Friday, January 23, 2015

What is 'inappropriate' use of baby aspirin? The risk of estimating risk

Something like a third of the American population* takes a baby aspirin every day to prevent cardiovascular disease (CVD).  But a new study ("Frequency and Practice-Level Variation in Inappropriate Aspirin Use for the Primary Prevention of Cardiovascular Disease : Insights From the National Cardiovascular Disease Registry’s Practice Innovation and Clinical Excellence Registry", Hira et al., J Amer Coll Cardiol) suggests that more than 1 in 10 of these people are taking it 'inappropriately.'

Aspirin slows blood clotting, and blood coagulation plays a role in vascular disease, so the thinking is that some heart attacks and strokes can be prevented with regular use of aspirin, and indeed there is empirical support for this.  As with many drug therapies, it was the side effects of aspirin use for something else, in this case rheumatoid arthritis (RA), that first suggested it could play a role in CVD prevention -- a 1978 study reported that aspirin use lowered the risk of myocardial infarction, angina pectoris, sudden death, and cerebral infarction in RA patients (study cited in an editorial by Freek Verheugt accompanying the Hira paper), a result that kick-started its use for CVD prevention.

The new Hira et al. study included about 68,000 patients in 119 different practices taking aspirin for prevention of a first heart attack or stroke, not recurrence.  The authors looked at clinical records in a network of cardiology practices to assess the proportion of patients in each practice that was taking aspirin, and whether they met the 10-year risk criteria for 'appropriate use' as determined by the Framingham risk calculator.  The calculator uses an algorithm based on age, sex, total cholesterol, HDL cholesterol, smoking status, blood pressure and whether the patient is taking medication to control blood pressure.

Appropriate use, according to Hira et al., is a 10-year risk of greater than 6%.  According to the calculator itself, 6% risk means that 6 of 100 people with whichever set of factors yields this risk will have a heart attack within the next 10 years.  The reason this even has to be thought about is because there is some risk to taking aspirin because it's an anticoagulant and can cause major bleeding, so maximizing the cost/benefit ratio, preventing CVD as well as major bleeds, is what's at issue here.  If the benefit is a long-shot because an aspirin user isn't likely to have CVD anyway, the potential cost can outweigh the pluses.

As Verheugt explains:
Major coronary events (coronary heart disease mortality and nonfatal MI) are reduced by 18% with aspirin but at the cost of an increase of 54% in major extracranial bleeding. For every 2 major coronary events shown to be prevented by prophylactic aspirin, they occur at the cost of 1 major extracranial bleed. Primary prevention with aspirin is widely applied, however. This regimen is used not only because of its cardioprotection but also because there is increasing evidence of chemoprotection of aspirin against cancer.
Hira et al. found that 11.6% of the population of patients visiting a cardiology practice were taking aspirin inappropriately, having a risk less than 6% as calculated by the Framingham calculator.  That is, their risk of bleeding outweighs the potential preventive effect of aspirin.

But, about this 6% risk.  Does it sound high to you?  Would you change your behavior based on a 6% risk, or would you figure the risk is low enough that you can continue to eat those cheese steaks?  Or maybe you'd just start popping aspirin, figuring that made it really safe to continue to eat those cheese steaks?

And why the 6% threshold?  So precise.  Indeed, a 2011 study suggested different risk thresholds for different age categories, increasing with age.  And, different calculators (such as this one from the University of Edinburgh) return different risk estimates, varying by several percentage points given the same data, so so much for precision.

Risk is, of course, estimated from population data, based on the many studies that have found an association between cholesterol, blood pressure, smoking status, and heart attack, particularly in older men.  A distribution of risk factors and outcomes would thus show that for a given set of cholesterol and blood pressure values, on average x% will have a heart attack or stroke.  These are group averages, and using them to make predictions for individuals cannot be done with precision that we know to be true.  Indeed, one of the strongest risk factors known to epidemiology, smoking, causes lung cancer in 'only' 10% of smokers, and it's impossible to predict who. But that's why these CVD risk calculators never estimate 100% risk.  The highest risk I could force them to estimate was "greater than 30%".

Hard to know what that actually means for any individual.  At least, I have a hard time knowing what to make of these figures.  If 6 of 100 people in the threshold risk risk category will have an MI in the next 10 years, this means that 94 will not.  So, another way to think about this is that the risk for 94 people is in fact 0, while risk for the unlucky 6 is 100%.  For everyone over the 6% threshold, the cost -- possible major bleed -- is assumed to be outweighed by the benefit -- prevention of MI --  even when that's in fact only true for 6 out of 100 people in this particular risk category.  But, since it's impossible to predict which 6 are at 100% risk, the whole group is treated as though it's at 100% risk, and put on preventive baby aspirin, and perhaps statins as well, and counseled on lifestyle changes and so on, all of which can greatly affect the outcome, and alter our understanding of risk factors -- or the effectiveness of preventive aspirin.  And what if it's true that a drink a day lowers heart failure risk?  How do we factor that in?

Further, a lot of more or less well-established risk factors for CVD are not included in the calculation. After decades of cardiovascular disease research, it seems to be well-established that obesity is a risk factor, as well as diabetes, and certainly family history.  Why aren't these pieces of information included?  Tens if not hundreds of genes have been identified to have at least a weak effect on risk (and even this number only account for a fraction of the genetic risk as estimated from heritability studies), and these aren't included in the calculation either.  And, we all know people who seemed totally fit, who had a heart attack on the running trail, or the bike trail, so at least some people are in fact at risk even with none of the accepted risk factors.

So, 11.6% of baby aspirin takers shouldn't be taking aspirin.  But, when risk estimation is as imprecise as it is, and as hard to understand, this seems like a number that we should be taking with a grain of salt, if not a baby aspirin.  Well, except that salt is a risk factor for hypertension which is a risk factor for heart disease....or is it?

*Or something like that.  It turns out that the Hira paper cited a 2007 paper, which cited a 2006 paper, which cited the Behavioral Risk Factor Surveillance System 2003 estimate of 36% of the American population taking a baby aspirin a day.  But this is a 12 year old figure, and I couldn't find anything more recent.


Michael Finfer, MD said...

I often try to explain to people that statistics don't necessarily mean anything to an individual. No matter what, one could still end up in that small percentage with a rare outcome. We are managing risks and offer no guarantees.

Anne Buchanan said...

Thanks for that. I think this is especially hard for clinicians, who have to make sense of these statistics for individual patients.

Ken Weiss said...

Statistics are, largely, about replication of similar conditions and their outcomes. Life is largely about divergence from common ancestry by being individually different. In my view, statistical thinking is being borrowed from other fields of inquiry, where replication is more literally correct. At the same time, sometimes identifying unique individuals isn't important (as in iodizing salt to reduce goiter problems in society as a whole, or fluoridating water). In other areas, such as presumably yours from a clinical point of view, perhaps what is needed would be a very different way of thinking or analysis, or something like that.

Anne Buchanan said...

Another issue is that we don't really understand causation when it's not a strong cause with a major effect. What else contributes to lung cancer in the subset of smokers who get it? Or heart attack in the subset who have one among all the people deemed to be at high risk, apart from the risk factors accounted for by the Framingham calculator? Unless it's just bad luck, which could be generalizable, everyone who has a heart attack may well have a bunch of personal contributors, some shared with other people and some not, but that makes each individual heart attack unpredictable. And even inexplicable in retrospect.

Kathleen D said...

Statistics are frequently abused in medical practice to rule out a possible diagnosis, with grave consequences, possibly fatal. I wonder whether actuarial data has become a substitute for real diagnostic skills. Here are the outlines of my story:

When I was 21 a lump in my neck was misdiagnosed 3 times before identified as adnexal carcinoma. I was the only diagnosis for that entire year worldwide, and that's a normal year. But still, I had adnexal carcinoma 100%. I was a National Science Foundation fellow at the time, with an interest in social data.

So imagine my frustration in recent years when, on different occasions, doctors dismissed my suggestions that evidence pointed to: diabetes insipidus, brain tumor, and apical hypertrophic cardiomyopathy. At the first hearing, usually the doc would smile and say, "That would be very rare," but would be entirely unmoved when reminded that I have already survived a cancer that is far more rare. When I returned with still more journal articles and data, the smiles became more frozen, and my suggested diagnosis would be dismissed after the most perfunctory consideration, if at all.

All of my proposed diagnoses were confirmed, but only by moving on and on, finally to other docs who actually examined the evidence with an open mind, but sometimes that took many, many years in which suffering and risk were prolonged, This particular abuse of percentages was so vehement and so widespread among the MD's I encountered that I wonder whether comes from mis-education or from insurance company intrusion into medical practice. Over and over again, my case may have been unusual, but I did have my conditions - and 100%.

Anne Buchanan said...

Kathleen: Yours is not a good story. When estimates are that 8-10% of the American population has a rare disease, that means it's not unusual for a physician to be facing a patient with a rare disease, which in turn means that, despite the admonition that the first thing a doctor should think of when s/he hears hoof beats is a horse, sometimes it really is a zebra.

We've had a number of rare conditions in my family -- indeed, even the cat has a rare condition -- but not all in one person. And we've had our share of years-long diagnostic odysseys like yours, though yours must be the worst one ever. You are fortunate to be good at research, even though it doesn't always translate into the physician doing the right thing.

I think when doctors are busy, and time with a patient limited, when they are right most of the time that the patient has the common condition rather than the rare one, it's tempting not to even consider the rare conditions. And, you may be right that insurers are sometimes reluctant to pay for testing for rare conditions. But it's always true that a single patient isn't a statistic, but translating population-based statistics to individual patient is tough.