Background and objective: When estimating incidence risk ratios in follow-up studies, subjects testing positive for the disease at baseline are excluded. Although the effect of disease misclassification on estimated incidence risk ratios has otherwise been extensively explored, the effect of disease misclassification at baseline has not previously been analyzed.
Study design and setting: The design was theoretical calculations assuming dichotomous disease and a follow-up study with a baseline and a follow-up examination, analyzed using cumulative incidence. Calculations consider nondifferential misclassification of disease mainly at baseline, but no misclassification of exposure.
Results: Nondifferential misclassification of disease at baseline can lead to bias either away or toward null in estimated cumulative incidence risk ratios. This bias is mainly a function of sensitivity at baseline, because imperfect sensitivity leads to failure to exclude all diseased subjects from the follow-up. Imperfect specificity at baseline has less effect. Bias is increased with high true prevalence of disease and low true incidence. Bias is also increased with large differences in true risk ratios at baseline and at follow-up, because observed incidence risk ratios in the presence of misclassification reflect both the true association at baseline and at follow-up.
Conclusion: Nondifferential disease misclassification at baseline examination of a follow-up study can lead to over- or underestimation of the cumulative incidence risk ratios. The bias can be substantial for disease with low incidence and high prevalence, such as asthma or myocardial infarction. The results underscore the need to select a highly sensitive test for disease at baseline to exclude all diseased subjects from the follow-up.