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So oftentimes people use the phrases "personalized medicine" and "pharmacogenomics" interchangably, in the sense that "real" personalized medicine means finding out about your risks and predispositions early, then taking treatments personalized to your genetic profile. But that's only one aspect of how things might play out. Before turning to drugs, it's likely physicians will recommend lifestyle changes - exercise, diet, etc - to ward off possible risks. The question is: Do such behavior modifications actually work? And do they take?

The promise of personalized medicine - pharmacogenomics to predictive testing - is that when you tailor medicine to the individual, you have a much better chance of effective treatment. But there's an assumption built into that model: The "medicine" you deliver has to be legitimately effective. That's the lesson of this British study that looked into tailored treatments. The problem: these were herbal medicines, not pharmaceuticals. The catch is that the research was basically a meta-analysis, based on previous clinical trials of herbal medicines. There were only three such trials available, however, so the conclusion that trials of these particular medicines turned up no real positive effects isn't quite the same as saying that all herbal medicines are bunk.

Just saw this research from a few weeks back that claims the biggest thing on prescription bottles is the store's logo, not any useful piece of information. Makes sense, I suppose - they're the ones selling it. But it reminded me of one of my favorite design stories of the past couple years, the innovative prescription bottle created by Target (shown above).

I've written here before about MRSA, aka antibiotic resistant staph. So makes sense to link to this curious story from the LA Times about the USC football team taking on staph infections and winning. Seems the squad suffered through up to 19 cases of staph infections in 2002 and 2003, resulting in two hospitalizations (and they got away easy). So the team stopped sharing towels (eww) and started using alcohol-based hand sanitizers. It worked; no more cases since 2004. Â (via WSJ Health Blog)

So maybe the crowd (such as it is) can help me with this one. I've been racking my brain and scouring Google to come up with some good examples - hell, any examples - of pharmacogenomics in practice, right now. I mean, this is the supposed Holy Grail of personalized medicine - that drugs will be tailored to our genomes - and there has been a good 20 years research. But I can only find two examples: Herceptin, which is used in breast cancer patients whose cancer is caused by excessive protein from the HER2 gene; and warfarin, a blood-thinning drug used for patients recovering from heart attack or major surgery - there's now a screening test for those with certain gene that causes excess bleeding, raising the possibility of serious side effects (stroke, etc). But really, that's it? I mean it's 2007, and this is the big payoff of personalized medicine, which we've been hearing about for a decade - two lousy drugs?

OK, that headline is an exaggeration, but one of the most stunning statistics I've gleaned in the past couple years is that when you put together all the known causes of coronary artery disease - high cholesterol, stress, high blood pressure - you account for something like half of all cases. That's it. In other words, for fully half of all cases of heart disease, we have no idea what the cause is (this comes from UC Berkeley's Len Syme; I'm trying to track down the specific stat he used. If you know, please tell me).

The new issue of Wired has an essay I wrote on a topic I've been mulling for a few months: liberating what I call "dark data" in science, the unpublished, inconclusive, or inconvenient results that too many researchers would rather stick in a drawer than put into the light so that others may learn from their work (and perhaps build on it). Here's the gist:

One of the most egregious injuries to public health of the 20th century - one that could've largely been avoided - was the widespread use of asbestos in industry, manufacturing, and construction. Though a great insulator and flame-retardant, the microscopic asbestos fibers also wreak havoc when inhaled - causing all sorts of lung complications, the worst being "mesothelioma", the cancer caused by asbestos exposure. Even after the first cases of "asbestos lung" became well known (the first court case was in 1929), it was still kept in widespread use.

I love this story: a survey says that even the threat of death won't get a majority of Britons to exercise and maintain their health. Just "38% of people questioned by YouGov said they would do more exercise if their life depended on it," according to the BBC story. Says Mike Knapton, director of prevention and care at the British Heart Foundation: "For many people, exercise has become an ugly word, something to avoid at all costs." Wow. And people call Americans lazy. Reminds me of Idiocracy, the 1/3 great movie by Mike Judge that, tragically, nobody saw.

Yesterday morning I had one of those experiences journalists dread: I opened up the Sunday New York Times and there on the front page of the Times Magazine was a story I've been kicking around. Titled "Do We Really Know What Makes Us Healthy?", the story by Gary Taubes is a thorough look at how so much scientific research in the name of public health gives us dodgy, even incorrect, results. Told through the vehicle of hormone replacement therapy, Taubes' story is really a discerning look at the purpose and limits of epidemiology - which is our best way of establishing what sort of behaviors and interventions might be good for us, and which might be bad. One thing I was expecting Taubes to mention was the killer study by John Ioannidis in the August 2005 issue of PLoS Medicine: "Why Most Published Research Findings Are False". This erudite bit of statistical analysis pointed out that one-off results are often wrong - in fact, are more likely to be false than true. One of the most downloaded papers PLoS has put out, it's the sort of clear, counter-intuitive and declarative paper that I wish was characteristic of more scientific research. I expect Taubes didn't get into it because it's full of talk of positive-predictive-vaules and power and bias. But still, if I had written the story - which I swear I had a version of on my to-do list - Ioannidis would've been on the source list.