Healthcare, etc.

Longevity, life expectancy, premature mortality: Are they lions and tigers and bears?

noreply@blogger.com (Marya Zilberberg) — Wed, 16 Sep 2015 20:13:00 +0000

Before I set up the context for this post, I am going to throw this out to you. Think of putting rocks on a scale to achieve the weight of, let's say, 1,000 lb. And let's say that you are required to use rocks of similar size. You have a bunch of bricks -- these are your biggest "rocks," and you have a bunch of pebbles like the ones I have in my driveway (perhaps you have them in yours too). In order to get to 1,000 lb, will you need more bricks or more pebbles? I am not trying to trick you. This is just an illustration of the fact that you can get to the same magnitude of a variable (in this case weight) by either using a smaller number of more weighty components (bricks) or a larger number of lighter ones (pebbles). Keep this in mind as you read on below.

I got an interesting comment from Brad F. on my post from yesterday regarding the 10% number for the premature death avoidance attributed to access to medical care. He pointed me to a blog post on the always-informative The Incidental Economist web site which called this a "zombie statistic." Despite having a fifteen-year-old who is an avid fan of zombie fiction and film, I was not familiar with this term, but inferred its meaning pretty easily.

The gist was that when people started to look for the origins of this number, the evidence was difficult to find, and, when discovered, was at best shaky:

Thus, as Austin and Adrianna had found, the 35-year old CDC paper seems to be at the root of the often-cited 10% number; it’s “paper 0,” if you will. But those that continue to reference 10% as an estimate for health care’s contribution to health should know that the only evidence they are referencing is a survey of 40 people, done when Jimmy Carter was president. It’s not evidence-based except by the weakest notions of “evidence.” It’s really a zombie statistic.

My obvious next question was whether a more trustworthy estimate existed for the medical care's contribution to life extension in the US. In my search for a better estimate, I continued to go down the rabbit hole of links, arriving here, the AcademyHealth Blog, landing on the article called "Half of longevity gains due to health care." It was a summary of the attempt by the authors of The Incidental Economist to answer this very question. And what did they find? First, they quoted a NEJM citation from 2006, where it was claimed that 90% of the increases in life expectancy since the 1960s was due to reduction in cardiovascular and neonatal deaths. After meandering through several other sources, the authors concluded that we can attribute about 50% of the responsibility for extending our life to medical interventions.

And that's when I really confused myself. I started thinking about whether premature death and longevity are related, and how they may be related, and are we even talking about the same thing when we invoke each of them.

Premature mortality can be quantified in several ways -- 1). percentage of all deaths that are considered premature, or 2). proportion of people in a population whose death is considered premature (that would be so many cases per 100,000 population). Longevity, on the other hand, is a measure of the average life span of a population. The current life expectancy in the US is 78.8 years. This begs the question of how these two, premature deaths and life expectancy, are numerically related to each other. And can the latter go up without the former going down?

Well, if the language here is consistent with how we speak it, "premature" implies that we know what "timely" means. The definition of a "timely" death must be based on the average life expectancy in a population. This number varies according to certain characteristics of a population, of course, so different subgroups would have a different life expectancy. For example, at any given age, the life expectancy of a person with heart disease should be lower than that for a person who is perfectly healthy. If we can reduce the risk of a premature death in people with heart disease, their life expectancy should edge closer to that of a healthy individual. And, in fact, according to the literature, this has happened in cardiovascular patients, partly due to better treatment of blood pressure, and partly due to fewer people smoking and other healthful lifestyle modifications.

So, it's clear that when death due to a disease is postponed, longevity increases and, ergo, premature deaths drop. It's a bit circular, I know. But here is one interesting detail to consider. Longevity or life expectancy (I use them interchangeably) is an age average. So here is one question: Does the impact on the magnitude of life expectancy gains vary with the age of the population in which premature deaths are avoided? I know, its a clunky question. What I mean is, would you expect life expectancy to go up more, less or same amount if we manage to reduce premature deaths in infancy versus old age? If you consider that life expectancy is an average, then infant mortality attenuates this average severely (think adding a whole bunch of numbers into the denominator without contributing anything to the numerator). So you can imagine, if infant mortality goes down a lot (a big reduction in premature deaths), overall population life expectancy spikes decisively. Reducing premature deaths among the elderly, clearly, by this same calculation, will not result in nearly the same increase in life expectancy.

Another way of looking at this is to consider that a much larger reduction in premature deaths among the elderly (think driveway pebbles) than among infants (those sizable bricks) would be needed in order to reach a similar degree of longevity improvement. A less intuitive corollary of this is that we indeed can have an increase in premature mortality in a group that contributes little to longevity (the elderly) and still witness a large bump in life expectancy with a much smaller reduction in premature deaths within a group with an outsized contribution to longevity (infants). So that answers the second question I posed about these measures -- they can diverge.

Now, on to the estimated contribution of medical care to either or both of these. We have, in fact, witnessed a dramatic reduction in infant mortality. I found this report from Health Resources and Services Administration that infant mortality has dropped from 55.7 per 1,000 live births in 1935 to 6.8 per 1,000 live births in 2007. And here is what the authors cite as reasons:

...dramatic declines in infant mortality rates over the long term were due to large declines in mortality from pneumonia and influenza, birth defects, prematurity and low birthweight, respiratory distress syndrome (RDS), sudden infant death syndrome (SIDS), and injuries. Improvements in living conditions, advances in neonatal medicine and infant heath care, reductions in smoking during pregnancy, and increased access to and use of prenatal care have been suggested as factors responsible for decreases in infant mortality over the past several decades...

And here is an interesting detail: the pace of this drop was a dizzying 3.1% per year on average between 1935 and 2000. However, between 2000 and 2007, the rate went down only from 6.9 to 6.8 per 1,000 live births, a staggering deceleration in this steep decline. A further detail indicates that "much of the statistically significant decline [occurred] in the neonatal period." The implication of this is that the latest declines are due to technology use, most likely among the very premature infants upon delivery. This is the very definition of access to medical care, and falls completely outside of the domain of public health.

Just one more random thought. Reductions in infant and cardiovascular mortality, each a product of both medical and public health interventions, are one side of the life expectancy equation. The other, darker, side is the fact that in some groups and locations in the US, the overall longevity is waning. Much of this phenomenon can be attributed to poverty, environmental factors and poor health behaviors, or, in sum, a reflection of our dismal investment in public health. And, sure, there is a component of access here too. And what about this calculus: Between 1990 and 2010, mortality from cardiovascular disease dropped by about 150,000 per year. That would be an awesome contribution to increased longevity and reduced premature deaths, if it weren't offset by all the deaths (presumably premature) related to the healthcare system itself.

I know that none of this gets to the crux of the matter: What is a reliable estimate of what proportion of the increases in life expectancy can be attributed to access to medical care? But what it does make me appreciate is the complexity of each and every term, every definition, every estimate that we confront daily. This devil, as always, is in the details.

If you like Healthcare, etc., please consider a donation (button in the right margin) to support development of this content. But just to be clear, it is not tax-deductible, as we do not have a non-profit status. And I post when I feel like it. Thank you for your support!

"Lifesaving": I don't think it means what you think it means

noreply@blogger.com (Marya Zilberberg) — Tue, 15 Sep 2015 20:13:00 +0000

Transparency, I think that is what pissed me off so much. Or rather the opaqueness. Got me to post again, though, right? Well, don't get used to it.

The message was clear: We are heroes, we are giving you lifesaving nuggets of information. And Gina Kolata swallowed it, hook, line and sinker. No pushback, no critical thinking, just drooly awe. I get pissed about stuff like that. Yes, I do. Am I the only one who sees the hypocrisy? The comments would suggest otherwise, but my reasons are a bit different from some of what I saw: we cannot scapegoat pharma for this one, folks.

The headline read "Lower Blood Pressure Guidelines Could Be ‘Lifesaving,’ Federal Study Says.” There has been a lot on triggers and trigger warnings these days in the press. Well, let me contribute to the discussion. If you know me, you know there are multiple “triggers” in that title for me; there really should have been a trigger warning. "If you have seen through cherry-picked data before, if you have seen through disease mongering, if sensationalized medical headlines induce vomiting in you, beware of triggers in this headline." And, by the way, the study will not be published for another couple of months, so who has vetted these data? The investigators who are so incredibly invested in the results? Their PR office? Journalists hungry for a story? Laughable!

So, "triggers."

First: Lifesaving. Very few things in life are lifesaving. Under the right circumstances, a parachute is indispensable for saving a life. A surgery can save the life of a traumatized human. An EpiPen can be lifesaving. There are just not that many circumstances in which medicine can really claim saving lives. Most of the strides we have made in extending life expectancy did not come through pills, contrary to breathless reports. We owe them to public health interventions – clean water, sewage treatment, vaccination. Even if you look at the current causes of premature death in the US, it’s largely unrelated to medicine. Believe it or not, only 10% of premature death can be attributed to not having access to medicine. The remaining 90% is just what you would think: genetics, behavior, environment and economics. Yes, money, or its flip side, poverty, contributes generously to early mortality in the US. So if you invoke “lifesaving” in a headline in the context of a medical intervention, the burden of proof in on you. But I guess the public bears the burden of credulity. And that pisses me off.

Second: "Lower blood pressure guidelines." So what they are telling me is that they have found evidence that getting one's blood pressure into a lower range (systolic 120 mmHg or below in this study) than what is currently recommended (systolic 140 in people 30-59, and150 mmHg in those over 60) will save lives. OK, what is the next obvious question? If you are me, there are several. One: Is this true for everyone over 50 (this study’s population) with high blood pressure? Is it true for my 80-year-old mother just as much as for a 55-year-old African American man who also has diabetes? And what about that 62-year-old executive whose stressful job occasionally throws her into a hypertensive paroxysm? Two: How much does it reduce any given person's risk for dying and over what period of time? To say that it reduces the risk of death is meaningless. We will all die eventually. As much as we like to split hairs about pre-diebetes, we prefer to remain silent on that much more prevalent chronic condition of humanity – pre-death. So, in the case of my 80-year-old mother, how much will it reduce her risk of dying, and over how long – 10 years, 20 years, more? Does it even make sense to ask these questions given that age puts us at risk for death from many causes at the same time? The question is much more relevant for the 55-year-old African American man, of course, but the headline, and, alas, the story fail to tell me this detail. Three: Was the observed mortality benefit even due to the blood pressure difference? That is, how well did they succeed in treating each group to their designated blood pressure target? These answers can only come once the paper becomes available. Right now we just have to take their word for it. And you know how much that appeals to me, right?

Third: The story made a reference to a 25% reduction in mortality. If it meant that everyone has a 100% chance of dying, and now this risk is down to 75%, well, that may be lifesaving. However, even the most optimistic among us surely cannot think that this is what this number means. In fact, what this number means is that whatever your risk is today of dying in the next 5 years, say, by keeping your blood pressure at or below 120 will reduce it by 25%. Someone like me, I would guess, has an under 5% risk of dying over the next 5 years. Reducing this risk by 25% gets me into a 3% range. Some may say that this is substantial. Others, me included, will ask another question.

Fourth: At what cost? And I have to say, the investigators along with Kolata thought of that. They indicated that these drugs are pretty cheap, as 90% of them are generic. Boom! All set, right? Wrong. Side effects are costly (the article skirts this issue). And not just in dollars, but in quality of life, in whether or not you can get out of bed to take care of your children, whether or not you can give a 30-minute talk at a conference without either running out to the bathroom or wetting yourself, in whether you increase your risk of passing out or even of having a stroke by dropping your blood pressure too much, in whether you injure your kidneys by the same mechanism. And to be fair, as a part of the study, the researchers are looking at least at some of these important questions. But here is the kicker: those data are still being analyzed. So even the investigators don’t know what is on the other side of the risk-benefit scale. It means that in essence, they are touting something as “lifesaving” without telling us in whom, how lifesaving, and what the trade-offs may be.

And oh, here is one last question that comes to mind for me:

Fifth: Did GSK sponsor this study? I ask that with my tongue firmly in my cheek, because I know that this study had federal funding. It was our tax dollars, on the order of $10-20 million, I am guessing, that picked up the tab. Why is my tongue in cheek? Because if GSK had put out a news release like this, not even the East Podunk Times, let alone The New York Times, the paper of record, would have been stupid enough to print it. Because pharma, right?

So what is the moral? There is more than one, take away what you will. What stands out for me is that we have become blind. I am not an industry apologist – there is history there, which I am not interested in rewriting. I am also quite realistic about investment in pharmaceutical business as a vehicle for wealth in the US. However, in this hunt for lies and liars, another head has popped up on the hydra. While we weren't looking, academic researchers somehow became more interested in their 15 minutes of fame than in the integrity of what they present to the world. And, as far as we think we have come away from accepting paternalism in medicine, we are right there to worship them.

Why does this piss me off so much? I don't know. Perhaps the arrogance. Perhaps because it makes me sad to see that my fellow researchers can be either so blind or so ambitious as to push out something so unfinished to media vultures looking for "lifesaving" meat. Perhaps I feel for my former colleagues in their offices, who will now need to deal with spikes in anxiety and even blood pressure in their already hypertensive elderly patients, and are now in a position to leave that anxiety unaddressed in this age of the incredible shrinking appointment that has done away with nuanced relationship-nurturing conversations. Perhaps I feel for them even more because they too will feel more anxiety in this unforgiving world of 21st century medicine in America, where their hides depend on meeting "quality metrics" built on half-baked data like those reported in Kolata's story. And finally, and most importantly, I feel for the patients, who, without knowing it, are the true subjects of this experiment in American medicine, where docs are beholden less and less to the individuals in front of them and more and more to the gluttonous bureaucratic machine that is swallowing their humanity. It is beyond time to stop this madness.

If you like Healthcare, etc., please consider a donation (button in the right margin) to support development of this content. But just to be clear, it is not tax-deductible, as we do not have a non-profit status. And I only post when I feel like it. Thank you for your support!

The slow work of healing

noreply@blogger.com (Marya Zilberberg) — Tue, 23 Apr 2013 16:32:00 +0000

I just finished reading "Tattoos on the Heart" by Gregory Boyle. I came to it partly via Krista Tippett's conversation with him last summer at the Chautauqua Institute, and partly through other sources. It is a far-ranging account of his work over the last 20 years with the members of toughest Latino gangs in LA through his non-profit Homeboy Industries. The book is suffused with love for these societal outcasts and peppered with wisdom, some in the Christian and some in other traditions, including secular.

What does a book like this have to do with healthcare? Well, a lot. There are many points that might help rehumanize clinical medicine. But this passage on page 179 really made me stop in my tracks:

Funders sometimes say, "We don't fund efforts; we fund outcomes." We all hear this and think how sensible, practical, realistic, hard-nosed, and clear-eyed it is. But maybe Jesus doesn't know why we are nodding so vigorously. Without wanting to, we sometimes allow our preference for the poor to morph into a preference for the well-behaved and the most likely to succeed, even if you get better outcomes when you work with those folks. If success is our engine, we sidestep the difficult and belligerent and eventually abandon "the slow work of God."

Now, I am not Christian or even particularly religious. I am, however, a fan of the Jesus persona who merged with the poor and the hungry and the downtrodden, who became the change he wanted to see. And I had to re-read this paragraph several times, particularly the last sentence. Is this not exactly what we are seeing in medicine? We have told ourselves a lie that by chasing only those outcomes that are quantifiable we are pursuing only that which is important. But wasn't it Einstein who said that not everything that counts can be counted, and not everything that can be counted counts?

Is this gaming of the system that Father Boyle talks about in the paragraph above not exactly what we are seeing as the end-result of the perversion of the idea of evidence-based medicine? What if we change a few of the words in the above paragraph (and stick to secular language)? Will it fit what is happening in medicine today?

Payors ~~Funders~~ sometimes say, "We don't fund efforts; we fund outcomes." We all hear this and think how sensible, practical, realistic, hard-nosed, and clear-eyed it is. ~~But maybe Jesus doesn't know why we are nodding so vigorously.~~ Without wanting to, we sometimes allow our preference to help the sick ~~for the poor~~ to morph into a preference to take care of ~~for~~ the well-behaved and the most likely to succeed, even if you get better outcomes when you work with those folks. If success is our engine, we sidestep the difficult and belligerent and sickest and eventually abandon "the slow work of healing ~~God~~."

I don't have the answers to how to solve our fiscal and quality crises in medicine. Well, I do, but they involve a cultural overhaul of the entire US of A. But this paragraph sure is making me think.

If you like Healthcare, etc., please consider a donation (button in the right margin) to support development of this content. But just to be clear, it is not tax-deductible, as we do not have a non-profit status. Thank you for your support!

The New York Times, aspirin and melanoma, oh my!

noreply@blogger.com (Marya Zilberberg) — Fri, 15 Mar 2013 15:45:00 +0000

One of the reasons my blogging has fallen off lately is because I hate sounding like a broken record. Yet here I am again calling this time the New York Times Well blog on its reporting of, yes, you guessed it, another cancer study.

The story this time is about a paper coming out of the humongous Women's Health Initiative study that examines the relationship between aspirin and melanoma development, hypothesizing that aspirin may help prevent this skin cancer. The paper was published in the journal Cancer and is, of course, behind a paywall. And the abstract, as always, tells me very little.

So I did a little guessing and left this comment on the blog:

So, an absolute risk reduction would have been a much more helpful number to cite, and because the full paper is behind a paywall I cannot get that number. But I can do a little educated estimating:

There were 548 incident melanomas among 59,806 women, amounting to a 0.9% risk of developing this cancer over 12 years. Let's just call it 1%, shall we? Understanding that this 1% is a hybrid of the risk with and the risk without aspirin, the baseline risk must be a little bit higher. Let's give aspirin a huge break and assign the risk without it to the entire group -- let's call it 1.25% over 12 years. Reducing this 1.25% risk by 21% relatively give us roughly 1% risk of melanoma in 12 years in this age group. So, really we are going from 1.25% to 1% risk by using aspirin. This means that 400 women need to take aspirin regularly to avoid 1 case of melanoma (if we believe that this relationship is causal). Mind you, we are not talking about death from melanoma, but just a diagnosis of melanoma. And let's remember that early melanomas are just excised without further treatment.

Now, among these 400 women daily aspirin can be expected to cause roughly 1 major bleeding event per year. So, over 12 years there would be up to 12 major bleeds. All to save 1 person from a melanoma diagnosis. Why not report the full story?

We'll see if it gets accepted. And by the way the aspirin and bleeding numbers came from a recent large study published in JAMA and covered here at Forbes.

If you like Healthcare, etc., please consider a donation (button in the right margin) to support development of this content. But just to be clear, it is not tax-deductible, as we do not have a non-profit status. Thank you for your support!

Healing medicine's moral injuries and spiritual violations

noreply@blogger.com (Marya Zilberberg) — Thu, 14 Mar 2013 15:43:00 +0000

This, from the On Being blog:

Dr. Shay has his own name for the thing the clinical definition of PTSD leaves out. He calls it “moral injury” — and the term is catching on with both the VA and the Department of Defense.

[...]

“Whether it breaks the bone or not,” he says, “that wound is the uncomplicated — or primary — injury. That doesn’t kill the soldier; what kills him are the complications — infection or hemorrhage.”

Post-traumatic stress disorder, Dr. Shay explains, is the primary injury, the “uncomplicated injury.” Moral injury is the infection; it’s the hemorrhaging.

And a parallel quote from Abe Verghese's The Tennis Partner:

It's important that you realize that every illness, whether a broken bone, or a bad pneumonia, comes with a spiritual violation that parallels the physical ailment.

As I was commenting on the Facebook page of On Being, I started to think about our constant pursuit of precision medicine, which just misleads us into a delusion of certainty, and how far we have drifted from the humanistic goals of medicine -- healing the soul along with the body.

Yesterday I listened to a podcast of Krista Tippett's conversation with Natalie Batalha, an astronomer who discovered the first rock planet outside of our solar system. Dr. Batalha, the ultimate scientist, reminded me that poetry and imagination are essential ingredients of science. She said something like "I am the universe looking at myself through the eyes of this sentient being." This is poetry and spirituality, and every component of this statement is grounded in scientific fact.

The science of medicine needs to regain its soul. It can do this only through the admission of our great uncertainties at the intersection of the "uncomplicated injury" and "moral injury." And even more than admit, we need to embrace and revel in these uncertainties -- this is where poetry and imagination reside. If we fail to do this, we risk compounding this "spiritual violation" instead of easing it. I know this isn't anywhere in the PPACA, and it is not a quality metric that anyone will monitor so as to reward/punish. And it's uncharted territory to boot. Yet this is precisely what is needed to heal medicine.

If you like Healthcare, etc., please consider a donation (button in the right margin) to support development of this content. But just to be clear, it is not tax-deductible, as we do not have a non-profit status. Thank you for your support!

ACOG's dysmenorrhea FAQs: Evidence of propaganda?

noreply@blogger.com (Marya Zilberberg) — Tue, 18 Sep 2012 14:00:00 +0000

I have been looking up information on endometriosis for a friend of mine, and came upon this from the American College of Obstetricians and Gynecologists:

So I bit and started reading. And about half way through my reading it I realized that this really reminds me of how they taught literature in the my native USSR. The teaching consisted of stock interpretations of the great authors' works through the prism of Communist Party propaganda. In this interpretation all of the writers' messages railed against the monarchy, and all exhortations were for the purpose of freeing the proletariat. No teacher ever dared to disagree, and no student was expected to question.

Why, you ask, do these ACOG FAQs on dysmenorrhea remind me of my schooling in the old country? Well, glad you asked. Check out this gem, for example:

That's it. No follow-up questions? Good!

But really let's take it from the top. So, OK, there is the pelvic exam. I can deal with that because I am used to that as the default for anything going on "down there." Then there is the ultrasounds exam. I guess I can deal with that too because there has been so much in the news about pelvic ultrasound, and that seems to be what is done to get a better look at what is down there. A laparoscopy? Wait, isn't that a surgical procedure? Yeah, they even say it's a surgery, and it's done to get a "look inside the pelvic region." Hmmm, this sounds pretty serious. How come they don't say anything here, in these FAQs, about what they are looking for, how good this surgery is at finding it, what the chances that what they find is responsible for my dysmenorrhea, what is the treatment and how successful it is at alleviating my symptoms of dysmenorrhea, and whether or not there are alternative interventions?

(Does anyone really ask the patients what their FAQs are or are they generated by the clinicians based on what they think should be important to the patient? Or even worse, based on what they think they can give a perfunctory answer to? Just from reading these Qs and As I think it's the latter.)

You get my point. This formulation of information is beyond useless. It seems paternalistic in its "there there, dear, we will take care of everything" attitude. Perhaps I am out of touch. Perhaps women, patients in general, don't want to go beyond what their doctor tells them to do. But I happen to think that it is these FAQs that are out of touch. Granted, I am a "difficult" patient, as even a pelvic exam, let alone ultrasound and surgery, meets with questions around the evidence of its effectiveness. But even if you have only completed ePatient 101, you should know enough to ask about something as serious as a laparoscopy! How can anyone be expected to just acquiesce and, sighing, say "yes, I guess I have to have surgery." This "FAQ" is completely absurd in its willful lack of useful information. And if you read the rest of the document, you will find many places where this is true as well.

I know that some of you will read this and click away saying "oh, there she goes again." But I think you need to rethink your apathy. After all, there are well over 200,000 deaths (and possibly even more than 400,000) annually in the US that happen unnecessarily just from contact with our "healthcare" system. If you can avoid the avoidable, is it not incumbent upon you to be fully informed? You may think that all these recommendations are evidence-based, and there is not a whole lot of wiggle room in how to proceed. Well you are wrong if you think so, since the evidence, even when it is available, is rarely, if ever, unequivocal. And furthermore, in medicine no benefit comes without a risk. Are you sure you want your doctor to make these decisions for you? How is it that people who are not even willing to take wardrobe advice from their mothers wade so enthusiastically into these high-risk medical adventures with their eyes and ears closed?

I wrote Between the Lines to show just how imprecise and uncertain the science of clinical medicine is. But beyond that, I wanted to provide you with tools at least to ask the right questions. So, please, go and ask. And insist that you be included in the FAQ processes. Otherwise, we are just wasting terabytes on propaganda.

If you like Healthcare, etc., please consider a donation (button in the right margin) to support development of this content. But just to be clear, it is not tax-deductible, as we do not have a non-profit status. Thank you for your support!

What does $750 billion in wasted spending look like?

noreply@blogger.com (Marya Zilberberg) — Fri, 07 Sep 2012 12:26:00 +0000

Here is an infographic (I know) from the Institute of Medicine who just released this report. According to it, we are wasting $750 billion annually in unnecessary healthcare costs, and here is the breakdown. Note the ~$250 billion on overdiagnosis and overtreatment. Now,what are we going to do about it?

BTL reader question: How do you get to 2%?

noreply@blogger.com (Marya Zilberberg) — Tue, 14 Aug 2012 14:08:00 +0000

I have started a FAQ page on the BTL book web site here, and I will cross-post the discussion here on the blog. This will give us an opportunity to have a more interactive discussion, if necessary, with additional comments and questions.

Here is the inaugural installment.

On August 13, 2012, this question came in via Twitter:

Well, here is the answer (and thank you for the question, Tia!)

First the problem. At the bottom of page 74 and going on to the top of page 75 I discuss the question posed in a 1978 New England Journal of Medicine paper by Casscells and colleagues to 60 physicians and physicians-in-training at Harvard Medical School. The problem went like this:

"If a test to detect a disease whose prevalence is 1/1000 has a false positive rate of 5 per cent, what is the chance that a person found to have a positive result actually has the disease, assuming that you know nothing about the person's symptoms or signs?"

The question clearly mimics a disease screening situation. The answer is simple yet elusive. Let us assume that 1,000 people are tested. Among them only 1 person has the actual disease. However, given that the false positive rate is 5%, we also know that out of the 1,000 people tested, 50 will have a false positive test. Assuming that the single person with the disease also has a positive test, we can expect 51 people to test positive. But since only 1 out of these 51 people with a positive test has the disease, the answer to the question above is 1/51=2%. This is a pretty shocking realization, given that a large plurality of the Harvard doctors and trainees chose 95% as their answer.

So, be careful not to let your intuition override the data when making medical decisions!

Medicine as the trolley problem

noreply@blogger.com (Marya Zilberberg) — Wed, 25 Jul 2012 19:11:00 +0000

Are you familiar with the trolley problem? It is an ethics dilemma first formulated by the great Philippa Foot as a part of a series of such dilemmas. Her formulation goes roughly like this. Imagine there is a tram hurtling down a track. If it keeps going straight, it will hit and kill 5 people who are working on that track. The conductor is able to throw a switch and divert the train to another part of the track, where 1 single worker will be killed by the trolley. The question is what should the conductor do? Most people when asked respond that yes, he should throw the switch and sacrifice 1 life to save 5. After all, the net benefit is n=4.

There are literally thousands of alternative formulations of this problem, but one of them from the philosopher Judith Jarvis Thomson merits special consideration. The problem starts out similarly, with 5 lives on a track in potential peril. The vantage point and the solution are quite different, though. Now there is a bridge over the rail track, and a very large man is looking at the tracks from the bridge. One way to stop the train is to throw a heavy object in its path, like this large man, for example. You are on the bridge standing behind the man. Would you be justified in pushing him off the bridge in front of the tram to meet his death in order to spare the 5 workers down the tracks? Most people when faced with this formulation say an emphatic "no." This is somehow puzzling, since the net benefit is the same, n=4, as in the original Foot formulation.

Philosophy professors have puzzled over this difference for decades, and there are several potential explanations for why we respond differently to the two scenarios. One explanation has to do with the proximity of the operator (conductor in the first case and the person doing the pushing in the second) to the sacrificial lamb -- in the first case one is enough removed from the action of killing by merely redirecting the tram, whereas in the second the action is, well, more active, and the operator is actually pushing an innocent person to his death.

Though in some ways the scenarios seem to bear no practical distinction from one another, we see the morals and ethics of each differently. This difference in the view point is instructive to the field of medicine, where it has implications to how policy relates to the individual patient encounter. Here is what I mean.

Suppose you are a policy maker, and you recommend that every woman at age 40 start to receive an annual screening mammogram to reduce deaths from breast cancer. At the population level, if we screen 1,000 women for about 30 years, we will save approximately 8 of them from a breast cancer death. (Yes, it's 8, not 80, and not 800). At the same time, among these 1,000 women, there will be over 2,000 false alarms, and over 150 of these will result in an unnecessary biopsy. Some of these biopsies will incur further complications, though currently we do not seem to have the data to quantify this risk. But what if even one of these biopsies were to lead to death of or another dire lasting complication in a woman who turned out not to have cancer? And by the way the accounting is not all that different when applying the new USPSTF mammography screening recommendations. Well, then we have the trolley problem, don't we? We are potentially sacrificing 1 individual to save 8. And who does the sacrificing is where the variations of the trolley problem come in.

Payers levy financial penalties on primary care physicians when they fail to comply with screening recommendations in their patient panels. The payer certainly sees this issue as the original formulation of the problem: Why not throw this financial switch to achieve net life savings? But for a clinician who deals with the individual patient this may be akin to pushing her over the bridge toward a potentially fatal event. Because we don't have a crystal ball, we cannot say which woman will die or incur a terrible complication. But the same population data that tell us about benefits must also give us pause when reflecting on the risks. Add the ubiquitous uncertainty (and lack of data) into this equation, and the implications are even more shocking. So, while making policy recommendations based on population data is sensible, policing uniform application of these recommendations to individual patients is fraught: of course, clinicians and patients need to be cautious about making individual decisions even when in population data benefits outweigh risks.

On the surface risk-benefit equations for many interventions may appear favorable, leading to blanket policy recommendations to employ them on everyone who qualifies. In the office, the clinician, caught in a tug of war between mountains of new literature and the ever-shrinking appointment times, is hard-pressed to take the time to consider these recommendations in the context of the individual patient. And furthermore, financial incentives from payers act as a short-hand justification, a "nudge," for doing as recommended rather than for giving it thought. So, who must look out for the patient's interest? The patient, that's who. Who understands the patient's attitude toward the risks and the benefits? The patient, that's who. Who now has to be responsible for making the ultimate informed decision about which track to stand on? The patient, that's who.

For me the trolley problem gives clarity to the reservations that I walk around with every day. I have done a lot of soul searching about why it is that, even if the benefits seem to outweigh the risks, I am still more often than not skeptical about whether a particular intervention is right for me. And since every intervention in medicine has a real risk, though mostly quite low, of going terribly awry, my skepticism is justified. This is my approach to evaluating these risks and benefits, based on my values and my understanding of the data as it is today.

What's the answer to this ethical conundrum in medicine? I cannot see that policy makers will stop throwing the switch in the near future, and so as a society we will be forced to accept the tram's collateral damage. And while this may make sense in an area such as vaccination, where thousands of lives can be saved by sacrificing a very few by throwing the switch, in most everyday less clear-cut medical decisions the answer is less clear-cut. Will doctors rebel against being forced to throw some patients on the tracks in order to save some marginally larger number of others? I don't think that they have the time or the energy or the incentive to do this, since the framing of the switch-throwing is through the rhetoric of "evidence." Right or wrong, doctors are shackled by the stigma of ignorance that comes with not following evidence-based guidelines, and this may act to perpetuate blind compliance. This leaves the patients, for some of whom the right thing will be just to get themselves off the tracks altogether, far away from the hurtling trolley until its brakes are fixed.

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Early radical prostatectomy trial: Does it mean what you think it means?

noreply@blogger.com (Marya Zilberberg) — Fri, 20 Jul 2012 14:37:00 +0000

Another study this week added to the controversy about early prostate cancer treatment. The press, as usual, stopped at citing the conclusion: Early prostatectomy does not reduce all-cause mortality. But the really interesting stuff is buried in the paper. Let's deconstruct.

This was a randomized controlled trial of early radical prostatectomy versus observation. The study was done mostly within the Veterans' Affairs system and took 8 years to enroll a little over 700 men. This alone should give us pause. Figure 1 of the paper gives the breakdown of the enrollment process: 5,023 men were eligible for the study, yet 4,292 declined participation, leaving 731 (15% of those who were eligible) to participate. This is a problem, since there is no way of knowing whether these 731 men are actually representative of the 5,023 that were eligible. Perhaps there was something unusual about them that made them and their physicians agree to enroll in this trial. Perhaps they were generally sicker than those who declined and were apprehensive about the prospect of observation. Or perhaps it was the opposite, and they felt confident in either treatment. We can make up all kinds of stories about those who did and those who did not agree to participate, but the reality is that we just don't know. This creates a problem with the generalizability of the data, raising the question of who are the patients that these data actually apply to.

The next issue was what might be called "protocol violation," though I don't believe the investigators actually called it that. Here is what I mean. 364 men were randomized to the prostatectomy group, and of them only 281 actually underwent a prostatectomy, leaving nearly one-quarter of the group free of the main exposure of interest. Similarly, of the 367 men randomized to observation, 36 (10%) underwent a radical prostatectomy. We might call this inadvertent cross-over, which does tend to happen in RCTs, but needs to be minimized in order to get at the real answer. What this type of cross-over does is, as is pretty intuitively obvious, blend the groups' differences in exposure, resulting in a smaller difference in the outcome, if there is in fact a difference. So, when you don't get a difference, as happened in this trial, you don't know if it is because of these protocol violations or because these treatments are essentially equivalent.

And indeed, the study results indicated that there is really no difference between the two approaches in terms of the primary endpoint (all-cause mortality over a substantially long follow-up period was 47% in the prostatectomy and 50% in the control groups [hazard ratio 0.88, 95% confidence interval 0.71 to 1.08, p=0.22]). This means that the 12% relative difference in this outcome between the groups was more likely due to chance than to any benefit of the surgery. "But how can cancer surgery impact all-cause mortality?" you say. "It only claims to alter what happens to the cancer, no?" Well, yes that is true. However, can you really call a treatment like that successful if all it does is give you the opportunity to die of something else within the same period of time? I thought not. And anyway, looking at the prostate cancer mortality, there really was no difference there either: 5.8% attributable mortality in surgery group compared to 8.4% in the observation group (hazard ratio 0.63, 95% confidence interval 0.36 to 1.09, p=0.09).

The editorial accompanying this study raised some very interesting points (thanks to Dr. Bradley Flansbaum for pointing me to it). He and I both puzzled over this one particularly unclear statement:

...only 15% of the deaths were attributed to prostate cancer or its treatment. Although overall mortality is an appealing end point, in this context, the majority of end points would be noninformative for the comparison of interest. The expectation of a 25% relative reduction in mortality when 85% of the events are noninformative implies an enormous treatment effect with respect to the informative end points.

Huh? What does "noninformative" mean in this context? After thinking about it quite a bit, I came to the conclusion that the editorialists are saying that, since prostate cancer caused such a small proportion of all deaths, one cannot expect this treatment to impact all-cause mortality (certainly not the 25% relative reduction that the investigators targeted), the majority of the causes being non-prostate cancer related. Yeah, well, but then see my statement above about the problematic aspects of disease-specific mortality as an outcome measure.

The editorial authors did have a valid point, though, when it came to evaluating the precision of the effects. Directionally, there certainly seemed to be a reduction in both all-cause and prostate cancer mortality in the group randomized to surgery. On the other hand, the confidence intervals both crossed unity (I have an in-depth discussion of this in the book). On the third hand (erp!) the portion of the 95% CI below 1.0 was far greater than that above 1.0. This may imply that with a study that could have achieved greater precision (that is, narrower confidence intervals) we might have gotten a statistical difference between the groups. But to get at higher precision we would have needed either 1) a larger sample size (which the investigators were unable to obtain even over an 8-year enrollment period), or 2) fewer treatment cross-overs (which is clearly a difficult proposition, even in the context of a RCT), or 3) both. On the other hand (the fourth?), the 3% absolute reduction in all-cause mortality amounts to the number needed to treat of roughly 33, which may be clinically acceptable.

So what does this study tell us? Not a whole lot, unfortunately. It throws an additional pinch of confusion into the cauldron already boiling over with contradiction and uncertainty. Will we ever get the definitive answer to the question raised in this work? I doubt it, given the obvious difficulties implementing this RCT.

House appropriations bill to terminate AHRQ and prohibit funding patient-centered research

noreply@blogger.com (Marya Zilberberg) — Tue, 17 Jul 2012 21:01:00 +0000

Update 7/18/12, 3:30 PM eastern:

The Hill has reported here that the bill has cleared the subcommittee. It will be going to the full committee next week.

The $150 billion bill cuts $6.3 billion from current levels of spending in the Labor, Health and Human Services and Education Departments and is part of Republican efforts to rein in government spending – an important message for the GOP on the campaign trail.

[...]

But other areas are slashed. The bill ends President Obama’s signature Race to the Top education initiative and cuts millions from advanced appropriations for the Corporation for Public Broadcasting, which funds NPR and PBS. The agency that monitors child labor abroad is cut by 68 percent and the agency that distributes Social Security payments gets cut by $764 million. It also would cut funding for Planned Parenthood if the organization continued to provide abortions.

(Hat tip to Michael Millenson for the above link)

Yes, folks, you read that right: The House of Representatives has drafted an appropriations bill that will dissolve the AHRQ and prohibit any funding for patient-centered outcomes research (PCOR). The AHRQ is an agency that spearheads and funds healthcare safety and quality research, as well as ways to rein in the costs while expanding access. If it is eliminated, there will be no one to focus on these critical issues. This bill is truly anti-patient and the reps must be informed that they have gone too far.

Here are the names of the Appropriations Committee members, with the subcommittee members responsible for this bill in bold (via STFM):

Democratic Members

Norman D. Dicks, Washington

Marcy Kaptur, Ohio

Peter J. Visclosky, Indiana

Nita M. Lowey, New York

José E. Serrano, New York

Rosa L. DeLauro, Connecticut

James P. Moran, Virginia

John W. Olver, Massachusetts

Ed Pastor, Arizona

David E. Price, North Carolina

Maurice D. Hinchey, New York

Lucille Roybal-Allard, California

Sam Farr, California

Jesse L. Jackson, Jr., Illinois

Chaka Fattah, Pennsylvania

Steven R. Rothman, New Jersey

Sanford D. Bishop, Jr., Georgia

Barbara Lee, California

Adam B. Schiff, California

Michael M. Honda, California

Betty McCollum, Minnesota

Republican Members

Harold Rogers, Kentucky, Chairman

C.W. Bill Young, Florida

Jerry Lewis, California

Frank R. Wolf, Virginia

Jack Kingston, Georgia

Rodney P. Frelinghuysen, New Jersey

Tom Latham, Iowa

Robert B. Aderholt, Alabama

Jo Ann Emerson, Missouri

Kay Granger, Texas

Michael K. Simpson, Idaho

John Abney Culberson, Texas

Ander Crenshaw, Florida

Denny Rehberg, Montana

John R. Carter, Texas

Rodney Alexander, Louisiana

Ken Calvert, California

Jo Bonner, Alabama

Steven C. LaTourette, Ohio

Tom Cole, Oklahoma

Jeff Flake, Arizona

Mario Diaz-Balart, Florida

Charles W. Dent, Pennsylvania

Steve Austria, Ohio

Cynthia M. Lummis, Wyoming

Tom Graves, Georgia

Kevin Yoder, Kansas

Steve Womack, Arkansas

Alan Nunnelee, Mississippi

Call yours at 202-225-3121!

Here are some pertinent links, courtesy of Kenny Lin, MD, and others:
-The House press release (note they brag about defunding ObamaCare and "protecting" life in the same breath)
-The draft of the bill (see page 90)
-AcademyHealth announcement (where I learned about the PCOR prohibition)
-Statement from Mary Wooley, the President of Research!America about why this is a stupid move
-The Incidental Economist blog is compiling a list of useful projects funded by the AHRQ here

So please please please call your reps to stop this insanity!

If you like Healthcare, etc., please consider a donation (button in the right margin) to support development of this content. But just to be clear, it is not tax-deductible, as we do not have a non-profit status. Thank you for your support!

DHHS: Does this lie make me look stupid?

noreply@blogger.com (Marya Zilberberg) — Tue, 10 Jul 2012 22:26:00 +0000

Update, July 12, 4:30 PM Eastern:
Just got this extra lame reply from healthfinder:

Dear Ms. Zilberberg, Thank you for contacting healthfinder.gov.  healthfinder is a government Web site featuring prevention and wellness information and tools to help you and those you care about stay healthy. At healthfinder.gov, you will find:
·         interactive tools like menu planners and health calculators
·         online checkups
·         printable information that you can share with a family member or take to the doctor.
healthfinder.gov is coordinated by the Office of Disease Prevention and Health Promotion (ODPHP), U.S. Department of Health and Human Services and the National Health Information Center (NHIC). NHIC links people to organizations that provide reliable health information. All of healthfinder.gov’s topics and tools go through subject matter expert reviews. As a result of these reviews, sentences and wording sometimes get updated and/or changed. This particular topic has already been reviewed, and the content team will be rewording the language; the word “best” will be removed from that sentence. This change will be reflected on the site in the next scheduled healthfinder.gov update. Sincerely,
healthfinder.gov TeamNational Health Information Centerhealthfinder.gov is coordinated by the Office of Disease Prevention and Health Promotion (ODPHP), U.S. Department of Health and Human Services and the National Health Information Center (NHIC).

HOW ABOUT INCLUDING A DISCUSSION OF SAFE SEX?!!!!!!! Idiotic.

Update July 11, 10:50 AM Eastern:
I have just sent the following e-mail to healthfinder.gov at the address healthfinder@nhic.org. I urge everyone who reads this to send them the same or a similar message. And if you do, please, leave a comment below to let everyone know.

Hello,

I wanted to let you know that the information you posted on this web page on Pap testing is erroneous and misleading. Telling women that the "best" way to prevent cervical cancer is through a regular Pap test is not supported by evidence. The "best" way is to prevent HPV infection by engaging in safe sexual intercourse. As a public health communicator you are doing a tremendous disservice to the public.

I urge you to change this message to reflect reality.

Thank you.

Marya Zilberberg, MD, MPH, FCCP

There is pounding in my temples, my back muscles are in a spasm, and I might even be turning green and busting out of my clothes. What caused all this? This innocent-looking tweet from the Department of Health and Human Services:

I had to do a double take. My blood started to boil almost immediately. But I persisted, clicked on the link, and saw this:

The first sentence really says "The best way to prevent cervical cancer is to get regular Pap tests." Jaw, meet floor. What does the word "prevent" really mean? I went to The Free Dictionary for enlightenment:

Just as I had suspected: to avert, to keep from happening. And how does a Pap test keep the cancer away? It finds "abnormal cells before they turn into cancer." And where do abnormal cells come from? God, right? Well, no, they are mostly associated with an HPV infection, which comes from exposing yourself to unprotected sexual intercourse, usually with someone whose HPV status you don't know. You see where I am going with this? The message here is that there is nothing more effective at preventing cervical cancer than having a Pap test to detect early changes and lop out the misbehaving piece of your cervix. Are they serious? Is this really the "best way"? Let's examine the meaning of "best":

I guess beauty (and value) are in the eye of the beholder. Does subjecting yourself to a surgical procedure that may leave your cervix unable to help your uterus to maintain a pregnancy qualify as "surpassing all others in excellence" or as "most desirable"? Not in my book, not when a little advanced planning and a nickel for a condom could could keep that horse from leaving the barn in the first place. True prevention does not take place in a doctor's office, and it is a mistake to equate screening to prevention.

Come on, DHHS, who writes your stuff? Fire them! You are risking your credibility. What's next? "Bulimia is the best way to prevent obesity"?

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Drugs and devices: expensive. Hubris: priceless.

noreply@blogger.com (Marya Zilberberg) — Mon, 02 Jul 2012 21:24:00 +0000

This morning I was listening to the Morning Edition on NPR, and heard a story about the tax on medical devices that is written into the healthcare law. As you can imagine, there is opposition to such a tax by the manufacturers, as they are concerned about the usual, "stifling innovation" (yawn). It's hard to be amused by anything to do with healthcare these days, but here is a part of the conversation that had me in LOLZ (my 14-yo's expression):

ARNOLD: Okay. So here's how this new tax works. When a medical device gets sold, there will be a 2.3 percent sales or excise tax. Now, people who support this tax say that the medical device makers are exaggerating about the impact. Paul Van de Water is an economist with the left-leaning Center on Budget and Policy Priorities. He says that this tax is basically the same as a sales tax that you pay at the grocery store.

PAUL VAN DE WATER: The grocery store is collecting the tax. The grocery store is the institution that sends the tax to the state government, just the way the medical device manufacturer is going to write the check to the Treasury.

ARNOLD: Van de Water says that the tax doesn't really target the medical device makers that much. They'll just pass most of the cost along to their customers, who are mostly big hospitals, the same way a grocery store charges their customers. But the industry disagrees. David Nexon is with the medical device trade group called AdvaMed.

DAVID NEXON: There's a difference between a tax that, you know, an individual consumer pays as opposed to one that you're negotiating a price with a large, sophisticated buyer.

ARNOLD: In other words, Nexon says a hospital chain will push back and resist paying anything extra.

NEXON: In this very competitive market, it's extremely difficult for our members to raise prices.

Hah! Is he saying what I think he is saying? That because individual consumers are too dumb to understand about externalizing additional expenses, such as taxes, it is easier to put one over on them than on the savvy hospitals? Could he possibly mean that only "large, sophisticated buyers," and not ordinary consumers, would never stand for the information asymmetry they thrive on? That the individual consumers just don't have the power that hospitals do to push up against potentially predatory pricing?

The last time I heard or read anything this blatant was in this New York Times piece from December 2009. This is a company executive talking about the rationale for the company's cancer drug's disproportionately steep price:

Mr. Caruso also said the price of Folotyn was not out of line with that of other drugs for rare cancers. Patients, moreover, are likely to use the drug for only a couple of months because the tumor worsens so quickly, he said. So the total cost of using Folotyn will be less than for many other drugs with lower monthly prices.

Wow, do these people get paid to advance their organizations' agendas? For my money they are not doing such a hot job at anything other than confirming all the societal views of them. Are they too stupid to realize that, even if you think stuff like this, you shouldn't say it out loud? How embarrassing.

Bottom line? Their drugs and devices: expensive. Their hubris: priceless.

If you like Healthcare, etc., please consider a donation (button in the right margin) to support development of this content. But just to be clear, it is not tax-deductible, as we do not have a non-profit status. Thank you for your support!

Molecular diagnostics: Making the uncertainties more certain?

noreply@blogger.com (Marya Zilberberg) — Fri, 29 Jun 2012 22:41:00 +0000

Scott Hensley over at the NPR's Shots blog posted a story about the recently approved molecular diagnostic test that can rapidly identify several gram-positive bacteria that cause blood stream infections. This is indeed important, since conventional microbiologic techniques rely on bacterial growth, which can take up to 2 to 3 days. This is too long to wait to identify the bug that is the cause of a serious infection. What doctors have done to date is make the best guess based on several factors, including the type of a patient, the source of the infection and the patterns of bacterial resistance at their site, to tailor empiric antibiotic coverage. The sicker the patient, the broader the coverage, until the culture results come back, when the doctor is meant to alter this treatment accordingly, either by narrowing or broadening the spectrum. The pitfalls of this work flow are obvious -- too many points where error can enter the equation. So on the surface the new tests are a great advance. And they actually are, but they are not free of problems, and we need to be very explicit confronting them.

Each diagnostic test can be evaluated on its sensitivity (how well it identifies the problem when the problem exists), specificity (how rarely it identifies a problem when it does NOT exist), and positive (what proportion of all positive tests represents true problem) and negative (what proportion of all negative tests represents a true absence of problem). Sensitivity and specificity are intrinsic properties of the test and can be altered only by how the test is performed. Positive and negative predictive values are dependent not only on the test and how it is done, but also on the population that is getting tested.

Let's take Nanosphere's test in Scott's story. If you trawl the company's web site, you will find that the sensitivity and specificity of this technology is close to 100%, if not 100%, the "gold standard" for comparison being conventional microbiology culture. And perhaps this is really the case in these very specialized hands that were testing the diagnostic. If these characteristics remain at 100%, disregard the rest of this post, please. However, the odds that they will remain at 100% in the wild of clinical practice are slim. But I am willing to give them 99% on each of these characteristics nevertheless.

OK, so now we have a near-perfect test that is available for anyone to use. Imagine that you are an ED doc at the beginning of your shift. An ambulance pulls up and rolls a septic patient into an empty bay. The astute ED nurses rush into settle the patient, and, as a part of the protocol, take a sample of blood for determining the pathogen that is making your patient sick. You quickly start the patient on broad spectrum antibiotics and walk away to take care of the next patient that has just rolled in with a heart attack. A few hours later, the septic patient, who is still in the ED because there are no ICU beds for him yet, is pretty stable, and you get the lab result back: he has MRSA sepsis. You pat yourself on the back because one of the antibiotics that you ordered was vancomycin, which should cover this bug quite adequately. You had also put him on ceftazidime to cover any potential gram-negative critters that may be lurking within as well. Now that you have the data, though, you can stop ceftaz and just continue vanc. The patient finally gets a bed upstairs, and your shift is over and you go home withe a sense of accomplishment.

The next morning you come in refreshed with your double-venti iced macchiato in your hand, sit at the computer and check on the septic patient. You are shocked to find out that last night he decompensated, went into shock and is now requiring breathing assistance and 3 vasopressors to maintain his blood pressure. You scratch your head wondering what happened. Then you come upon this crazy blog post that tells you.

Here is what happened. What you (and these tests) did not take into account is the likelihood of MRSA being the real problem rather than just a decoy false positive. Let's run some numbers. The literature tells us that the likelihood of MRSA causing sepsis is on the order of 5%. Let's create a 2x2 square to figure out what this means for the value of a positive test, shall we?

	MRSA present	MRSA absent	Total
Test +	495	95	590
Test -	5	9405	9410
Total	500	9,500	10,000

What this says is the following. We have 10,000 patients roll into our ED with sepsis (in reality there are about 1/2 million to 1 million sepsis cases in the US annually), and we test them all with this great new test that has 99% sensitivity and 99% specificity. Of these 10,000, ~~fifty~~ five hundred (thanks, Brad, for noticing this error!) are expected to have MRSA. Given this situation, we are likely to get 590 positive tests, of which 95, or 16%, will be false positive. Face-palm, you drop your head on the desk realizing that Mr. Sepsis from yesterday was probably one of these 16 per 100 false positives, and MRSA is probably not the cause of his infection.

You begin to wonder what if your lab really did not get the sensitivity and specificity of 99%, but more like 98%? Still pretty generous, but what if? You start writing madly on a napkin that you grabbed at Starbucks, and your jaw drops when you see your 2x2:

	MRSA present	MRSA absent	Total
Test +	490	190	680
Test -	10	9310	9320
Total	500	9,500	10,000

Wow, you think, this false positive rate is now nearly 30% (190/680)! You can't believe that you could be jeopardizing your patients' lives 3 times out of 10 because you are under the mistaken impression that they have MRSA sepsis. This is unacceptable. But can you really trust yourself with these calculation? You have to do one more thing to convince yourself. What if your lab only gets 97% specificity and sensitivity? What then? You choke when you see the numbers:

	MRSA present	MRSA absent	Total
Test +	485	285	770
Test -	15	9215	9230
Total	500	9,500	10,000

It's and OMG moment -- nearly 40% would be treated for MRSA when they potentially have something else.

But you, my dear reader, realize that in the real world docs are not that likely to remove gram-negative coverage if MRSA shows up as the culprit pathogen. Why should you think otherwise, when there is so much evidence that people are not that great about de-escalating antimicrobial coverage in response to culture data? But then I have to ask you what's the use of this new test if no one will act on it anyway? In other words, how is it expected to help curb the rise of resistance? In fact, given the false positive MRSA rates we see above, might there not even be a paradoxical increase in the proliferation of resistance?

The point is this: We are about to see many new molecular diagnostic technologies on the market that have really really high sensitivity and specificity. The fly in this ointment, of course is the pre-test probability of the bug causing the problem. Look how in a very low risk group (5% MRSA) even a near-perfect test's value of a positive is reduced by almost a ridiculous magnitude. Do feel free to check my math.

So you trudge into the hospital the next day for your shift and check on Mr. Sepsis one more time. Sure enough, his conventional blood culture grew out E. coli, a gram-negative bug. You notice that he is turning around, though, ceftazidime having been restarted by the astute intensivist (well, I am a bit biased here, of course). All is well in the world once again. Except you hear an ambulance pull up and the nurse talking on the phone to the EMTs -- it's another sepsis on your hands. What are you going to do now?

If you like Healthcare, etc., please consider a donation (button in the right margin) to support development of this content. But just to be clear, it is not tax-deductible, as we do not have a non-profit status. Thank you for your support!

ACA: The reports of its death were greatly exaggerated

noreply@blogger.com (Marya Zilberberg) — Thu, 28 Jun 2012 18:06:00 +0000

This is a big day for President Obama's signature legislation, the Affordable Care Act. The Supreme court upheld its constitutionality, and the punditdom thinks that further challenges are unlikely. On the other hand, if Romney takes the White House in the next election... Well, you can guess what will happen then.

It has been interesting to watch the run-up to this decision. Most recently I have been amused by surveys finding that on the one hand many American people are in favor of the pre-existing condition inclusion (this part of the bills forbids insurance companies to discriminate against people with prior health conditions), as well as the provision that allows young adults to stay on their parents' insurance policies through a certain age. On the other hand, reportedly the majority of Americans are against the healthcare law, and most also oppose the individual mandate provision (this is the part where everyone has to buy insurance or pay a tax). Given this imbalance in the public opinion, a more pertinent survey should have assessed how well people understand these provisions in the first place. And this would have had to establish how well the public gets our whole healthcare "system."

To start from the beginning, any healthcare system can be judged on three criteria:
1. How accessible is it?
2. Is it of adequate quality?
3. How expensive is it?

The answer to the first question provides one of the rationales for the individual mandate. Currently there are about 50 million people without health insurance in the US, and, hence, without adequate access to the system. Many of these people are the young and the healthy who gamble on staying young and healthy. And many are consigned to relying on expensive emergency care when this gamble fails. Some of them go bankrupt trying to pay for it, while others become "safety net" cases, where the institution that cares for them swallows the costs. These institutions do get some public dollars for providing safety net care, but not nearly enough to break even. Since many of the 50 million don't buy health insurance because they cannot afford it, the healthcare bill provides a way to create more affordable insurance products.

The answer to the second question is not related directly to the individual mandate. Since much of this blog is devoted to the issues of healthcare-associated harm, I do not wish to belabor this point here. Suffice it to say that the bill does try to address this catastrophic situation, though it remains to be seen if it will succeed.

The third question is the crux of the story. Many have said that the escalation of healthcare costs is unsustainable, and I subscribe to this notion: I am not sure how much more than $2.6 trillion/year we want to pay for this insatiable beast. Yet judging by the near-revolt that "death panels" rhetoric caused, the citizenry is not interested in being thoughtful about what services make sense. The vehement knee-jerk to the "R"word shuts down the discussion before it even starts. So, OK, how do we pay this ever-increasing bill? Moreover, since we are all happy with the government mandate for all insurance to pay for pre-existing conditions, how do we propose to pay for this additional coverage? Short of printing money (not generally a good idea) or creating a single-party payer system that regulates these expenditures, the only way is to broaden the pool of revenue. The way the ACA has proposed to broaden this pool is through the very individual mandate that is anathema to our American way of life. But without it, there is no broadening of coverage, and there is no paying for every intervention that we seem to feel entitled to.

I doubt very much that the ACA will substantively contain healthcare costs. I even doubt that it will solve the quality problems, but I am willing to wait and see on that. This bill is but s band-aid on an arterial bleed. However, I do believe that upholding this legislation allows us to take the first steps toward a reasonable national dialog about the kind of healthcare system we need. This dialog will not be helped by stupid surveys that reinforce our willful ignorance. We have the opportunity to move this conversation to a higher level, where people begin to understand the issues we are up against more deeply. Let's take it.

If you like Healthcare, etc., please consider a donation (button in the right margin) to support development of this content. But just to be clear, it is not tax-deductible, as we do not have a non-profit status. Thank you for your support!

Peeling the cabbage of "works" in treatment interventions

noreply@blogger.com (Marya Zilberberg) — Tue, 26 Jun 2012 13:23:00 +0000

What exactly does it mean when we say that a treatment works? Do we mean the same thing for all treatments? Are there different ways of assessing whether and how well a treatment works? I am sure you've guessed that I wouldn't be asking this question if the answer were simple. And indeed, the answer is "it depends."

What I am talking about is examining outcomes. I did a post a couple of years ago here, where I use the following quote from a Pharma scientist:

"The vast majority of drugs - more than 90 per cent - only work in 30 or 50 per cent of the people," Dr Roses said. "I wouldn't say that most drugs don't work. I would say that most drugs work in 30 to 50 per cent of people. Drugs out there on the market work, but they don't work in everybody."

Here is that word "work" again. What does this mean? well, let's take such common condition as heart disease. What does heart disease do to a person? Well, it can do many things, including give him/her such symptoms as a chest pain, shortness of breath, dizziness and palpitations, to name a few. These symptoms may have at least two sets of implications: 1) they are bothersome to the individual, and in this way may impair his/her enjoyment of life, and 2) they may signal either a present or a future risk of a heart attack. Why are heart attacks important? Well, they are important because one may kill the person who is having it, or one (or several) may weaken the heart to the point of a substantial disability and thus a deterioration in the quality of life. So, there certainly seems to be a good rationale to prevent heart disease either from happening in the first place or from at least worsening when it's already established.

Now, what's available to us to prevent heart disease? Well, some think that lowering one's cholesterol is a good thing. OK, let's go with that. What is the sign that the statins (cholesterol-lowering drugs) "work"? What would it look like if it was about lowering the cholesterol? Say, your total cholesterol is 240. You go on a statin and in 6 months your total cholesterol is 238. Your cholesterol was lowered, it worked! Well, yes, but if you are asking what this 2-point drop really accomplishes, you are beginning to understand the meaning of "work." So, just intuitively we can say that there needs to be a certain, perhaps "clinically significant," drop in the total cholesterol in order for us to say that the drug "worked."

Great! Now we are sidling up to the real issue: What constitutes a "clinically significant" drop in cholesterol? Is it some arbitrary number that looks high enough? Probably not. How about some drop that correlates to a drop in the risk of the actual condition we are trying to impact, heart disease? Say, a 40-point drop, or getting to below 200, may be the right threshold for the "works" judgment. Ah, but there is yet another question to ask: How often does this type of a drop lead to a reduction in heart disease? Is it always (not likely), or is it the majority of the time (rarely) or at least some of the time (most likely in clinical medicine)? And what portion of that time do we consider satisfactory -- 60%? 40%? 20%? 2%?

Let me bring just one more layer into this discussion. Many people walk with heart disease and don't know that they have it. Some of these people are destined to have a heart attack and/or die from it. Many others are likely to die from something else before they ever experience any symptoms or signs of their heart disease. This raises the question of whether the statins' ability to reduce cholesterol and hence reduce the risk of heart disease is enough to say that the drugs "work." Perhaps "work" means that by lowering cholesterol (say in the majority of those who take it) they reduce the risk of hear disease in some proportion of those who are at risk for it, and among that proportion whose risk is reduced they also reduce the risk of a heart attack in a few, and of death in even fewer.

So, to sum up, "works" is a loaded term. For the case we are discussing, there is what I call a "dwindle" effect, where the main outcome, cholesterol lowering, is likely to show a somewhat robust result. On the other hand, this (surrogate) outcome itself is not all that interesting when divorced from what we really care about -- symptoms, heart attacks and death. And I haven't even gone into the side of the equation where the patient gets to decide what "work" means for him/herself. The layers of the possible "works" are a cabbage that we all need to peel when discussing treatment plans with our clinicians and when reading news about new technologies.

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Thank you for your support

noreply@blogger.com (Marya Zilberberg) — Mon, 25 Jun 2012 13:18:00 +0000

A few moths ago I quietly put a "Donate" button in the right margin of my blog. It was an experiment to see what it can do just by sitting there. But now that I have had a few donations come my way, I feel the need to explain why I decided to solicit donations.

I have now been blogging for a little over three years, and have a small but loyal following. One of the ways I have considered to support my blogging is by allowing ads and sponsorships on the site. Having considered that, I have ruled it out as a possibility for the moment. The reason is simple: even if I manage not to give in to the cognitive biases created by a financial relationship, there will still be the hazard of a perception of conflict. And I prefer to keep my blogging free of such real or imagined conflicts.

At the same time, when I do a meaty post, I spend considerable time on it, and often wish I had more time and resources to spend. So, I thought that direct donation through the site might be a good way to support my blogging.

The posts that seem most valuable, those deconstructing studies, take the longest time and the most effort to do. And it's no wonder: The amount of misinformation that is available to us is staggering, and it is not always clear how to filter it. Although I acknowledge that my interpretations are still informed by my own (conscious or unconscious) cognitive biases, I try to be as transparent as possible about where I am coming from.

Thank you all for your support and for encouraging me to continue this work.

So, if you like Healthcare, etc., please consider a donation (button in the right margin) to support development of this content. But just to be clear, it is not tax-deductible, as we do not have a non-profit status. Thank you for your support!

Unstructured medical record: Another case of "not everything that counts can be counted"?

noreply@blogger.com (Marya Zilberberg) — Thu, 21 Jun 2012 16:13:00 +0000

Have you ever wished that instead of choosing a single answer on a multiple choice exam you could write an essay instead to show how you are thinking about the question? It happened to me many times, particularly on my medical board exams, where the object seemed more to guess what the question writers were thinking than to get at the depth of my knowledge. And even though each question typically had a menu of 5 possible answers, the message was binary: right vs.wrong. There was never room for anything between these two extremes. Yet this middle ground is where most of our lives take place.

This "yes/no" is a digital philosophy, where strings of 0s and 1s act as switches for the information that runs our world. These answers are easily quantifiable because they are easily counted. But what are we quantifying? What are we counting? Has the proliferation of easily quantifiable standardized testing led us to more and deeper knowledge? I think we all know the answer to that question. Yet are heading in the same direction with electronic medical data? Let me explain what I mean.

There was an interesting discussion yesterday on a listserv I am a part of about structured vs. unstructured (narrative) clinical data. I don't often jump into these discussions (believe it or not), but this time I had to make my views heard, because I believe they are similar to the views of many clinicians.

My understanding of one of the comments was that the narrative portions of the medical record are less valuable, since they are more difficult to digitize, and, therefore, do not represent data per se. The narrative, it was stated, serves more as a memory and communication aid for the clinician, and furthermore it frequently misses patient perspective. Right or wrong, what I walked away with is that "narrative parts of the record are not as valuable as the structured parts."

I responded:

Isn't the point of the narration to synthesize the structured data into a coherent whole that feeds into the subsequent plan? I completely agree that the patient perspective is often missing, but the two are not mutually exclusive. In fact, I see the synthesis of both narratives giving rise to most valuable interpretation and channeling of the "objective" data.

When I was in practice, I often had patients referred to me in consultation for lung issues. And while the S and O parts of the SOAP note (Subjective, Objective, Assessment, Plan) lent themselves relatively naturally to structured data, the A and P parts really did not. In the A I waxed poetic about how the S and the O fit together for me and why (why I thought that diagnosis X was more likely than diagnosis Y), and in the P I discussed why I was making the recommendations I was making. And while... this was a way to communicate with other docs and to jog my memory about the patient when I saw him/her next, this was the most valuable part for me, since it had already contained the cognitive piece of the process. And yet this was the part that was most challenging to fit into a predetermined structure of a EMR.

The richness of patient participation would come in a dialogue between clinicians and their patients, which I still think requires a narrative, no?

And then someone else piped in and talked about two-dimensional holes being forced to hold the multidimensionality of our health and being, and the disruption that this represents. And I have to say this is exactly my recollection of my interactions with the (very early) EMR that my group adopted. I had loved to sit and write my SOAPs by hand, even the S and the O, but especially the A and the P. There was something about the process that solidified and imprinted for me the particular patient. The printed dictation was secondary to that somehow, and I always tended to refer to my hand-written note. This is how I knew my patients. That was slow medicine.

Perhaps this was a byproduct of how I grew up -- largely analog, not anywhere near as digital as the younger generations, and much more inclined to put my thoughts on paper through the interaction of my brain, hand and pen. Strangely, today I have a hard time writing by hand, and my preferred method is to type on my keyboard. So, perhaps some brain rewiring has taken place. All I can say is this: for me the act of writing down my thoughts about the patient made the encounter real and memorable. Even more, I think it lent a certain level of respect to the individuality of each encounter. It is possible that if I were in practice today, I could achieve the same by typing my note.

But the writing medium is somewhat separate from "structured vs. unstructured" data. The "ideal" structured record is all about yes/no checkboxes. Having to fit our analog thoughts into such limited and limiting digital environment is distracting. And a lot of data from brain science suggest that it takes us a while to get back to the same level of focus on a task or a thought once we have been distracted. A clinical encounter is woefully brief, and these distractions can and do reduce its efficiency and integrity.

As a health services researcher, I rely on digital data for my work. Yet as a clinician I railed against it, as many clinicians continue to do today. Is the answer to abandon all electronic pursuits? Of course not. But I am baffled by the attitude that it is clinicians' duty to adapt to the digital way of thinking rather than the other way around. There does not seem to be a recognition that the purpose and meaning of a clinical record is different to a clinician from what it is to a researcher or a policy maker. Yet the current EMR development seems to focus on the latter two constituencies virtually ignoring the clinical setting. Given our vastly improved computing capabilities over the last decade, why does a clinician still have to think like a computer? Moreover, if medicine is indeed a mix of art and science, do we really want our doctors to fit strictly into the digital model?

I believe that it is a lazy way out for developers. They are the ones that need to step up and create an electronic record that does not gratuitously disrupt the clinical encounter. This record needs to fit the work flow of clinical medicine like a glove. We cannot wait for some miracle to come along and magically transform our sick healthcare system. Today's EMR will not succeed unless it takes into account the art of medicine. The narrative parts of the record must be preserved and enriched by patient collaboration, not eliminated in the interest of easy bean counting. Because several smart people tell us that "not everything that counts can be counted, and not everything that can be counted counts." It's time to pay attention.

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Plagiarism and advertising and COI, oh my!

noreply@blogger.com (Marya Zilberberg) — Fri, 15 Jun 2012 15:00:00 +0000

Update #4, 7:45 AM Eastern, Sunday, June 17 (Happy Father's Day, everyone!)
As of this morning, the HealthWorks Collective has taken down the story as well. What is interesting to me is that neither OneMedPlace nor HealthWork Collective has put any explanation on their respective site, and the reader is essentially consigned to finding "ERROR 404." I sure hope that this is not either of the organization's attempt to sweep the whole thing under the rug.

Update #3, 6:00 PM Eastern (and last for tonight, I hope)
Another e-mail from Matt Margolis, in which he requested that I let my readers know that

...we took down our piece after an internal discussion, before you and I made any contact. Hence my request to remove a reference to us.

Still no answer on Aviisha -- perhaps it will appear in the "similar piece" they are planning to publish next week. looking forward to it.

Update #2, 4:35 PM Eastern
Another exiting update for y'all. A few hours ago I got a message from a Matt Margolis at OneMedPlace informing me that the company has taken the post down after realizing their mistake. Well, why don't I just share the whole message (emphasis mine)?

Hello Marya,

Thank you for reaching out to us. We quickly realized there was an error in attribution and have since pulled the story. We would appreciate at this time that you do not include our name or our article in your post. However, we will be publishing a similar piece next week that will incorporate some of the facts in the NYT story. At which time, I am happy to answer any questions to help give depth to your piece.

Best,

Matt Margolis

Managing Editor, OneMedPlace

I responded asking for "more depth" with respect to whether Aviisha is a client of OneMedPlace. I will let you know what I hear when I hear it. And by the way, the HealthWorks Collective still has the story on its page.

Update #1, 1:45 PM Eastern
As of right now, the OneMedPlace story page has been taken down. No one from OneMedPlace has communicated with me at this point. The story is still up on the HealthWorks Collective site here.

About four years ago I decided that it was time to learn more about the recent abundant advances in brain science. Since then, I have read avidly on our neurobiology, behavioral economics and decision science. I have learned about our predictable irrationality, biophilia, heuristics and biases, and our drive to create linear explanations for phenomena where none exists. I also learned about priming, where subtle messages delivered prior to a task's completion (did you know that you can, for example, get kids to improve more on their exams by commending their hard work than their native brilliance?) influence the outcome of the task.

It is in this context of (some) understanding about how the human brain assembles its information pathways that I read this story from yesterday's OneMedPlace News (also reprinted by The HealthWorks Collective here under the byline of Herina Ayot, the Managing Editor for OneMedPlace). This story about a correlation between severe sleep apnea and cancer, starts out thusly:

Two new studies have found that people with sleep apnea, a common disorder that causes snoring, fatigue and dangerous pauses in breathing at night, have a higher risk of cancer. The new research marks the first time that sleep apnea has been linked to cancer in humans.

About 28 million Americans have some form of sleep apnea, though many cases go undiagnosed.

[...] For sleep doctors, the condition is a top concern because it deprives the body of oxygen at night and often coincides with cardiovascular disease, obesity, and diabetes.

All of this is true and truly concerning. The next two paragraphs state

In light of the recent studies, Aviisha Medical Institute, LLC is taking $200 off the cost of its home sleep test, which was originally $449.49, and offering free assessments for the duration of May. The special offer is intended to encourage the public to get tested for sleep apnea and raise awareness about the deadly consequences of untreated apnea. Studies estimate that 85% of sleep apnea sufferers don’t know they have the condition.

One may speculate that other diagnostic technologies developers may promote offers in light of this newfound cancer correlation, as well.

This is when I got a little uncomfortable thinking that this is an advertisement rather than a story. And the final statement really got my hackles up:

Although the study did not look for it, study author Dr. Miguel Angel Martinez-Garcia, of La Fe University and Polytechnic Hospital in Spain, speculated that treatments for sleep apnea like continuous positive airway pressure, or CPAP, which keeps the airways open at night, might reduce the association.

And how does sleep apnea cause cancer?

Lead author Dr. F. Javier Nieto, chair of the Department of Population Health Sciences at the University of Wisconsin School of Medicine and Public Health, commented that five times the risk of cancer is more than just a statistical anomaly. Previous studies in animals have shown similar results, while other studies have linked cancer to possible lack of oxygen or anaerobic cell activity over long periods of time, therefore, it’s possible poor breathing fails to oxygenate the cells sufficiently.

But then even more happened. From the very beginning of the article, I had sensed something familiar in it. It was my recollection that I had seen this story before about the two studies presented at the American Thoracic Society last month. Dutifully clicking on the link provided in the first paragraph of Ayot's story, I found myself on the NYT's "Well" blog reading the post from May 20, 2012, by Anahad O'Connor. Here is how it starts:

Two new studies have found that people with sleep apnea, a common disorder that causes snoring, fatigue and dangerous pauses in breathing at night, have a higher risk of cancer. The new research marks the first time that sleep apnea has been linked to cancer in humans.

About 28 million Americans have some form of sleep apnea, though many cases go undiagnosed. For sleep doctors, the condition is a top concern because it deprives the body of oxygen at night and often coincides with cardiovascular disease, obesity and diabetes.

And then, disappointingly, toward the end of the post:

Although the study did not look for it, Dr. Martinez-Garcia speculated that treatments for sleep apnea like continuous positive airway pressure, or CPAP, which keeps the airways open at night, might reduce the association.

A couple of things shocked me (in addition to the final statement about CPAP):
1). Ayot's story was almost verbatim (with the exception of the Aviisha advertisement) reprinted from O'Connor's story. There did not seem to be an attribution, unless linking the the original post counts as one. Please, someone who is well versed in this, tell me if this is an acceptable way to attribute. I'll tell you now that in the academic circles this would be (and has been) called plagiarism. As you may recall, I am pretty sensitive to this, having had my work plagiarized recently.
2). The thinly veiled advertisement (inserted into the body of this story which is practically copied from the NYT word for word). The advertisement would not bother me if it had stayed on the OneMedPlace web site -- after all they seem to be a PR agency. But is was reprinted on the HealthWorks Collective's site as a legitimate news item, and I don't believe that HWC is a purveyor of advertorials.

I browsed the web site of Ayot's employer OneMedPlace to see if there is evidence that Aviisha is a client, but did not find any, though my search was admittedly perfunctory. I have reached out to the company for a comment and to understand whether a conflict of interest may exist with Aviisha, but have not heard from them at this time. I will update the post if and when I hear from them.

So drawing on my limited understanding of how the brain works, here is what I am thinking this piece aims to accomplish:
1). Create an awareness of a condition that is apparently common and largely undiagnosed, and do it using words from a high-impact publication
2). Prime the reader with the idea that we understand how it causes cancer (if only in laboratory animals, maybe)
3). Set up Aviisha (and "other diagnostic technology developers") as solution providers
4). Create a linear path to CPAP as the answer

But this is just my uneducated guess at how the human brain may perceive this story. Of course, I could just be playing right into my cognitive biases.

If you like Healthcare, etc., please consider a donation (button in the right margin) to support development of this content. But just to be clear, it is not tax-deductible, as we do not have a non-profit status. Thank you for your support!

A FORCE against disease mongering

noreply@blogger.com (Marya Zilberberg) — Wed, 13 Jun 2012 13:27:00 +0000

Have you been over to The Oransky Journal lately? If not, go and see what is happening there. What is happening is a microcosm of the larger debate we are having about detection and diagnosis of real disease versus overdiagnosis of phantom conditions whose treatment is worse than anything that the potential disease may deliver.

The issue is as follows. In his talk at TEDMED in April, Ivan gave an excellent and measured presentation about the folly of pre-disease classifications and the harm they can bring. As my readers are well aware, this is the subject of great interest to me -- after all, it is a travesty that contact with the so-called "healthcare" system is the third leading cause of death in the US, and that overtreatment costs us at least 10 cents of each healthcare dollar, and probably much more (you will find a slice of my posts on this issue here). So, Ivan's talk was timely and cogent.

After he posted the talk on his blog, he received a letter from a group called FORCE (Facing Our Risk of Cancer Empowered) who, as it turns out, coined the word "previvor," one of the many words Ivan used to illustrate the philosophy of disease mongering. The letter voiced a vigorous objection to Ivan's use of the word to "misunderstanding" its meaning. But what really happened?

Apparently, "previvor" defines a group of people who are at a heightened risk for cancer, but have not yet been diagnosed. It seems that the majority of FORCE's constituency consists of women with the BRCA gene mutations, which put them at an extraordinarily high risk of several cancers, most notably breast and ovarian. Moreover, these cancers tend to occur at an early age, and are generally quite a bit more aggressive than those not associated with these mutations. We are not talking a trivial rise in the risk either; BRCA1, for example, raises one's lifetime risk for breast cancer to about 80%! To mitigate this risk, many women with these types of mutations undergo prophylactic mastectomies and oophorectomies. These are life-changing events, and their genetic make-up hangs like a Damocles' sword over the offspring of these women as well. So, what's the problem with using whatever word suits them?

The issue is the group's definition of this neologism "previvor." As quoted in Oransky's post (italics mine):

“Cancer previvors” are individuals who are survivors of a predisposition to cancer but who haven’t had the disease. This group includes people who carry a hereditary mutation, a family history of cancer, or some other predisposing factor. The cancer previvor term evolved from a challenge on the FORCE main message board by Jordan, a website regular, who posted, “I need a label!” As a result, the term cancer previvor was chosen to identify those living with risk. The term specifically applies to the portion of our community which has its own unique needs and concerns separate from the general population, but different from those already diagnosed with cancer.

So, the definition is quite broad, as you can see, especially the "some other predisposing factor." Who doesn't have one? Just by virtue of being alive we have predisposing factors to many diseases, including cancer. And aging is one of the strongest predisposing factors to cancer as well. The concern is that a broadly defined term like this plays right into our national paranoia about our health and our enthusiasm for screening as the primary mode of prevention. And if you really don't feel well informed about why screening is not all it's cracked up to be, I urge you to dig through the annals of this site thoroughly (if you don't have much time, you can get a solid primer on the issue from my book). In my view, given the extent of the harm from overdiagnosis and overtreatment, Oransky's call-out of this word in the ultra-visible forum of TEDMED was a public service.

And indeed, it turned out this public service has gone well beyond just delivering the information. The discussion that ensued over the last couple of days with FORCE has shown what this organization is made of. An 80% lifetime risk of breast cancer is a grave matter, and the group is an important force in advocating for these patients and supporting their families. But as it turns out, it stands for even more than that. I commend Dr. Friedman, the Executive Director of the group, for being open to narrowing the definition of the term "previvor." This willingness signifies a real desire to do the right thing not only for her constituency, but also for the public at large. Even more, she should be proud that her organization is taking a stand against disease mongering.

If you like Healthcare, etc., please consider a donation (button in the right margin) to support development of this content. But just to be clear, it is not tax-deductible, as we do not have a non-profit status. Thank you for your support!

Healthfinder.gov: Education or indoctrination?

noreply@blogger.com (Marya Zilberberg) — Tue, 12 Jun 2012 14:36:00 +0000

Ever heard of healthfinder.gov? It's a web site from the US Department of health and Human Services

...where you will find information and tools to help you and those you care about stay healthy.

Sounds like a laudable goal, right? Great! Now, help me! Here is the "help" that I found when I went to the page called "Colorectal Cancer Screening: Questions for the doctor":

What do I ask the doctor?

It helps to have questions for the doctor written down ahead of time. Print out these questions and take them to your next appointment. You may want to ask a family member or close friend to come with you to take notes.

So far so good. But here is the list that follows:

What puts me at risk for colorectal cancer?

When do I need to start getting tested?

How often do I need to get tested?

What screening test do you recommend? Why?

What’s involved in screening? How do I prepare?

Are there any dangers or side effects involved?

How long will it take to get the results?

What can I do to reduce my risk of colorectal cancer?

Note the wording: "When do I need to start getting tested?" "How often do I need to get tested?" And these "needs" come well before the "why?" In fact, the "why" never really comes. The oblique "why" about which test is recommended is too little too late. The real "why" is why, or even whether, I need to get tested in the first place. I am happy to see a question on the dangers of screening, but again it leaves plenty of room for the clinician to minimize and patronize.

The list of questions is built upon one (erroneous) assumption: Everyone is bound to perceive the risk-benefit equation of colorectal cancer screening the same way. We know this is false, and each person needs to make an individual decision based in what we know today and according to the values he/she places on the outcomes. The way the questions are written, they simply reinforce the bullying attitude of the screening bias, making those who swim against this tide feel irrational and unreasonable. But may I point out that some of us spoke out against universal mammography screening even before it became the main-stream recommendation? So perhaps there are good reasons to be more cautious with screening for everything, even colon cancer.

Science evolves, our knowledge evolves. What we think we know today will be modified tomorrow. I take a strong exception to this dogmatic and one-sided formulation of how to have a discussion about testing whose risk and benefit profile may not (and should not) elicit the same unbridled enthusiasm from everyone. So please, healthfinder.gov, rethink your "helpful" questions so as to educate, rather than indoctrinate.

Hat tip to @DCPatient for pointing me to this page

If you like Healthcare, etc., please consider a donation (button in the right margin) to support development of this content. But just to be clear, it is not tax-deductible, as we do not have a non-profit status. Thank you for your support!

Why "efficacy" does not equal "effectiveness"

noreply@blogger.com (Marya Zilberberg) — Mon, 04 Jun 2012 16:13:00 +0000

As you may have noticed, one of the biggest medical conferences is in progress right now in Chicago -- the American Society of Clinical Oncology. It is the premier meeting of cancer doctors, where new data are the order of the day. This stream of data is reflected in a constant barrage of media coverage. One of the stories I saw today serves as a great illustration of the title of this post: why efficacy does not equal effectiveness. Although I do discuss this in my book, I thought it might be nice to apply these ideas to a current story.

The MedPage story opens with this:

Older patients with advanced cancers treated in the community had survival that fell short of that for patients who received the same regimens in clinical trials, analysis of a large government database showed.

Most of the differences were small in absolute terms, except for patients with stage IV colorectal cancer treated with the FOLFIRI chemotherapy regimen. Patients in the community had a median survival of 16.1 months, which was 30% lower than that of patients treated with the same regimen in a cooperative-group randomized clinical trial.

Moreover, survival among FOLFIRI-treated older patients was 4 months shorter than that of older patients treated with FOLFOX chemotherapy, Elizabeth B. Lamont, MD, reported here at the American Society of Clinical Oncology meeting.

This is a common conundrum, and a poster child for the distinction between efficacy and effectiveness. So, what are these two "e"s? Efficacy is essentially a statistical distinction between the outcomes of interest among patients who undergo a particular treatment compared to those who do not, or those who get treated with a placebo. Efficacy is measured under the controlled circumstances of a clinical trial, where only very specific patients are enrolled, very specific treatments are administered, and very specific outcomes are monitored. These trials usually randomize patients to either the treatment or the placebo, thus ensuring that treated and untreated patients are the same in all ways save for the treatment under examination. Efficacy is frequently represented by what we call surrogate outcomes, such as laboratory measurements or radiographic tests. In cancer studies, for example, a frequent surrogate outcome that is used is so-called progression-free survival. This refers to the duration of time from treatment that a person is alive AND the tumor has not shown any evidence of growth on a scan. Another frequently used surrogate measure is blood pressure as a marker for heart disease. These are surrogates because, although correlated with such important outcomes as death and heart attacks, respectively, they themselves do not tell us with any precision how our interventions impact these ultimate measures. I will not belabor at this time why we rely on efficacy and surrogate outcomes, since I go into detail about that in the book.

Effectiveness, on the other hand, is something altogether different. Effectiveness tells us exactly what happens in the real messy world to outcomes that matter, such as death and quality of life, in conjunction with the treatment in question. We have known for a long time that the outcomes we see in naturalistic studies are often much less spectacular than those reported in RCTs of efficacy. Why is this? And more importantly, which do we believe? The second question is easier to answer than the first: we believe what happens in the real world, because it is precisely what happens in the real world rather than in the laboratory of clinical research that matters. As to why this difference exists, there are many reasons for this, most of which I have discussed elsewhere on this blog and in Between the Lines. Some of the reasons may have to do with patient selection, which in real life tends to be less restrictive than in RCTs. For example, individuals who are more ill may get the intervention that was intended to be given to those with lesser illness severity. In this population the intervention may not prove to be as effective as in those who are not as ill. This is called "confounding by indication," and we talked about it most recently here. Other reasons may be that other conditions patients have in real life, which tend to be excluded from RCT populations, attenuate the impact of the intervention. When looking at mortality in cancer, patients with end-stage heart disease may be excluded from the RCT, but treated in the wilds of clinical practice. And this treatment may give us a Pyrrhic victory, where cancer is indeed held at bay, but the patient dies of his heart disease. And here is yet another reason for the efficacy-effectiveness disconnect: attribution. In clinical trials there is a meticulous process that has to be followed in order to attribute the cause of death to a particular disease. In real life -- not so: death certificates are a notoriously dicey source of information on the causes of death.

So here are some of the challenges with applying RCT data to the real world, illustrated so palpably in the story we started out with. Please, do not misunderstand my message: I am not saying that RCTs are useless. What I am saying (I must sound like a broken record by now) is that we need different types of studies to see the whole picture. RCTs by their nature are exclusive undertakings whose findings are only narrowly translatable to the real world. Naturalistic observational data are key components of building the entire jigsaw puzzle of how our interventions really work.

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How to game mortality data

noreply@blogger.com (Marya Zilberberg) — Wed, 30 May 2012 13:07:00 +0000

There is a great illustration in this BMJ article of what I discuss in Chapter 2 of my book: the type of mortality that matters. In the figure below from the paper, note that, as the new diagnoses of each of the cancers rise (green lines), the attendant "Deaths" (red lines) stay unchanged. If you look at the Y-axis of each graph, it tells us that the unit of measurement is "Rate per 100,000 people." So the red lines represent population mortality.

"Population mortality" means that the denominator for this value is all people in the population who are at risk for the disease in question. This means that for prostate cancer, for example, we include only those men who have a prostate and exclude all women and men who have had a prostatectomy. Population mortality stands in contradistinction to case fatality. The latter is defined as deaths among all the people diagnosed with the disease. So, for prostate cancer, case fatality would be deaths among all men who have been diagnosed with prostate cancer.

It is not difficult to see how case fatality is a somewhat circular, even self-referential, measure of our diagnostic prowess, but says very little about how well we are doing with disease treatment. If we have tests that are capable of picking up the most minute of diseases, those that are not likely to cause death in the first place, then the denominator becomes inflated with this noise, while the numerator, the actual fatalities, does not change. This leads of course to an apparent reduction in deaths from the disease, but a reduction that is an artifact of overdiagnosis. Population mortality, on the other hand, cannot be gamed this way, as you can see in the figure above. This is the only mortality that gives us honest feedback without a bias about how we are doing with our early detection and other interventions. In the case of the cancers in the figure, the answer is "not so well."

You can learn more about this in Chapter 2, where I even have a figure that illustrates this critical distinction.

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Three wrong reasons to dismiss the azithromycin data

noreply@blogger.com (Marya Zilberberg) — Tue, 29 May 2012 11:58:00 +0000

There is a lively discussion over at KevinMD about the azithromycin study in the New England Journal of Medicine, which I blogged about here. A certain ethos has emerged in the comments that bears unpacking. There are 3 distinct points that I am feeling unsetlled by:

#1. As a retrospective cohort study it should be ignored.
This is an intellectually indefensible position in my mind -- it is a study that uses a set of methods developed and validated for this type of data. Yes, it's complex; yes, it's messy; no, it's not to be ignored. The discipline of pharmacoepidemiology relies heavily on observational data. To expect anything more is to indulge in misapprehensions that a). it is feasible to run a RCT to detect such rare signals, and 2). that a RCT like that would give us a definitive answer.

#2. They really had to add a lot of zeros to the denominator to make the numerator seem impressive.
This is a baseless accusation, since 1 million prescriptions is not that difficult to generate. Z-pak has been on the market for over a decade, and according to this article, last year 55 million prescriptions for azithro were handed out in the US. So, just a back-of-the-envelope calculation for excess deaths per year at this rate is well over 2,000. And this is just in one year! So, as a safety signal this is not something to be trivialized.

#3. A concern that this information will keep patients from doctors' offices and delay needed treatment.
I find this to be rather a hollow concern (though I am sure that the person putting it forward believes it wholeheartedly). As another commenter pointed out, the overuse and misuse of antibiotics is completely out of control! And yes, cardiac deaths from azithromycin are but a small part of the issue, where the elephant in the room is the evolution of resistance. It is not just these latest data that should keep patients as far away as possible from unnecessary healthcare encounters, seeing as how these encounters are the third leading cause of death in the US. Why aren't we worried that this entire monster is keeping patients away? And quite frankly, why isn't it?

So, all in all, I am very glad that Rob Lamberts chose to blog the study, and the discussion has been worthwhile. The comments have really confirmed for me that it is not only the lay public, but also healthcare professionals, who have a hard time interpreting data. And when a study is somewhat challenging, it is generally easier to let our cognitive biases run amok.

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Septic shock doesn't need my rescue bias

noreply@blogger.com (Marya Zilberberg) — Thu, 24 May 2012 13:46:00 +0000

Rescue bias and auxiliary hypothesis bias are tempting distractions when it comes to dealing with data that are counter to our preconceived notions. In general, the role of our cognitive biases in all kinds of discourse, including clinical and scientific, is under appreciated. For this reason I devoted fully two chapters of my book to cognitive biases.

Which makes it even more frightening that, as I read this NEJM paper on the failed drotrecogin PROWESS-SHOCK study, I am still looking for reasons why it failed, other than that just doesn't work. After so many years of trials and tribulations with Xigris, and hopes that this lone therapy ever to have been approved for treating this deadly disease, I am having a hard time letting go.

Yet the rial was meticulous, as all trials designed and overseen by B. Taylor Thompson are -- he is just a brilliant clinical researcher that we all need to learn from. The design considered all the right issues a priori -- multiple interim looks at the data, a possible need to increase the power, heterogeneous treatment effect, and others. Although there were a few numerical imbalances between the treatment and the placebo groups -- blood cultures were positive 4% more frequently and the offending pathogen overall was 5% more likely to be identified in the Xigris than in the placebo group -- I have to accept that these are not the reasons for the observed failure to improve either the 28-day or the 90-day mortality.

I have seen and even blogged about these data before -- the press release had some of them, but, more importantly, Taylor presented them at the Society of Critical Care Medicine meeting back in January. So, this is nothing new. Yet reading all of the details in the pages of the NEJM brings back that pre-conscious cognitive wall that I have to climb over in order to get to reality. And the reality is that the drug just did not work.

But the reality is also that sepsis patients have a better chance of surviving this deadly assault than they did 10 years ago. In the original PROWESS study 28-day mortality in the placebo group was 31%, and these were all kinds of sepsis patients. In the current study, among most severe sepsis patients, those with septic shock, the 28-day mortality was on the order of 25% in both arms -- that's a staggering reduction in this most ill septic population! We really need to appreciate this. In part this trend may be due to some evolution of the disease-host interaction. But in part it has to be because of the concerted effort to understand sepsis better, to study various treatment options, and, most importantly, to implement these learnings at the bedside. In no small part we owe these advances in sepsis care to the short life of drotrecogin alpha.

The data are clearly anticlimactic, and for this reason the current paper has no sex appeal -- just look at the (lack of) press coverage about it. Yet, this is a clear example of countering the traditional publication bias: Here is a manufacturer-funded negative study published in a premier peer-reviewed journal. I realize that it was always a high-profile undertaking, but let's pause for a moment to enjoy this small victory for those who have railed against the spread of biased information in the medical literature.

I don't know if and when another therapy will emerge courageous enough to brave the rough waters of sepsis and septic shock. But one thing is clear: Xigris has served out its purpose, and no amount of rescue bias from me will save it. Rest in peace.

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