Zwinderman AH, Glas AS, Bossuyt PM, Florie J, Bipat S, Stoker J. Statistical models for quantifying diagnostic accuracy with multiple lesions per patient.
Biostatistics 2008;
9:513-22. [PMID:
18204044 PMCID:
PMC2430771 DOI:
10.1093/biostatistics/kxm052]
[Citation(s) in RCA: 12] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
We propose random-effects models to summarize and quantify the accuracy of the diagnosis of multiple lesions on a single image without assuming independence between lesions. The number of false-positive lesions was assumed to be distributed as a Poisson mixture, and the proportion of true-positive lesions was assumed to be distributed as a binomial mixture. We considered univariate and bivariate, both parametric and nonparametric mixture models. We applied our tools to simulated data and data of a study assessing diagnostic accuracy of virtual colonography with computed tomography in 200 patients suspected of having one or more polyps.
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