Thursday, April 29, 2010

A Different Model for Biomedical Risk and Innovation

One of the interesting things about the FDA as a government agency is that it largely seems to be trusted by Americans, and respected (if grudgingly) by the industry it regulates - possibly because its domain, medical science, is an area which requires non-fakeable technical expertise. Its "strange" respectability is highlighted in this book review.

J.S. Mill pointed out in On Liberty that medicine was a market ripe for failure, because most consumers of medicine are not in a position to evaluate its safety and efficacy. His observation presaged the problems that triggered the creation of the FDA (or its ancestor) in the early twentieth century: too many kids were dying from liver failure, brought on by the alcohol and ethylene glycol (antifreeze) that America's own witch doctors were using to sweeten their literal snake oil.

The drawbacks of having a central agency responsible for allowing the marketing of new drugs are several. First, like any agency, FDA is not immune to politics: for example, post-TGN-1412, scrutiny of any cytokine-interacting antibody increased to an almost paranoid degree (in corporatese this is known as a CYA). Perhaps more sinister on this count, it is often the case that a compound which receives marketing approval in its home market (where its developer is headquartered) does not receive it overseas (case in point, Paris-HQ'd Sanofi-Aventis and their weight-loss drug rimonabant, approved in Europe with a few side effects, and rejected in the U.S. for those same side effects. Coincidence?) Furthermore, all government agencies have limited resources, subject to the vagaries of central planning and economic swings. The decade began with an ominous trend in increasing approval times; this is the metric that individual biomedical companies care about. Much more alarming was the trend of decreasing numbers of new chemical or biological entities being submitted per year. This is the best index of overall biomedical innovation in a market and is affected not just by the agency but by the greater R&D environment of the industry - which of course, anticipates increasing conservatism in the agency that makes or breaks it, since you don't spend hundreds of millions chasing a compound that can't be legally marketed. Fortunately the NCE and NBE numbers are turning around; in 2009 there were 9 NCEs and 13 NBEs, compared to 1 NCE at one point in the mid-2000s.

It's important to point out that FDA approves drugs for a specific indication, not just for general sale, but that physicians are still allowed to prescribe them off-label. This creates strange pressures. First, the temptation for companies to actively market off-label is great. It's highly illegal, and highly lucrative (recent off-label marketing settlements in the last few years easily reach a half billion or more). More important is that this creates dangers for patients. Physicians have the authority to prescribe off-label at their discretion, and they often do, particularly with psychoactive drugs. While the companies that develop the drugs are obligated to produce general safety information, there are under no such obligations to produce safety information (much less efficacy) for off-label populations that physicians end up prescribing to, though they're stupid if they don't explore this as a potential new revenue source.

The point is this. By having an agency with such a structure - that approves drugs for specific indications - we create these pressures and these false senses of security (that off-label use is as well-characterized as the labeled indication). An agency that approved a drug only for safety, but not for efficacy, might be more beneficial to everyone. In other words, the FDA would require the company to label their drug as not harmful within certain dosing parameters, and contraindicated with certain other medicines. Since we're already trusting physicians to read NEJM and prescribe the drug on that basis, isn't this a far more efficient way to get drugs on the markets to patients who need it, without compromising safety? This discussion is a non-starter in the current administration but perhaps in a vigorous developing economy with a sense for social experimentation, we might see whether this would provide a greater good for a greater number; that is, increase innovation speed without increasing risk to patients. With ongoing drug research, overconservatism and the slowing of innovation is absolutely an ethical problem, because we can't forget the patients who haven't yet gotten sick.

Quiz: Which is a Better Indicator of China's Rise?

1) China's leap-frog to #3 voter at the World Bank, or 2) the huge increase I've seen in Chinese blog comment spam over the last six months? When comments are short, it's tough to tell the real ones apart from the Vile Offspring.

Sunday, April 25, 2010

China Understands Cultural Coordination Games

Coordination games occur not just with media and exchange formats but with culture. Language and values are subject to the principles of coordination games as well, and when equilibria shift in coordination games, they do so fast - no one wants to be stuck with all their videos on Betamax, and outcomes like PC vs Mac where more than one hangs on are rare.

So it's interesting to read about how the Chinese government clearly understands this and is funding Mandarin classes in the U.S. I know it's not just in Los Angeles because they're also funding classes in Eastern Pennsylvania.

It's a good idea to learn Mandarin (I plan to develop basic proficiency in the next few years) but I don't know what kinds of controls on course content there will be; since we have little Federal oversight of high school education in the U.S. and chronically broke schools, thinking as a cynical CCP official, this is an excellent Achilles heel. It will be interesting to see if social conservatives become less resistant to Federal school oversight as this educational effort becomes better-known.

Wednesday, April 14, 2010

Market Efficiency and Dating

Katja Grace has a great post at Meteuphoric called "How Does Information Affect Hook-ups", where she looks at the impact of online dating and the free up-front exchange of information about partners that it engenders, as well as the impacts thereof.

In a comment I argued that this was one example of how increased market efficiency has changed the romantic behavior of humans. Sometimes increased market efficiency is the result of information technology as in Katja's example, but it can also be the result of urbanization, as I argued previously.

In response to Katja's post, I argued that if we want to see the effect of efficient markets on dating, we didn't need to wait for online dating - single people in dense urban centers were and are exposed to many, many other potential partners over the course of a day, and even though they don't get the same up-front information that online dating allows, the effect is that people have a much better idea of the overall market (even if not necessarily an immediate read on the quality of the individual across the dinner table from them). In a little town in a rural area, you can't take individual dates too lightly, because how many single people in your league in your age group are there going to be out there? Contrast with Manhattan or Tokyo, where on every date you can tell yourself well yes, s/he is attractive and pleasant and interesting, but that guy/gal you just met at a professional mixer last night seems even better, and if neither of them work out there are still (literally!) a million other potentials out there. Given that dating is a usually required step before marriage, one would expect this is contributing to later marriage ages in dense urban centers, although there are confounding factors: a) urban centers in the developed world have large numbers of highly educated high-earning women; women often seek men with greater education or earning than themselves; therefore, they may hold out longer for this reason, and b) that education takes time, and people haven't even started the earning phase of their careers when they're 24, much less are they ready to get married. Comparing urban to rural marriage age while controlling for education and income would tease this out.

A further confounding factor is the partner-finding-process itself, which varies considerably across countries - hence the mention of Tokyo (arranged marriage is still more common in Japan than Westerners realize). Consequently it would also be interesting to compare arranged marriage rates in Tokyo to outlying areas of the country. A personal observation of Asian friends who've accepted an arranged partner is that they seem to view one of the biggest benefits of accepting an arranged partner as having been relieved of the task of the search. This theory's prediction is that in a large and efficient dating market, rationally optimizing singles should be less inclined to listen to bothersome parents who want to arrange a marriage with the down-the-street neighbors' nice but homely son or daughter from back home. (Also known as "Mom, are you actually serious?")

Notably, Katja's post is about hooking up, not dating/marriage. She states an apparent conundrum, that people want partners equal to or better than themselves, which leads us to wonder why people hook up at all. One answer is that people have different valuation criteria and they look for different qualities (otherwise very little exchange of goods and services in general would occur!) Hence, romantic partner's frequent "joking" that s/he got the better end of the deal in the relationship (one hopes the other partner is not so self-deprecating that they agree!) This argument extends to whether people are looking to hook up or to date seriously. In particular, people looking only to hook up might not be so concerned with having a higher quality partner. This is where your own anecdotal experience of dating in a big city may be helpful to understand the phenomenon: you might have had a relationship with a good-looking successful guy that you thought was going somewhere and was quickly ended by him, for no reason that you could figure out (reason: he was never serious and it was doomed from the start). Or, you might be a young guy pleased with yourself that you were able to get a really hot, smart professional woman (often a few years older) only to realize after a few nights together (and a few oblique comments about a recently departed ex) that she's not returning your calls anymore (I dub thee "transition man", and I share your pain or at least your ambivalent feelings about the situation). It is likely that these encounters would not occur if both partners were looking for the same level of commitment. Traditionally women are more likely than men to express interest in romantic relationships that go somewhere, rather than in flings, although the latter situation has become more common.

It's worth mentioning that in tolerant large cities there are also questions about same-gender hook-ups and relationships, but my comments are restricted to heterosexual pairings since as a straight male my experience and reading has been about that realm. The underlying assumptions of the dynamic (male vs. female reproductive strategies, dad vs. cad, short- versus long-term mating females, seeking genetic quality for future reproduction) may not apply or have very different effects in same-sex relationships, though these relationships may also provide a unique venue for testing these theories.

If we expect that access to information and market size affects dating and marriage, it should affect reproduction and gene frequency and distribution, which is what I was posting about before. I think that exactly this effect can already be observed to have worked more in some areas of the world than in others.

As a final speculation - because our romantic lives are far different than those of our paleolithic ancestors, and there are probably paleolithic-diet/mismatch hypothesis type arguments to be made about widespread relationship and family problems that we see in modernity; i.e. is divorce rate in industrialized countries the obesity and diabetes of modern relationships?

Monday, April 5, 2010

U.S. Life Span, Obesity, Elevation and Temperature

I had a conversation with a friend a few months back about the effect of cold temperatures on life expectancy; bottom line, she thought the colder the place you live, the longer you live. She theorized that this might have something to do with brown fat storage and/or thyroid function. I was skeptical, but curious.

Consequently I did a (very) little digging into questions of thyroid levels and brown fat and their impact on body mass index (BMI) and life expectancy. That adult humans even have brown fat at all was only accepted in the last few years, so there won't be brown fat maps floating around as yet. As for THR, TSH, or T3/T4 levels, I would guess that people living in cold climates would have higher T3/T4, at least seasonally (this is probably what drives the "blood thickening" that you lose when you move to Florida, for example). However after a brief search I wasn't able to find any solid studies relating thyroid levels to life expectancy and/or climate.

But we still have amateur epidemiology! Recall, the original discussion was about whether there is an effect of climate on obesity and/or life expectancy; let's not worry for now about how it might be mediated. (The following hyperlinks go to data sources.) I threw together some scatter plots comparing average U.S. state temperature and average U.S. state elevation to average state BMI and average state lifespan. I also used per capita income and % black population as a comparison for the effects of poverty. Instead of tarting up some boring scatter plots I'll just show the R-values:


RelationshipR-valueCorrelation
Obesity-Ave Temp0.47833Positive
Obesity-Elevation0.642028Negative
Obesity-PCI0.225389Negative
Obesity-% Black0.648228Positive


RelationshipR-valueCorrelation
Life Expect-Ave Temp0.631585Negative
Life Expect-Elevation0.292404Positive
Life Expect-PCI0.583952Positive
Life Expect-% Black0.724155Negative



So, what do we see here?

1) For both obesity and life expectancy, % black state population by state is a better predictor than PCI, average temp or altitude.

2) However, for obesity, % black population is just barely a better predictor than altitude. Low pO2 makes you skinny. No surprise there.

3) Interestingly, while altitude almost tied for best predictor of obesity, it is the weakest predictor here of life expectancy. People at altitude are a lot skinnier on average but don't live that much longer on average.

4) The situation is reversed for income. The richer a state, the less obese it is, although the relationship is weak. However, the richer a state, the longer-lived it is, with a substantially stronger relationship than with obesity.

5) There is a positive correlation between obesity and temperature, and a negative one with life expectancy and temperature. My friend would argue that this supports her position. However, people are not distributed evenly among states: Southern and South-central states (that both have a higher black population and are not as wealthy) make up 17 of the 20 warmest states, so it's difficult to tell what's going on, especially since those were better predictors anyway. A real study would look at economically and ethnically-matched individuals at least. While I'm ordering up studies from real epidemiologists to satisfy my curiosity, I'd still like to see average T3/T4 levels by average temperature and average January temperature.

Added later: from Marginal Revolution - I'd always been curious why obesity would suddenly become a problem in the second half of the twentieth century, when a lot of the production problems had made large volumes of calories cheap before. Turns out there's no mystery and it was already a problem a century ago.