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Bias in Estimating Accuracy of a Binary Screening Test with Differential Disease Verification by Todd A. Alonzo; John T. Brinton; Brandy M. Ringham; Deborah H. Glueck is a Mathematics article available to read on EtoBox.

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## Abstract Sensitivity, specificity, positive and negative predictive value are typically used to quantify the accuracy of a binary screening test. In some studies, it may not be ethical or feasible to obtain definitive disease ascertainment for all subjects using a gold standard test. When a gold standard test cannot be used, an imperfect reference test that is less than 100 per cent sensitive and specific may be used instead. In breast cancer screening, for example, follow‐up for cancer diagnosis is used as an imperfect reference test for women where it is not possible to obtain gold standard results. This incomplete ascertainment of true disease, or differential disease verification, can result in biased estimates of accuracy. In this paper, we derive the apparent accuracy values for studies subject to differential verification. We determine how the bias is affected by the accuracy of the imperfect reference test, the percent who receive the imperfect reference standard test not receiving the gold standard, the prevalence of the disease, and the correlation between the results for the screening test and the imperfect reference test. It is shown that designs with differential di

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Author

Todd A. Alonzo; John T. Brinton; Brandy M. Ringham; Deborah H. Glueck

Publisher

John Wiley and Sons; Wiley (John Wiley & Sons); John Wiley & Sons Inc.; Wiley (ISSN 0277-6715)

Published

2011

Language

EN

Field

Mathematics (Physical Sciences)