A surrogate endpoint is defined as a biomarker intended to substitute for a clinical endpoint, such as an incidence, or mortality. The evidence supporting the linkage of a biomarker to accurately substitute for a clinical endpoint may be derived from epidemiologic studies, clinical trials, in vitro analysis, animal models, and simulated biologic systems. Analytical epidemiological studies of the relationship between putative intermediate endpoints and disease help postulate the nature of the interrelationship among epidemiological risk factors, intermediate endpoints, and disease. This presents problems in a system where more than one causal path exists. Adjustment for the presence of standard epidemiological factors may have different interpretations. Specifically, the disappearance of an association between a putative intermediate endpoint and disease after adjustment for the presence of some epidemiological risk factors may have opposing interpretations: either the intermediate endpoint is causal, related to disease and mediates the effects defined by the epidemiologic risk factor or it has nothing to do with disease in a causal sense. Several contributors throughout this issue have described and used a variety of biomarkers in treatment trials. Selected biomarkers may be proposed as potential surrogate endpoints, however, relatively few are likely to achieve this status because of the complexity of disease mechanisms and the limited capability of a single biomarker to reflect the collective impact of multiple chemopreventive and therapeutic effects on outcome. It is likely that the future studies would employ a panel of biomarkers as a surrogate endpoint, which would require additional biologic studies and insights. A biomarker does not have to be causally related to a disease to play a valuable role in early detection and intervention of that disease. However, causally related biomarkers, i.e., surrogate endpoints, if measured with precision, are likely to have the strongest association with disease.