Hidden Heart Risk Factor



Estimating the Risk of Heart Disease - Questioning a New Calculator

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Historically, guideline recommendations for a medical therapy were based on the inclusion criteria used in large clinical studies that demonstrated the benefits of the therapy.  Large studies were done and, if positive, the therapy was recommended for patients that were like those included in the studies. Recent guidelines from the ACC/AHA have taken a different approach in attempting to predict risk of heart disease, in this case the 10-year and lifetime risk of cardiovascular disease, and using the risk score as the basis for treatment recommendations.

Both approaches have their limitations.  Clinical studies often exclude a large proportion of patients who might benefit from the therapy under study.  The generalizability of study findings is questioned, and which patients should be treated who are unlike but similar to those studied is debated.  On the other hand, the risk prediction method is highly dependent on the risk prediction model.  Models that underestimate the risk result in underutilization of the therapy; that is, patients who should receive the therapy may not get it.  Models that overestimate the risk of heart disease result in overutilization of the therapy; that is, patients who should not receive the therapy may get it.

It appears that the model in question may overestimate the risk of heart disease and this may result in many (millions) of people receiving statin therapy who should not. This problem was brought to our attention by Dr. Nancy Cook and Dr. Paul Ridker of Harvard Medical School, in a paper just released by The Lancet.  Their work indicates that the predictor overestimates the risk of cardiovascular disease by 75% to 150%.

So where does this leave us? Back to where we started in medicine before guideline recommendations, using sound clinical judgment. Clinicians should always take into account the totality of available information when making treatment decisions. Reliance on any single number, such as a risk prediction score, or blind adherence to any guideline recommendation without consideration of an individual patient’s situation is potentially perilous.

Last Updated:11/18/2013
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Date: 06.01.2019, 06:12 / Views: 43133