For the last several weeks I have been reviewing cancer survival statistics from patients that were treated for their disease during the pandemic. My eyes are glossing over from reading Meier-Kaplan curves. The Meier-Kaplan curve is a graphical representation of the survival function. It shows the probability that a subject will survive up to time “t” The curve is constructed by plotting the survival function against time. The end point into the future is not known Using techniques of extrapolation and interpolation we can estimate survival benefits. The difference between these two techniques—Interpolation refers to predicting values that are inside of a range of data points. Extrapolation refers to predicting values that are outside of a range of data points. The end points are not known into the future. Physicians of my era—I graduated from medical school in 1976, remember when chemotherapeutic agents were not as well understood and toxic events were more common. The survivability lines comparing treatment and no treatment often crossed early on because the complications of therapy were more lethal in the short term and led to earlier deaths and adverse outcomes. If patients could survive therapy, there may be a long-term benefit to treatment. In all the curves that I reviewed over the past couple of weeks, never did I see such a phenomenon which means that the treatments and techniques we are using to combat cancer have all but eliminated the short-term complications of therapy.
I have written several articles about risk over the past five years. I became interested in this subject after reading the classic book by Peter Bernstein entitled AGAINST THE GODS—The Remarkable Story of Risk. What occurred to me this week was that the quantification of risk and the subjective concern for risk that every individual has are very different and are seldom appreciated by those making recommendations about how we should mitigate for our own individual risk. Many times, during the pandemic, the experts extrapolated their subjective concerns into a decision about mitigation. Governments then used their coercive powers to enforce these prejudices and create mitigation policies that were not consistent with the data. Perceived risk replaced statistical risk in the mitigation calculous. Doctors in training are always advised not to influence a patient’s decision by allowing their own prejudices into the process. Public Health specialists should have followed similar advice.
Let me use an “apolitical” example to illustrate my point. One of my closest friends owns his own trucking company. He is a good businessman because he understands that worrying about things that one can’t control and focusing on things that one can control is how good decisions are made. But he has expressed concern to me about my exercising habits. I swim outdoors every day in the summer at 4AM by myself. He tells me that I should only swim at my age with a lifeguard and with other people around. There is a risk of swimming alone. It is the same risk as if I rode my bike on the greenbelt or in the foothills by myself at 4AM. It is a short-term risk. It is my risk and my responsibility to mitigate that risk.
He on the other hand has gained over 100lbs over the last 3 years. He doesn’t exercise. His long-term risk of heart disease and its complications are far greater than my long-term risk. I have more of a chance of dying early on from exercise. He doesn’t have that risk but by not taking on the risk of exercise, his chance of dying in the long-term years early—we need to extrapolate, is greater. Sometime along the way our Maier-Kaplan curves cross.
This is where the “experts” and bureaucrats and advisory boards missed the boat. It would be like a doctor trying to get a patient out of the hospital early on to get maximum reimbursement, but the patient dies in 30 days because they were discharged too early. This happened when patients who were being prophylaxed for deep venous thrombosis (DVT) and who stayed in the hospital for many days, started being discharged early and were not being prophylaxed at home. The thirty-day deaths increased significantly.
My point in bringing all this up is that by considering only the short-term risks, the long-term ramifications of the various mitigation strategies were ignored. This is true not only with medical morbidities and mortalities, but also with the economic and social ramifications of the strategies. The Maier-Kaplan curves are bound to be crossing and we will never know about it.
Politicians and info “babes and guys” in the fake news have a short-term horizon. They have already moved on to “monkey-pox” and “January 6th“. Businesspeople, farmers and ranchers, and families look into the future—many years, sometimes across generations. Mitigating against a long-term risk sometimes mean taking a greater short-term risk. That decision is one that we can only make for ourselves. Our politicians and those in the medical community in Idaho failed to respect that fact.
The curves are crossing before our eyes.