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Three types of issues need to be considered in the application of epidemiology results to individuals. First, epidemiology results are subject to random error, and can be applied only to an ideal subject with average values of all variables under study, including potential confounders included in the regression models. Second, the observational nature of epidemiology makes it susceptible to systematic error, and any extrapolation to individuals would mirror the validity of the original results. Quantitative bias analysis has been proposed to assess the likelihood, direction and magnitude of bias, but this has not yet become part of the normal practice of epidemiology. Finally, external validity of the results (i.e., their application to individuals and populations other than those included in the underlying studies) needs to be addressed, including population-based factors, such as heterogeneity in exposure or disease circumstances, and individual-based factors, such as interaction of the risk factors of interest with other determinants of the disease. Similar considerations apply to the application of results of clinical trials to individual patients, although in these studies sources of systematic error are better controlled.