- The shame of college sports. Great article by Taylor Branch.
- Retraction watch
- protein folding problem solved by on-line gamers
- Edward Jay Epstein review of two books about the 2001 anthrax attacks
Thanks to Dave Lull and Justin Owings.
First, Let Them Get Sick
In Cities and the Wealth of Nations, Jane Jacobs tells how, in the 1920s, one of her aunts moved to an isolated North Carolina village to, among other things, have a church built. The aunt suggested to the villagers that the church be built out of the large stones in a nearby river. The villagers scoffed: Impossible. They had not just forgotten how to build with stone, they had forgotten it was possible.
A similar forgetting has taken place among influential Western intellectuals — the people whose words you read every day. Recently I wrote about why health care is so expensive. One reason is that the central principle of our health care is not the meaningless advertising slogan promoted by doctors (“first, do no harm”) but rather the entirely nasty first, let them get sick. Let people get sick. Then we (doctors, etc.) can make money from them. This is actually how the system works.
It is no surprise that doctors and others within the health care system take the first, let them get sick approach. It is wholly in their self-interest. It is how they get paid. If nobody got Disease X, specialists in Disease X would go out of business. What is interesting is that outsiders take the first, let them get sick attitude for granted. It is not at all in their self-interest, just as it was not at all in the self-interest of the Carolina villagers to think building with stones impossible.
An example of an outsider taking first, let them get sick for granted is a recent article in the London Review of Books by John Meeks, an excellent writer (except for this blind spot). The article is about the commercialization of the National Health System. Much of it is about hip replacements. How modern hip replacements were invented. Their inventor, John Charnley. How a hospital that specialized in hip replacements (the Cheshire and Merseyside NHS Treatment Centre) went out of business. And so on. Nothing, not one word, is said about the possibility of prevention. About figuring out why people come to need hip replacements and how they might change their lives so that they don’t. Sure, a surgeon (John Charnley) is unlikely to think or say or do anything about prevention. That’s not his job. But John Meeks, the author of the article, is outside the system. He is perfectly capable of grasping the possibility of prevention and the parasitic nature of a system that ignores it. Long ago, people understood that prevention was possible. As Weston Price documents, for example, isolated Swiss villagers knew they needed small amounts of seafood to stay healthy. But Meeks — and those whom he listens to and reads — have forgotten.
How to Start a Talk
A recent talk at the London School of Economics by Carne Ross, author of a book called The Leaderless Revolution: How ordinary people will take power and change politics in the 21st century, began with this:
I was preparing the talk this afternoon at my beloved cousin’s, where I’m staying. ’cause I don’t live in London anymore. She said, “How are you, Carne, how are you doing?” I said, “I’m a bit nervous, to be honest.” She said, “Don’t worry, Carne, I’ve heard lots of bad talks at the LSE.”
Why is Health Care So Expensive?
Because health care costs have been increasing faster than other costs for a long time. Everyone knows that. But why is that happening? Not so clear. This excellent article (via Marginal Revolution) says that health care is not subject to the same pressures as industries where costs have come down. Off-shore manufacturing is one such pressure. For example, a cell phone used in California can easily be made in China. In contrast, the health care a person in California is likely to want (e.g., X-rays, check-ups) must be supplied locally.
Let me suggest other reasons:
1. A large fraction of medical school professors are co-opted by industry. They get lots of money from health care companies. The companies have no interest in cutting costs. They fund research by medical school professors for exactly one reason: to sell more product.
2. The average medical school professor has little idea how to do research. Recently I mentioned a study in which they threw away half of their data. An article about the Potti scandal revealed that Potti’s main co-author, Dr. Nevins, essentially confessed he didn’t understand the research in the papers he had co-authored with Potti. As far as I can tell, medical school professors usually know so little statistics they cannot analyze the data from the studies they do. If you don’t understand how to do research, innovation will be difficult.
But I think the bigger and less obvious reasons are these:
3. The health-care supply chain is long. Some medical school professors can innovate — Peter Provonost, for example. But they face a special problem: the enormous health-care supply chain. It includes doctors, nurses, hospital workers, drug company employees, health insurance employees, medical equipment manufacturers, alternative medicine practitioners, psychotherapists, X-ray techs, health food store employees, and on and on. No other industry is like this. No one in the supply chain can innovate, yet all of them can block innovation. Everyone in the health-care supply chain must be paid. They care enormously about being paid. They hate to take a pay cut. Any innovation — unless it increases the cost of health care — threatens their paycheck. So there is a huge bias in favor of change that increases cost and a huge bias against change that decreases costs.
4. Let them get sick. If a man is not afraid, you cannot sell him protection. This is why protection rackets have two parts: (a) threat followed by (b) offer of (expensive) protection. Modern health care workers understand a similar truth: If a person is not sick, you cannot sell him (expensive) health care. Modern health care workers do not actively make people sick, they let a dysfunctional research system do that. (E.g., cluelessness about how to stimulate the immune system.) Then they pounce — and the money starts to flow. Once the money starts flowing, political power builds up. In a sane world, schools of public health, which care about prevention, would receive vastly more money than medical schools, which ignore prevention. In fact, the opposite is true.
This is why personal science will be so important: It is a way around our massively-dysfunctional health-care system — dysfunctional, that is, for everyone outside it.
Assorted Links
- Jason Epstein on Jane Jacobs. He edited most of her books.
- How former Emory psychiatrist Charles “Disgraced” Nemeroff found a home at the University of Miami. A comment on the article put it well: “I am even more concerned as to the scientific truth and validity of the studies, drugs, treatments etc they [= Nemeroff and his supporters] have been involved in.” At the same time her university was hiring Nemeroff, the president of the University, Donna Shalala, sent out a letter boasting how the University of Miami was increasing the “integrity” of their medical school by improving policies related to conflicts of interest! “There is no room for compromise in this area,” wrote Shalala.
- More about Jane Jacobs
Thanks to Dave Lull, Paul Sas and Alex Chernavsky.
Assorted Links
- A medical device expected to reduce strokes turns out to make them three times more likely. Revealing how well stroke researchers understand strokes.
- skin cancer diminished with marijuana oil
- why might current climate models — the ones supporting Anthropogenic Global Warming — be way off? Cosmic rays.
Thanks to Peter Spero and Alex Chernavsky.
Great TV: Downton Abbey, Switched At Birth, Suits
Everyone knows Mad Men, The Good Wife, and Glee – especially Mad Men — are great TV. If you read about TV, you have read about them — especially Mad Men — endlessly. Not everyone knows that Downton Abbey (second season trailer), Switched At Birth, and Suits are also great TV.
Downton Abbey is great because Julian Fellowes, who also wrote Snobs and Gosford Park, is a great writer. The plot is good, the details are good. I’d read or watch anything he does. (After I wrote this post I came across this interview with Fellowes — apparently the NY Times saw the same gap in coverage as I did.)
Switched At Birth is great because to a perfectly good idea for a TV show (two girls are switched at birth, a fact discovered when they are teenagers) was added — by management, not the originators of the show — an excellent idea: one of the girls is deaf. This adds an attractive layer of complexity and novelty (deaf teenage life).
Suits appears formulaic: lawyer show, buddy show, cartoon villain, romantic plot connecting the episodes, every episode, the good guys win cleverly. But perhaps the formula, whatever it is, is really well-executed because I enjoy every episode and don’t feel dirty afterwards.
Acupuncture Critic Misses Big Points
Recently the Guardian ran an article by David Colquhoun, a professor of pharmacology at University College London, complaining about peer review. His complaints were innocuous; what was interesting was his example. How bad is peer review? he said . Look what gets published! He pointed to a study of the efficacy of acupuncture and included graphs of the results. “It’s obvious at a glance that acupuncture has at best a tiny and erratic effect on any of the outcomes that were measured,” he wrote.
Except it wasn’t. There were four graphs. Each had two lines — one labelled “acupuncture,” the other labelled “control”. You might think to assess the effect of acupuncture you compare the two lines. That wasn’t true. The labels were misleading. The “acupuncture” group got acupuncture early in the experiment; the “control” group got acupuncture late in the experiment. Better names would have been early treatment and late treatment. You could not allow for this “at a glance”. It was too complicated. With this design, if acupuncture were effective the difference between the two lines should be “erratic”.
The paper’s data analysis is poor. To judge the efficacy of acupuncture, their main comparison used only the data from the first 26 weeks. They could have used data from all 52 weeks. That is, they ignored half of their data when trying to answer their main question. Colquhoun could have criticized that, but he didn’t.
Colquhoun’s criticism was so harsh and shallow, apparently he is biased against acupuncture. But there are two big things few pharmacology professors appear to know. One is how to stimulate the immune system. This should be central in pharmacology, but it isn’t. Half of why I think fermented foods are so important is that I think they stimulate the immune system. (The other half is they improve digestion.) There are plenty of less common ways to do this. The phenomenon of hormesis suggests that small doses of all sorts of poisons, including radiation, stimulate repair systems. The evidence behind the hygiene hypothesis suggests that dirt improves the immune systems of children. Bee stings have been used to treat arthritis. And so on. In this context, sticking needles into someone, which puts a small amount of bacteria into their blood, is not absurd. Acupuncture also allowed patients to share their symptoms, the value of which Jon Cousins has emphasized.
The other big thing Colquhoun doesn’t seem to know is the absurdity of the chemical imbalance theory of depression. Speaking of ridiculous, that’s ridiculous. Which plays a larger role in modern medicine — antidepressants or acupuncture? If you want criticize peer review, criticize the chemical imbalance theory. It is as if peer reviewers have been saying, yes, the earth really is flat for fifty years. Perhaps this is ending. During a talk that Robert Whitaker gave at the Massachusetts General Hospital in January, he was told by doctors there that the chemical-imbalance theory was an “outdated model”.
Thanks to Dave Lull and Gary Wolf.
Anil Potti, Ranjit Chandra, and Reducing Scientific Fraud
An account of the genomics scandal at Duke University has appeared in Significance (a journal sponsored by British and American statistical societies). The scandal caused the end of a clinical trial — it had been based on fraudulent data — and the resignation of assistant professor Anil Potti, who had among other things falsified his resume.
It reminded me of the Ranjit Chandra case. Similarities: 1. The published results could not be reconstructed from data. In Chandra’s case, some of the results were statistically impossible. In the Potti case, two statisticians were unable to go from raw data they were given to the published results. 2. Outsiders important. Saul Sternberg and I, who are psychology professors, not nutrition professors, wrote an article that drew attention to what Chandra had done and caused retraction of one of his papers. As far as I could tell, at least a few nutrition professors had believed for many years that Chandra made up data. In Potti’s case, the deception was revealed by two statisticians. Perhaps Chandra and Potti both believed (a) hardly anyone will notice and (b) if anyone notices, they won’t do anything. 3. Incidental fabrication. In one paper, Chandra said that everyone asked to be in the study agreed to participate. The study involved having blood drawn many times. Potti claimed to be something similar to a Rhodes Scholar. 4. Found innocent. Years before Sternberg and I got involved, Chandra had been accused by his research assistant, a nurse. A Memorial University committee found him innocent of her accusations — at least, her accusations were not upheld. Chandra then sued the nurse. In the Potti case, a Duke University committee looked into the case and found no serious wrongdoing. A clinical trial based on the Potti results, which had been stopped, was resumed.
Factor 2 (outsiders important) is no surprise to readers of this blog, although the new account doesn’t mention it. But Factors 1 (reconstruction impossible) and 3 (incidental fabrication) mean that the fabrication should have been relatively easy to confirm. Yet Factor 4 seems to suggest it was hard to confirm. Factor 4 — in spite of Factors 1 and 3 — implies there is something mysterious and important going on here, more mysterious and interesting than someone lying. But I cannot say what.
The Significance article, which is by Darrel Ince, a professor of computing at the Open University, includes several suggestions for improving the system. I fail to see why they will help and they have significant costs. One of them is to put the original data and software in an independent repository. I think this would make things worse. People would continue to fake research; now. they would now also fake raw data, in addition to the graphs and tables needed for publication. In the past, thinking they wouldn’t be caught, fakers would either (a) not make up the raw data (Chandra) or (b) do so carelessly (Potti). Their overconfidence was key to catching them.
My suggestion along these lines is a requirement that researchers make available upon request the raw data and any original software. They store it themselves, in other words. If they fail to fulfill outside requests for these materials within one month, this will be grounds for immediate retraction of the paper. Without something like this, a store-it-yourself requirement means little. I once requested the raw data for a paper that had appeared in a journal that had a make-data-available policy. The authors refused my request. The editor did nothing. As A. W. Montford makes clear in The Hockey Stick Illusion, we would all be better off if Michael Mann and other authors had simply handed over the raw data behind their “hockey stick” temperature graphs when requested rather than fight a long string of FOIA battles (and mull over what emails to delete).
Poor Replication Rate in Psychiatric Genetics Research
With the ability to measure individual genes has come interest in learning what they do. Perhaps Person X is depressed and Person Y is not depressed because Person X’s genes differ from Person Y’s. A whole generation of psychiatry researchers now believes this is plausible. There are “general reasons to expect that GxEs [gene by environment interactions] are common,” says a new review paper in the American Journal of Psychiatry. By “common” they mean large enough and common enough to do research about.
I don’t agree with this conclusion. Sure, twin studies show that genes matter for psychiatric diagnoses. Identical twins are more likely to be concordant (= have the same diagnosis) than fraternal twins, for example. But this is a very long way from indicating that single genes matter. Twins results are entirely consistent with the possibility that a large number of genes each matter a little. If this is true — and I find it far more plausible, when it comes to psychiatry, than the single-gene idea — then searching for one gene that does this or that is a waste of time. Individual genes are too weak. To do psychiatric gene research you have to dismiss or ignore the many-tiny-effects possibility, because if true it would mean what you are doing is bound to fail. The new review paper I mentioned ignores it.
The new review paper surveys all of the research papers about GxEs during the first decade of research (2000-2009) in this area — about 100 papers. It asks (a) if initial findings have been repeatable and (b) how much we should trust the repetition attempts. To answer the first question, they found that only a third (10 of 37) of initial findings were repeated when tested a second time. If things were working well, all of the initial findings would have been repeatable. The low replication rate doesn’t mean that two-thirds of the initial findings were false. Perhaps the replication attempts were poorly done and all of the initial findings would have held up if they were better done (e.g., larger samples). Or perhaps the replication attempts were biased toward positive results and none of the initial findings would have held up if they were better done.
The review paper also found that positive replication attempts had much smaller samples (median sample size about 150) than negative replication attempts (median sample size about 380). This suggests that the negative replication attempts are more trustworthy than the positive ones. The true replication rate is probably lower than one-third.
The findings, in other words, support my initial belief that the whole field is a waste of time. Amusingly, the authors of the review (one at Harvard, the other at the University of Colorado) conclude the opposite. Here’s what they say:
This review should not be taken as a call for skepticism about the G×E field in psychiatry. . . . True progress in understanding G×Es in psychiatry requires investigators, reviewers, and editors to agree on standards that will increase certainty in reported results. By doing so, the second decade of G×E research in psychiatry can live up to the promises made by the first.
Of course their findings support skepticism about GxE research. This isn’t slanting your conclusions to be more convenient, this is bending them backwards. And failure to mention the many-tiny-effects possibility, a plausible explanation for all the results they describe, is another sign that this area of research is not to be trusted.