Identification of new risk factors for specific diseases is an enduring theme in medical research. Advances in molecular biology, genetics, and computational biology are accelerating the pace of this work. The research seeks to increase our understanding of the causes of diseases, but there is also hope that the recognition of new risk factors will lead to improved methods for identifying persons who are in the early stages of, or at high risk for, the diseases of concern. Research has shown, however, that a risk factor must have a much stronger association with the disease outcome than we ordinarily see in etiologic research if it is to provide a basis for early diagnosis or prediction in individual patients. 1, 2 A simple example will illustrate the problem.

Suppose that the goal is to identify persons at high risk for acquiring a disease (the outcome) within 5 years. We will assume, as shown in the figure, that the risk factor is normally distributed in the group of persons who will not experience the outcome. We will further assume that the risk factor is also normally distributed with the same variance, but with a mean 0.5 SD that is larger among persons who will have the outcome than among the group of persons who will not.(The results that follow do not depend on the values of the mean end variance in the group of persons without the outcome.) Finally, let us suppose that the cumulative incidence of the outcome within 5 years is 5%.