Five ways to tame the risk-benefit-uncertainty troika

There was a story on NPR this morning that sent me in a radical direction. It discussed the increase in use of brachytherapy for localized breast cancer. The idea is that this is a concentrated dose delivered much more locally and rapidly (over 5 days) than the conventional external beam radiation (over 6 weeks). The issue is that it has not been tested rigorously in a randomized controlled trial yet, and some oncologists are concerned about its outcomes as they compare to the conventional approach. One of the concerns stems from an increase in the rates of subsequent mastectomies, which are double in brachytherapy relative to conventional. At the same time, there are clear benefits, not the least of which is the period of exposure and the hassle associated with daily trips for radiation for 6 weeks.

Several points popped up in my head in response to the story:
1. When discussing this predominantly women's disease, the expert voices mostly heard from were male (5 of the 6 doctors quoted). Does this matter? Not sure.
2. The priorities addressed by the experts were the traditional outcomes -- survival, recurrence, metastasis. The priorities described by the patient were about her time and convenience today.
3. The concern about the procedure stems from the observed doubling of the need for mastectomy within 5 years among patients treated with brachytherapy, an event "rare no matter what what kind of radiation women got."

So what's my point? Do I think that more rigorous testing is not indicated? Not at all; we need a more rigorous evaluation of the technique. No, what I am wondering is at what point should a procedure like this (or any intervention, for that matter) become available to patients as an option to be considered? Should its availability be determined in a dark room by bespectacled men around a conference table, or should it be put on the menu of choices, along with its risks, benefits and uncertainties, as soon as it looks safe enough, whatever that looks like?

The larger question this raises is what is the degree of uncertainty that we are willing to accept around interventions that become available, be it a drug or a procedure or a device? How do we incorporate patients' priorities for outcomes that are important to them into these decisions? Remember ACT-UP and how they moved the FDA to make more rapid decisions about treatments for HIV/AIDS? Have we swung too far in the opposite direction today, whereby we want a virtual guarantee of safety before a technology is approved?

I offer these 5 potential question to help with making these decisions:
1. How severe/deadly is the disease in question?
2. What is (are) the known potential benefit(s) of the intervention?
3. What is (are) the known potential risk(s) of the intervention?
4. What uncertainties bracket this risk-benefit equation?
5. How does the patient feel about the extent of this risk-benefit-uncertainty balance in the context of her condition?

I think that the first four are the questions that the FDA struggles with every day. They are the gatekeepers for the availability of new technologies, and, therefore, for the relevance of the fifth question. What I am wondering is whether it is not better to start bringing a lot more of the public perspective to the discussion much earlier, so that the patient can have the option of evaluating more choices sooner. I know I may be treading on thin ice here, but I am ignoring any market forces or special interests for the moment. The question I am asking is "In the best of all possible worlds, where no one is trying to sell you anything, when is the best time to give the patient an opportunity to accept or reject an intervention, given the risk-benefit-uncertainty profile?"

Bottom line: There are no guarantees. Just because something is available on the market does not mean that it is completely safe or completely effective. Most importantly, it does not mean that we come even close to being certain about these attributes. As a corollary, just because there are uncertainties about the risks and benefits of an intervention, does it mean that it should not be available as an option for a patient? My guess is that there is a balance of this troika of properties that may be optimal on average, but I am also guessing that that this average balance will miss a substantial volume of outliers. Just as some people thrive on the thrill of bungee jumping while others clamp down just at the mere thought of it, so some patients may surprise us with their position on this risk-benefit-uncertainty continuum.

I apologize if my argument is not clear -- I am definitely thinking about this stuff actively. The one thing I am absolutely sure of is this: Unless the public and clinicians are educated about how to have these conversations, we will always have to rely on and, consequently, blame someone else for making decisions for us.

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How to make safer decisions in medicine

I love when an article I read first thing in the morning gets me to think about itself all through my morning chores and then erupts into a blog post. So it was with this little gem in the statistical publications "Significance." The author suggests making gambling safer by placing realistic odds estimates right on the poker machines in casinos. He even goes through the generation of the odds of winning and losing and how much based on really transparent assumptions. In fact, what he has in effect constructed is a cost-benefit model for the decision to engage in the game of poker on these machines. Seems pretty simple, right? Just a few assumptions about how long the person will play, some objective inputs about the probabilities, and PRESTO, you have a transparent and realistic model of what is probable.

In medicine, there is a discipline known as Medical Decision Making, and what it does is exactly what you see in the "Significance" article: its practitioners construct risk- (and, hence, cost-) benefit models for decisions that we make in medicine. To be sure,these turn out to be rather more complex, since the inputs for them have to come from a large and complete sampling of the clinical literature addressing the risks and the benefits. But that's the meat; the skeleton upon which this meat hangs is a simple decision tree with "if this then that" arguments. In this way these models synthesize everything that we know about a specific course of action and put it together into a number driven by probability.

They usually go something like this. We have a group of women between 40 and 49 years of age with no apparent risk factors for breast cancer. What is the risk-benefit balance for mammography screening in this specific age layer? One way to approach this is to take a hypothetical cohort of 1,000 women who fit this description and put it through a decision tree. The first decision node here is whether to perform a screening or not. What follows are limbs stretching out toward particular outcomes. Obviously, some of these outcomes will be desirable (e.g., saving lives), while some will be undesirable, ranging from worry about false positive results to unnecessary surgery, chemotherapy, radiation, and even death. Because these outcomes are so heterogeneous, we try to convert everything to monetary costs per quality of life (quality because there are outcomes worse than death, as it turns out). But what underlies all of these models is the mathematics derived from clinical studies, not pulled out of thin air. This is the most useful synthesis of the best evidence available.

To be sure, MDM models are rather more complicated than the poker example. They require a little more undivided attention to follow and understand. Furthermore, I personally did not get a whole lot of exposure to them in my training, but perhaps that has changed. Like anything to do with probability, these models tend to be off-putting in a society that has consigned itself to wide-spread innumeracy. And doctors are certainly not immune from misunderstanding probability. Yet without them perceptions rule, and our healthcare becomes a reckless gamble. In our ignorance we collude to build profits that come with medicalizing small deviations from the perceived normality. Sadly, the primary interests that drive these profits are not usually doing so with probabilistic forethought either, but rather on the basis of red hot conviction that they are right.

Doctors and e-patients need to lead a radical transformation in how we handle decisions in healthcare. It is very clear that willful ignorance has not served us well, and we are all too easily led into panic about every pimple. Resilience can only come when we question our assumptions. Alas, our intuitive brain is almost certain to mislead us when faced with complex information; why else would we need explicit odds listed on poker machines? The absurd complexity of information in medicine deserves no less. It's time to start the probability revolution!

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The probabiltiy dozen of participatory medicine

Yesterday my rant about uncertainty and probability got quite a bit of play in cyberspace, and I am glad.

Uncertainty is ubiquitous. We consider the odds of rain when choosing what to wear. We do (or at least we should do) a quick mental risk-benefit analysis before buying a burger at Quickie-Mart. We choose our driving routes to work based on the probability of encountering heavy traffic. We do this mental calculus subconsciously but reliably, mostly getting it right. What is odd, though, is that there are certain parts of our lives where we expect complete and utter certainty. I will not get into the political aspects of this fallacy, but I do want to continue down this line of reasoning about healthcare.

As I said yesterday, and many many times in the past, the only certain thing about medicine is uncertainty. And here is what I want you to understand deeply: the amount of uncertainty is much greater than you think. So, every time you say to yourself "I think there is a lot of uncertainty in this information," multiply it by 100, and then you may get close to just how uncertain most information is.

And again, I want to emphasize that this uncertainty gets magnified in the office encounter. So, what is the solution, short of having everyone understand the totality of evidence? Yesterday I said that the solution is to teach probability early and often, and this is indeed the best long-range answer. But is there anything we can do in the short-term? The answer, of course, is yes. And here is what it is.

Everyone needs to learn what questions to ask. Instead of nodding your head vigorously to everything your doctor says, put up your hand and ask how certain s/he is that s/he is on the right track. Here is a dozen questions to help you have this conversation:

1. What are the odds that we have the diagnosis wrong?
2. What are the odds that the test you are ordering will give us the right answer, given the odds of my having the condition that you are testing me for?
3. How are we going to interpret results that are equivocal?
4. What follow-up testing will need to happen if the results are equivocal?
5. What are the implications of further testing in terms of diagnostic certainty and invasiveness of follow-up testing?
6. If I need an invasive test, what are the odds that it will yield a useful diagnosis that will alter my care?
7. If I need an invasive test, what are the odds of an adverse event, such as infection, or even death?
8. What are the odds of missing something deadly if we forgo this diagnostic testing?
9. What are the odds that the treatment you are prescribing for this condition will improve the condition?
10. How much improvement can I expect with this treatment if there is to be improvement?
11. What are the odds that I will have an adverse event related to this treatment? What are the odds of a serious adverse event, such as death?
12. How much will all of this cost in the context of the benefit I am likely to derive from it?

And in the end, you need to understand where these odds are coming from -- the clinician's gut or evidence or both? I prefer it when it integrates both, which, I believe, was the original intent of evidence-based medicine.

Perhaps for some of us this is a stretch: we don't like numbers, we are intimidated by the setting, the doc may be unhappy with the interrogation. But it is truly incumbent on all of us to accept the responsibility for sharing in these clinical decisions. I believe that the docs of today are much more in tune with shared decision-making, and understand the value of participatory medicine. And if they are not, educate them. Ultimately, it is your own attitude to risk, and not just the naked data and the clinician's perceptions of your attitude that should drive all of these decisions.  

Knowledge is empowering, and empowerment is good for everyone, patient and clinician alike. As patients, taking control of what happens to us in a medical encounter can only bring higher odds of a desirable outcome. For physicians, a cogent conversation about their recommendations may help safeguard against future litigation, not to mention augment the satisfaction in the relationship.

And thus starting to discuss probabilities explicitly is very likely to get us to a better place in terms of both quality and costs of medical care. And in the process it may very well train us how to make better decisions in the rest of our lives.

I would love to hear about your experiences discussing probability, be it in a medical or non-medical setting. And as always, thanks for reading.


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Clinician as the Politbureau of medicine?

Do you think that medicine in the US is centralized? I do, but not in the way that we generally understand centralization. And furthermore, it is this centralization that I believe is making the idea of shared decision making so intimidating to some. Here is what I mean.

If you read management texts, centralization refers to an organization that is run predominantly top-down. In other words, a couple of oligarchs at the top of the ladder make all the decisions without consulting anyone below. In this way all the power is concentrated in the hands of the few. In an antithesis to this, in a decentralized organization, grassroots input and initiatives are incorporated into the fabric of the organization. And while in the times of a great crisis, when rapid decisions are necessary, the benefits of centralization may outweigh its risks, during normal day-to-day operations, such unilateral power can result in obviously negative consequences, from discontent among the employees to making the wrong choices. Furthermore, as organizations grow in size, it gets that much more difficult to run them effectively within the centralized paradigm.

Now, let us look at medicine. The traditional model of the doctor-patient relationship relies on the clinician to know what is right for the patient: take this pill and don't worry about the side effects, dear. Now, clearly, when someone shows up to the emergency room in septic shock, there is very little room for a democratic process; we want the doctor to do rapidly what needs to be done to save the patient. But this is a catastrophic exception to the rule of what modern medicine cares for. From pre-diabetes to pre-hypertension to "borderline cholesterol" to osteopenia to mild depression, these are the "diseases" that are prevalent in the office of the 21st century. None of these is particularly urgent or life-threatening. And if we are honest with ourselves, even a devastating diagnosis of cancer does not demand an instantaneous intervention: in the vast majority of cases there is ample time for discussion and contemplation. So, the centralized approach is the wrong way to go. Thus enter the robust discussion about shared decision making. 

Another reason that centralization of medical decisions is crumbling is the expanding patient panels that clinicians need to engage with in order to stay solvent, all within the context of increasing compliance and regulatory burdens along with decreasing reimbursements. Without an equal growth in one's cognitive ability to multi-task, this escalating imbalance is creating a rising risk for unilateral decisions to be plain wrong.

So, in my mind, this is yet another argument for all parties to embrace shared medical decision making to the extent we as patients are willing and able to do so. Because what is the alternative?