The use of imperfect diagnostic tests had an impact on prevalence estimation

Abstract Objective Problems arising with the estimation of sensitivity and specificity when two imperfect diagnostic tests are applied are widely discussed. Effects on the estimation of prevalence may be of importance as well. Different methods of dealing with two or more imperfect tests and unknown reference standard are contrasted with regard to their implications on prevalence estimation: discrepant analysis, composite reference standards, and latent class models. Study Design and Setting Prospective epidemiological multicenter study to determine the prevalence of respiratory syncytial virus in children with lower respiratory tract infections. A subsample of 1,003 patients from a hospital population and from a practice population is considered. Virus isolation, polymerase chain reaction, and rapid antigen test had been applied. Results Prevalence estimates obtained under various assumptions ranged from 0.263 to 0.386 in the hospital population and from 0.214 to 0.277 in the practice population. Conclusion Estimation procedures involving a resolver test applied to some but not all cells are at risk of introducing a serious bias in prevalence estimation as well as in the estimation of test accuracy parameters. Estimation via latent class modeling may be more useful, but care should be taken regarding the underlying assumptions.