Multicategory reclassification statistics for assessing improvements in diagnostic accuracy.

TitleMulticategory reclassification statistics for assessing improvements in diagnostic accuracy.
Publication TypeJournal Article
Year of Publication2013
AuthorsLi, Jialiang, Binyan Jiang, and Jason P. Fine
JournalBiostatistics
Volume14
Issue2
Pagination382-94
Date Published2013 Apr
ISSN1468-4357
KeywordsArea Under Curve, Biomarkers, Biostatistics, Computer Simulation, Diagnostic Tests, Routine, Gene Expression, Humans, Leukemia, Logistic Models, Models, Statistical, ROC Curve, Synovitis
Abstract

In this paper, we extend the definitions of the net reclassification improvement (NRI) and the integrated discrimination improvement (IDI) in the context of multicategory classification. Both measures were proposed in Pencina and others (2008. Evaluating the added predictive ability of a new marker: from area under the receiver operating characteristic (ROC) curve to reclassification and beyond. Statistics in Medicine 27, 157-172) as numeric characterizations of accuracy improvement for binary diagnostic tests and were shown to have certain advantage over analyses based on ROC curves or other regression approaches. Estimation and inference procedures for the multiclass NRI and IDI are provided in this paper along with necessary asymptotic distributional results. Simulations are conducted to study the finite-sample properties of the proposed estimators. Two medical examples are considered to illustrate our methodology.

DOI10.1093/biostatistics/kxs047
Alternate JournalBiostatistics
Original PublicationMulticategory reclassification statistics for assessing improvements in diagnostic accuracy.
PubMed ID23197381
PubMed Central IDPMC3695653
Grant ListP01 CA142538 / CA / NCI NIH HHS / United States
P30 AI050410 / AI / NIAID NIH HHS / United States
R01 CA094893 / CA / NCI NIH HHS / United States
Project: