Resumen de The crisis of the epidemiology of the averages - A call for discriminatory accuracy
All over the world, large amounts of economical and intellectual resources are allocated to the study of both traditional risk factors and novel biomarkers for diseases. Today, it is broadly recognized that epidemiology aims at improving our knowledge on individual risk prediction for a more satisfactory and individually-tailored treatment.
However, for this purpose, we typically compute simple measures of average association like the odds ratio (OR). The expectation is that this procedure will help us to identify the exposures that discriminate with accuracy the individuals who will develop the disease from those who will not in order to target effective medical or public health interventions. Nevertheless, during the last years a number of relevant publications have pointed out that measures of association alone are unsuitable for this discriminatory purpose. In fact, what we normally consider as a strong association between a risk factor and a disease (e.g., OR=10) is related to a rather low capacity of the risk factor to discriminate cases and non-cases of disease in the population.
In analogy to diagnostic tests, promoting population level screening and treatment of risk factors with a low discriminatory accuracy may lead to unnecessary side effects and costs. It also raises ethical issues related to risk communication and the perils of both unwarranted medicalization and stigmatization of individuals with the risk factor/biomarker. We need a new epidemiological approach that goes beyond differences between average group risks and systematically informs on discriminatory accuracy and inter-individual heterogeneity of effects.
