title: Reducing decision errors in the paired comparison of the diagnostic accuracy of screening tests with Gaussian outcomes.
abstract: BACKGROUND
  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 suspicious results or signs and symptoms of disease receive the reference standard test. The remaining participants are classified as non-cases, even though some may have occult disease. The standard analysis includes all study participants, which can create bias in the estimates of diagnostic accuracy since not all participants receive disease status verification. We propose a weighted maximum likelihood bias correction method to reduce decision errors.
  
  
  METHODS
  Using Monte Carlo simulations, we assessed the method's ability to reduce decision errors across a range of disease prevalences, correlations between screening test scores, rates of interval cases and proportions of participants who received the reference standard test.
  
  
  RESULTS
  The performance of the method depends on characteristics of the screening tests and the disease and on the percentage of participants who receive the reference standard test. In studies with a large amount of bias in the difference in the full areas under the curves, the bias correction method reduces the Type I error rate and improves power for the correct decision. We demonstrate the method with an application to a hypothetical oral cancer screening study.
  
  
  CONCLUSIONS
  The bias correction method reduces decision errors for some paired screening trials. 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.
authors.affiliation: Center for Cancer Prevention and Control Research, University of California, Los Angeles, 650 Charles Young Drive South, Room A2-125 CHS, Los Angeles CA 90095, USA. bringham@ucla.edu.
authors.forename: Brandy M
authors.initials: BM
authors.lastname: Ringham
authors.forename: Todd A
authors.initials: TA
authors.lastname: Alonzo
authors.forename: John T
authors.initials: JT
authors.lastname: Brinton
authors.forename: Sarah M
authors.initials: SM
authors.lastname: Kreidler
authors.forename: Aarti
authors.initials: A
authors.lastname: Munjal
authors.forename: Keith E
authors.initials: KE
authors.lastname: Muller
authors.forename: Deborah H
authors.initials: DH
authors.lastname: Glueck
mesh_terms: D015982:Bias; D003657:Decision Making; D003951:Diagnostic Errors / Q000706:statistics & numerical data*; D055088:Early Detection of Cancer / Q000379:methods*; D006801:Humans; D008403:Mass Screening; D009010:Monte Carlo Method; D009062:Mouth Neoplasms / Q000175:diagnosis* / Q000453:epidemiology; D016011:Normal Distribution; D015995:Prevalence; D012372:ROC Curve; D012015:Reference Standards