Potential bias due to prevalent diseases in prospective studies.

In prospective studies, subjects found to have the disease under investigation at the initial screening examination are commonly excluded from analyses. However, the possibility of bias due to prevalent conditions other than the disease of interest is usually not considered. In the present study, an algebraic development enables analysis of the effects of inclusion and exclusion of subjects with certain prevalent conditions upon risk estimates. Hypothetical data are presented for which an association between a risk factor and an incident disease could become null or even reversed after removing subjects with certain prevalent diseases. Bias appears even when the only association present is between risk factor and total disease incidence. Data from the Honolulu Heart Study also have been used to illustrate this finding, examining the association between coronary heart disease (CHD) incidence and smoking. Decisions regarding the inclusion or exclusion of subjects with prevalent diseases requires prior knowledge of alteration of usual risk factors levels by individuals with these diseases. Simply removing all subjects with prevalent diseases might on the contrary create bias. Therefore, people with prevalent diseases should be screened for potential alteration of their risk factor levels as a result of the diseases. The situation becomes still more complex when several risk factors and prevalent diseases need to be considered at the same time as it happens in multivariate analyses. Because this situation represents a bias, and not confounding or effect modification, controlling for the effect of prevalent diseases is not appropriate.