Abstract
Scientists often use a paired comparison of the areas under the receiver operating characteristic curves to decide which continuous cancer screening test has the best diagnostic accuracy. In the paired design, all participants are screened with both tests. Participants with unremarkable screening results enter a follow-up period. Participants with suspicious screening results and those who show evidence of disease during follow-up receive the gold standard test. The remaining participants are classified as non-cases, even though some may have occult disease. The standard analysis includes all study participants in the analysis, which can create bias in the estimates of diagnostic accuracy. If the bias affects the area under the curve for one screening test more than the other screening test, scientists may make the wrong decision as to which screening test has better diagnostic accuracy. We propose a weighted maximum likelihood bias-correction method to reduce decision errors. The amount of bias in the study and the performance of the bias correction method depend on characteristics of the screening tests and the disease, and on the percentage of study participants who receive the gold standard test. In order to determine if bias correction is needed for a specific screening trial, we recommend the investigator conduct a simulation study using our software. We demonstrate the proposed method with an application to a hypothetical oral cancer screening study.
Citation Format: Brandy M. Ringham, Todd A. Alonzo, John T. Brinton, Keith E. Muller, Deborah H. Glueck. Reducing decision errors in the paired comparison of the diagnostic accuracy of continuous screening tests. [abstract]. In: Proceedings of the Fifth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2012 Oct 27-30; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(10 Suppl):Abstract nr A06.
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