Tuesday, November 19, 2013

To statin or not to statin, that is the question....or is it?

Last week we all heard about the new recommendations concerning predicting and preventing heart disease.  An online calculator was going to be used to predict risk, based on past experience of a study cohort, and if we were found to be at risk, we'd be advised to start taking statins.  Based on various risk factors -- BMI, whether we smoke, etc., -- the calculator would advise our doctor if our risk of heart disease was greater than 7.5%, and if so, that would trigger the writing of the prescription.  Estimates were that this was going to lead to 1/3 or more of American adults taking statins for the rest of their life.

We had various reasons to question this recommendation, as we wrote then, and that was even before new issues have come home to roost.  As reported in the NY Times yesterday (and in The Lancet today), experts are now showing that the calculator is way over-estimating risk, which would mean millions more people on statins than the generous new guidelines themselves would recommend.    Some leading cardiologists are calling for a halt to implementation of the new guidelines until the calculator issues get sorted. 

But apparently this shouldn't have come as a surprise to the cardiac community -- two Harvard cardiologists, authors of the Lancet paper, warned a year ago that the calculator overestimates risk.  The problem seems to stem from the use of old data to do the estimations. Ten or more years ago more people smoked, and developed cardiovascular disease earlier than they do now.  Risk estimates on that background now overestimate the effect of factors such as blood pressure and cholesterol because additional background factors, also a component of risk, have changed.  That is, there are confounding variables that affect risk, whose frequency in the population have change, but the calculator doesn't take this into account.  

Or at least that's probably the problem.  It may be even more fundamental than that.  Decades ago, a very well-known cardiovascular disease epidemiologist, Reuel Stallones, used to say that heart disease rates had both risen and fallen in the 20th century for reasons that were not understood.  Diet, exercise, smoking, cholesterol, none of the obvious risk factors explained either the rise or the fall, and it's still true.

However, the risk calculator problem raises another truly fundamental issue that pertains to this sort of risk prediction in general, not just to heart disease.  We have several times noted that one essential flaw in the whole concept of risk estimation based on the kinds of studies that are done, is that risk is estimated retrospectively, from a study sample's past experiences, but what we want are prospective risks: yours and mine for the future, not the past.  But future experiences, mainly here involving lifestyle environmental factors, are inherently unpredictable (In case you missed it, that's inherently unpredictable).

The critique of the new recommendations, in an unusual way, showed just this problem.  Risks were estimated for the new calculator from past data, but used to estimate risks subsequently.  However, since lifestyle risk has changed (less smoking, for example) our ultimate experiences can't be adequately predicted from risks based on the earlier experiences of the cohort used to estimate risk.  Whatever would lead properly cognizant epidemiologists to think that things would be different for the real future?

Indeed, this shows the stubbornness of our clinging to kinds of statistical association mechanisms, the belief in big-science, the haste, and so on that plagues much of what is afoot these days.  To a great extent, we do what we know how to do, the problems are very challenging and often risks are small in absolute value so that, with our approach, we do look to very large studies.  But we also stick with this rather than slowing down, taking a deep breath, and really re-evaluating what we face.  This is the issue we often write about: the need for a deep change in our scientific concepts or methodology, not just keeping the research factory humming.

Plus, we already know a better way to prevent heart disease, and that is lifestyle choices, exercise, not smoking, eating more vegetables than fats and meats.  Statins are largely generic drugs now, but they are still an expensive way to prevent illness -- people without disease become patients (see Jim Wood's August post on how he became sick), they are in the medical system, requiring not only drugs for life but testing and follow-up testing and so on.  And, statins aren't benign drugs; they do have side effects, including muscle pain, liver damage, diabetes.  The industry's credibility is at stake now with this calculator issue, but there are other reasons to question their word about going on statins.  


ITooWasAbused said...

As smoking rates have dropped, changing heart disease rates, I wonder how the increase in obesity has simultaneously changed risk rates.

Ken Weiss said...

That is exactly the competing-causes problem. Even if one just added up the risk associated with each factor, Risk=statinExposure + ObesityExposure, if we don't know how much exposure there will be we can't know the risk. Statins might lower risk but during the extra survival years, one eats more and raises net risk, or slims down and no longer needs (but still is taking) the meds. And if different risk factors act in some more complex way, say, statinExposure x obesityExposure, which can be quite complicated and almost impossible to understand accurately unless the situation is quite simple, then who knows where risk estimates will stand, relative to the true risk.

ITooWasAbused said...

Well and I suppose the problem of not knowing *current* risk still stands. We won't know the answer to how obesity rates and smoking rates affect the risk of people living now, until "now" is "then."

Ken Weiss said...

That is exactly right. If we knew approximately how things might change and basically all factors that were important, we would be in better position to understand risk. We need more humility and less definitive claims, and in particular, to be circumspect about lifetime medication when it may not be needed, and when we know of more important factors that are not technological, but societal.

We could put high tax on big Colas, the way we do on tobacco, and things like that. But as long as private business trumps everything else in our culture, including health, we're stuck with what we've got.

Ken Weiss said...

And yesterday (Nov 19) another story about heart-disease drug trials in which harmful effects were, essentially, covered up and had basically to be forced out of the companies involved. The point is that we cannot automatically trust those with vested interests, and the more that their interests tend, or can be predicted to tend, to generating open-ended business for those interests, the more rigorously their potential conflicts of interest should be examined and the less automatically trusted.

John R. Vokey said...

You write: ``Plus, we already know a better way to prevent heart disease, and that is lifestyle choices, exercise, not smoking, eating more vegetables than fats and meats.''

Aside from the obvious smoking, really, we "know" this? Based on what evidence? What *controlled* studies do you have at hand that have this as the obvious conclusion?

Ken Weiss said...

I'm pretty much of a skeptic, as you know, but I think this as a general statement is supported by so many kinds of studies, including correlational, longitudinal, genetic, historical, and mechanistic that I think on a population basis it's reliable. On an individual basis, of course, it's only probabilistic and far from certain.

But let's put it this way: there are very clear secular trends in these disorders, showing that they are not 'genetic' but most of the genetic evidence has to do with these sorts of things (associated with fats, plaque, weight, etc.). Nonetheless, your point is valid, but even then it doesn't point to statins-for-everyone as justified.