title: A non-inferiority test for diagnostic accuracy based on the paired partial areas under ROC curves.
abstract: Non-inferiority is a reasonable approach to assessing the diagnostic accuracy of a new diagnostic test if it provides an easier administration or reduces the cost. The area under the receiver operating characteristic (ROC) curve is one of the common measures for the overall diagnostic accuracy. However, it may not differentiate the various shapes of the ROC curves with different diagnostic significances. The partial area under the ROC curve (PAUROC) may present an alternative that can provide additional and complimentary information for some diagnostic tests which require false-positive rate that does not exceed a certain level. Non-parametric and maximum likelihood methods can be used for the non-inferiority tests based on the difference in paired PAUROCs. However, their performance has not been investigated in finite samples. We propose to use the concept of generalized p-value to construct a non-inferiority test for diagnostic accuracy based on the difference in paired PAUROCs. Simulation results show that the proposed non-inferiority test not only adequately controls the size at the nominal level but also is uniformly more powerful than the non-parametric methods. The proposed method is illustrated with a numerical example using published data.
authors.affiliation: Division of Biometry, Institute of Agronomy, National Taiwan University, Taipei, Taiwan.
authors.forename: Chi-Rong
authors.initials: CR
authors.lastname: Li
authors.forename: Chen-Tuo
authors.initials: CT
authors.lastname: Liao
authors.forename: Jen-Pei
authors.initials: JP
authors.lastname: Liu
mesh_terms: D003198:Computer Simulation; D016001:Confidence Intervals; D003955:Diagnostic Tests, Routine / Q000379:methods* / Q000592:standards; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D010190:Pancreatic Neoplasms / Q000175:diagnosis; D011237:Predictive Value of Tests; D012372:ROC Curve; D018709:Statistics, Nonparametric