An article in this week’s New York Times called Will This Treatment Help Me? There’s a Statistic for that highlights the disconnect between the risks (and risk reductions) that epidemiologists, researchers, guideline writers, the pharmaceutical industry, and policy wonks think are significant and the risks (and risk reductions) patients intuitively think are significant enough to warrant treatment.
The authors, bloggers at The Incidental Economist, begin the article with a sobering look at the number needed to treat (NNT). For the primary prevention of myocardial infarction (MI), if 2000 people with a 10% or higher risk of MI in the next 10 years take aspirin for 2 years, one MI will be prevented. 1999 people will have gotten no benefit from aspirin, and four will have an MI in spite of taking aspirin. Aspirin, a very good drug on all accounts, is far from a panacea, and this from a man (me) who takes it in spite of falling far below the risk threshold at which it is recommended.
One problem with NNT is that for patients it is a gratuitous numerical transformation of a simple number that anybody could understand (the absolute risk reduction – “your risk of stroke is reduced 3% by taking coumadin“), into a more abstract one (the NNT – “if we treat 33 people with coumadin, we prevent one stroke among them”) that requires retransformation into examples that people can understand, as shown in pictograms in the NYT article. A person trying to understand stroke prevention with coumadin could care less about the other 32 people his doctor is treating with coumadin, he is interested in himself. And his risk is reduced 3%. So why do we even use the NNT, why not just use ARR?
