Literature DB >> 31250693

A comprehensive and comparative review of optimal cut-points selection methods for diseases with multiple ordinal stages.

Jia Hua1, Lili Tian1.   

Abstract

Cut-points selection is a key topic in the field of diagnostic studies. For binary classification, there exist several well-developed methods, some of which have been extended to three-class settings and beyond. This paper focuses on optimal cut-points selection methods for diseases with multiple ordinal stages. The purpose of this paper is two-fold: 1) to propose three new cut-points selection methods; and 2) to present a comprehensive simulation study to assess and compare the performance of all the available methods. Two real data sets, one from ovarian cancer and the other from pancreatic cancer, are analyzed.

Entities:  

Keywords:  ROC curve; ROC surface; Youden index; area under ROC curve; volume under ROC surfac

Mesh:

Substances:

Year:  2019        PMID: 31250693     DOI: 10.1080/10543406.2019.1632876

Source DB:  PubMed          Journal:  J Biopharm Stat        ISSN: 1054-3406            Impact factor:   1.051


  2 in total

1.  Estimation and construction of confidence intervals for biomarker cutoff-points under the shortest Euclidean distance from the ROC surface to the perfection corner.

Authors:  Brian R Mosier; Leonidas E Bantis
Journal:  Stat Med       Date:  2021-06-03       Impact factor: 2.497

2.  Mutual Information as a Performance Measure for Binary Predictors Characterized by Both ROC Curve and PROC Curve Analysis.

Authors:  Gareth Hughes; Jennifer Kopetzky; Neil McRoberts
Journal:  Entropy (Basel)       Date:  2020-08-26       Impact factor: 2.524

  2 in total

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