Bryan Caplan at George Mason University and the Library of Economics and Liberty has a couple of posts on medical screening and treatment.
First, Caplan shares data on prostate cancer. It turns out that screening does nothing good for the patient:
That’s right. Statistically speaking, prostate cancer screening is worthless. Over the course of ten years, 1-in-100 men dies of prostate cancer regardless of screening. 20-in-100 die for any reason, regardless of screening. The only difference: 2-in-100 screened men – and screened men alone – endure hellish treatments, and another 18-in-100 endure milder torments and a false alarm.
Actually, as he points out, the treatments, besides being extraordinarily uncomfortable and inconvenient are worthless:
Gigerenzer actually understates his case. Since 1-in-100 die of prostate cancer either way, we have to conclude that either (a) positive biopsies don’t lead to treatment, or (b) the treatments do not, on average, work. Since (a) is clearly wrong, (b) is the logical inference. If you have terminal prostate cancer, modern medicine won’t help you. It will however still hurt you during treatment, and quite possibly make you incontinent and/or impotent for your remaining years.
Then, Caplan looks at breast cancer screening and treatment.
At first glance, screenings save the life of one women in a thousand. On closer look, however, screenings only alter the kind of cancer that kills you, not overall cancer mortality. Whether they’re screened or not, 21-in-1000 women died of cancer within ten years.
As with prostate cancer, breast cancer treatment doesn’t seem to alter life expectancy:
Furthermore, since diagnosis typically leads to treatment, the fact that more-diagnosed women don’t live longer is striking evidence that breast cancer treatments are, on average, ineffective. Hansonian medical skepticism may be overstated, but it is firmly grounded in fact.
This is another example of our society’s extreme risk aversion, a result of excessive concern for Type I errors and lack of interest in Type II errors. See yesterday’s post for a discussion of Type I and II errors.
I don’t believe there is a doctor in America that would tell her patients that she is no longer screening for breast cancer because it doesn’t change life expectancy. If she did, she would be punished. She may be sued. She may lose her licence. Most likely, social media would chase her into hiding within 24 hours of a Twitter post revealing her refusal to screen.
If screening results in a positive, failure to treat will result in similar punishment. By contrast, doctors are not punished for false positives or ineffective treatments, as long as they follow standard protocols.
Yesterday’s flourishing post was about the lack of innovation that comes from the excessive risk aversion that results from myopic attention to Type I errors. Today’s post is about the costs of excessive risk aversion and insufficient appreciation of Type II errors. It’s clear that society loses in many ways. We need to get some balance.