determined using statistics whether a significant difference exists between the two groups. The difficulty, as any clinician knows, is applying the results of clinical trials to individual patients. In any population, there is, after all, a range of responses to any drug or treatment, and it would be desirable to be able to predict which patients will fall at the end of the bell-shaped curve where the treatment is most effective and which will fall at the end of the curve where the treatment works poorly or not at all.
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