Personalizing Evidence-Based Primary Prevention With Aspirin

Abstract

One of the unfortunate side consequences of evidence-based medicine (EBM) is that sometimes there is no escaping how small the benefit of any individual treatment may seem. In the “days of the giants,” doctors saved lives; now we can consult league tables that bloodlessly inform us how many patients—10, 50, or 200—must receive a treatment to avert even a single bad outcome,1 EBM's venerable number needed to treat. Article see p 268 The number needed to treat is, of course, based only on average treatment effects. A limitation of EBM is that we study groups of patients, whereas we treat individuals. This mismatch can be partially addressed by the use of statistical models to calculate the important risks that determine a more “personalized” probability of benefit. When this is done, it turns out, the degree of benefit for an intervention in any typical patient is often even less than the overall average.2 This is because benefits are determined by the baseline risk, which is usually highly skewed, such that a few high-risk patients may account for most of the benefit, whereas most patients have baseline risks (and therefore potential benefit) considerably less than the average.3 This is true particularly when the overall risk of the outcome of interest is low because there is a lower bound for risk at 0%, creating a “floor effect.” In this issue of Circulation: Cardiovascular Quality and Outcomes , Sussman et al4 describe the “personalized” risks and benefits of aspirin therapy for primary prevention of cardiovascular diseases, a rather extreme exemplar of the pattern described above. The number needed to treat to prevent a single ischemic event for any typical patient in a primary prevention population can easily exceed 1000 per year but may vary substantially, depending on individualized risk. Because …