With this history, I find the new book SuperFreakonomics fascinating. I was reading the chapter yesterday about large statistical analysis of the efficacy of medical treatment and thought how timely given this week's announcements of proposed changes to the screening for breast cancer and cervical cancer. It made sense to me that if the risk of harm from false positives in ages 40-50 outweighs numerically the likelihood of finding true positives, as a society we may be better off not screening women from ages 40-50. As Karen Kaplan wrote yesterday in the LA Times:
After decades of focus on the upside of cancer screening, public health experts are increasingly reevaluating the wisdom of administering routine cancer screening tests to millions of asymptomatic people.
Though screening certainly saves lives, recent studies make it clear that it also leads to biopsies, surgeries, chemotherapy and radiation -- even some deaths -- that otherwise would not have occurred.
That screening has a downside is not easy to accept, as evidenced by the furor over this week's recommendation from the U.S. Preventive Services Task Force that most women wait until age 50 to start routine mammograms, and then get them only every other year.
One of the reasons people are in an uproar over the proposed changes is the notion that we should be able to control our health by proactive measures such as visits to doctors and screening tests. But again, SuperFreakonomics' analysis of data involving doctor strikes show that death rates are negatively correlated with doctor visits, i.e. the death rates went down when the doctors were on strike.
And another reason for uproar is the notion that decisions about healthcare would be made taking into account the good for all as opposed the good for each individual. Interestingly, I do not have a problem with using this rationale to limit screenings for otherwise asymptomatic people. I do however get the chills, as I did last night, when the rationale is extended to providing chemotherapy to stage 4 cancer victims. SuperFreakonomics argues that the numbers show that outcomes for such cancer patients on average are not positive but the cost is astronomical. They report that a treatment for non-small cell lung cancer costs $40,000 but only extends survival by two months on average. Should society bear the cost of this treatment if it does not change length of survival in any significant amount?
My very close friend was diagnosed with stage 4 lung cancer in early January 2008. The average survival time after such a diagnosis is 8 months. My friend has beaten that average and then some. In the past two years she has had, she told me at lunch the other day, seven protocol of chemotherapy and her last scan showed shrinkage of the tumors. Every additional month she has lived over the average expectancy is a blessing to her family and friends, like me. Every day that we get to be in her presence is special. She has pain but it appears to be manageable. She is now in a wheelchair all the time due to the tumors' effect on her left leg and the possibility that it has destroyed bone in other places. She needs to be hypervigilant about getting sick. But she still is able to go out to restaurants and other people's houses. She is living her life one day at a time and I feel privileged whenever I can share time with her.
When the numbers are pushed aside by the personal experience, we all drop our scientific viewpoints and become advocates for the good of the one over the good of the many. I think the strong history of individualism in this country makes us so susceptible to this type of reaction. The push to bring our system of medical care in line with the rest of the developed nations in the world must always butt heads with this very powerful desire to put the needs of the individual close to us over the needs of the group. I could try to distinguish between applying the numbers to screening vs. applying the numbers to treatment but in the final analysis, when it becomes personal, the numbers do not matter. After all, like average survival expectancies, they do apply only to the population and do not predict any particular individual. And who is to say that the value of those extra months and years are not worth the cost?