Tuesday, April 30, 2013

Breast cancer and other unknowns -- between a (probalistic) rock and a (probabilistic) hard place

The New York Times Magazine cover story on Sunday was disturbing.  With "Our Feel-Good War on Breast Cancer," Peggy Orenstein, herself a woman with a history of breast cancer, confronts the frustrating lack of progress in understanding what causes this disease that has or will touch so many of us, the best ways to detect it, how to treat it, which messages to convey to at-risk women (which is, of course, essentially all of them) and how best to do it.
It has been four decades since the former first lady Betty Ford went public with her breast-cancer diagnosis, shattering the stigma of the disease. It has been three decades since the founding of Komen [the best-funded breast cancer foundation in the US]. Two decades since the introduction of the pink ribbon. Yet all that well-meaning awareness has ultimately made women less conscious of the facts: obscuring the limits of screening, conflating risk with disease, compromising our decisions about health care, celebrating “cancer survivors” who may have never required treating. And ultimately, it has come at the expense of those whose lives are most at risk.
A central ongoing debate is over mammography and whether it saves lives. It's clear that it doesn't detect all tumors, and that it does detect tumors that would disappear with no intervention, and tumors that will never metastasize, and may itself be a risk factor, and yet it's the primary tool for health education and prevention that the breast cancer advocacy groups have, and which they fiercely defend. Despite statistical evidence that it may not save lives and could be causing a lot of harm.

What is 'risk' and how do we know?
People who pay attention are told that this procedure, or that treatment, has certain 'risk' associated with it, or some 'probability' of success. These are difficult words for ordinary people and even for professionals. And the problem is by no means confined to complicated biomedical situations. There is the emotionally subjective aspect of risk, as in "oooh, that's risky", in which emotions override considerations of numbers, often very misleadingly. And there is the scientifically subjective aspect of risk, as in "significant at the 0.05 level." (0.05 is just an arbitrary cutoff for 'signficance' -- another loaded and widely misperceived word).

But even if we overlook these aspects of subjectivity, there is another that is at least as important. A risk is a value between 0 (can't happen) and 1 (certain to happen). How is that determined? It's estimated from some sample of data, in which some number, say m, of observations were made, and some number, n, of them experienced the outcome for which the risk is estimated as n/m. But that is retrospective, meaning it only relates to what happened to those we studied, and there are all sorts of problems in making the data 'representative' of what we want to estimate. Did we measure all the proper variables that might affect the risk. Did we measure the exposures and outcomes accurately enough? Did we sample enough people, and were they 'random' relative to the causes and effects we want to understand?

Even if all went well, there is the inescapable fact that what we want for making decisions, such as clinical decisions on treatment, are clear-cut answers, and we can't get them because they don't exist. Every patient is different, there are multiple kinds of breast cancers, as most other cancers, and multiple ways to get the disease, so predicting an individual's risk of disease is impossible to do with very much precision. Even women with BRCA1 or 2 mutations that are strongly associated with risk aren't at 100% risk, and at some times in history, have been at much less risk than others.

And risks cutting in all directions
It is not just the risk of cancer we have to consider. It is the risk of cancer that might be due to having a mammogram. It is the risk (or probability) that the test will accurately detect a cancer. It's the risk that the cancer being detected would otherwise have progressed to become a health danger (rather than regressing and just going away unnoticed). There is the emotional risk of having a diagnosis.

Then there is the risk of any sort of treatment: biopsies, surgeries of this or that type, radiation treatment, chemotherapy. And risks associated with aspects of life that might yet induce a cancer if you don't already have one, or induce another if you do. And risks are often in these cases not just some simple probability, but the probability of living 1, 5, or 10 years, or of no recurrence.

Every one of these is a probability of sorts that has to be estimated. Since risk factors, such as lifestyles that might be associated with disease, are always changing, and we don't even know what most of those factors are, and since any treatment must be followed up on a large enough number of people to know how well (in probability terms!) it works, women are caught between many probabilistic rocks and probabilistic hard places.

It's exquisitely painful to have to deal with so many competing uncertainties in so very personal an area, when everyone is doing his or her best to evaluate options and knowledge for the shared goal of avoiding or treating disease. Our society is very poorly trained to deal with probabilities in any serious quantitative way; we're more used to high and low values that we can think of as won't-happen or will-happen. And the subtleties play on the scientists and physicians, too. No matter how sincere you are, you want your patients to do what you think is best, as unemotionally as possible, based on your personal assessment of this host of competing probabilities. And you are also embedded in this subjectivity, because you want your view to be correct, and you are always vulnerable to shading the evidence to suit your preferences.

There is plenty of advocacy, dissembling, careerism, vanities, and all that in those dealing with these issues, both patients and perhaps especially researchers and clinicians. New findings that challenge the currently accepted verdict of probabilities are emotionally adopted or resisted.

One might say that much of this includes improper or uninformed behavior. But the problem is that our knowledge, and probabilistic 'knowledge' in particular, is shaky and difficult to handle and would be if we were all saints with IQs of 200.

Trying to balance incomplete information, probabilistic estimates imperfectly arrived at, emotional reactions, and the poor understanding of probabilities plagues even the most honorable and objective of us. And it's generally even worse.  Probabilities and risks in cases like this are averages based on analysis of groups -- patients treated this way or that, screening populations, and so on.  But the risks you need to know about are for you, though is far from clear that everyone in one of these risk groups has the same risk.

It is not even clear that there is advice one can give: since the many relevant probabilities are all imperfectly known, to imperfectly known extents, the most we can do perhaps is acknowledge the realities, that the kind of evidence we must weigh is just the way science works these days.  When, whether, or how we might conceive of the problems differently, to get closer to actual individuals rather than groups, when everybody is different, is an open question--but one of widespread relevance.

Unfortunately, at this time in history of course, even in so painfully urgent and important areas as diseases like cancer, life is a roll of the dice -- and we don't even know what kind of dice we're rolling.

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