The length of the receiver operating characteristic curve and the two cutoff Youden index within a robust framework for discovery, evaluation, and cutoff estimation in biomarker studies involving improper receiver operating characteristic curves.
None
Youden
isoperimetric
kernels
likelihood ratio
optimal ROC
sensitivity
specificity
stochastic ordering
two-cutoff ROC
Journal
Statistics in medicine
ISSN: 1097-0258
Titre abrégé: Stat Med
Pays: England
ID NLM: 8215016
Informations de publication
Date de publication:
30 03 2021
30 03 2021
Historique:
received:
17
02
2020
revised:
09
12
2020
accepted:
14
12
2020
pubmed:
3
2
2021
medline:
30
6
2021
entrez:
2
2
2021
Statut:
ppublish
Résumé
During the early stage of biomarker discovery, high throughput technologies allow for simultaneous input of thousands of biomarkers that attempt to discriminate between healthy and diseased subjects. In such cases, proper ranking of biomarkers is highly important. Common measures, such as the area under the receiver operating characteristic (ROC) curve (AUC), as well as affordable sensitivity and specificity levels, are often taken into consideration. Strictly speaking, such measures are appropriate under a stochastic ordering assumption, which implies, without loss of generality, that higher measurements are more indicative for the disease. Such an assumption is not always plausible and may lead to rejection of extremely useful biomarkers at this early discovery stage. We explore the length of a smooth ROC curve as a measure for biomarker ranking, which is not subject to directionality. We show that the length corresponds to a
Identifiants
pubmed: 33530129
doi: 10.1002/sim.8869
pmc: PMC9976806
mid: NIHMS1758184
doi:
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
1767-1789Subventions
Organisme : NIGMS NIH HHS
ID : P20 GM130423
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR002366
Pays : United States
Informations de copyright
© 2021 John Wiley & Sons, Ltd.
Références
Epidemiology. 1996 Nov;7(6):605-11
pubmed: 8899386
Cancer. 1950 Jan;3(1):32-5
pubmed: 15405679
Int J Biostat. 2019 Apr 3;15(1):
pubmed: 30943172
Cancer Res. 2015 Aug 15;75(16):3246-54
pubmed: 26088128
J Clin Oncol. 2013 Dec 20;31(36):4536-43
pubmed: 24248694
Med Decis Making. 1991 Apr-Jun;11(2):95-101
pubmed: 1865785
Stat Methods Med Res. 2019 Jul;28(7):2032-2048
pubmed: 29243554
Cancer Res. 2013 Mar 1;73(5):1502-13
pubmed: 23269276
Biometrics. 2014 Mar;70(1):212-23
pubmed: 24261514
Stat Med. 2003 Aug 15;22(15):2503-13
pubmed: 12872305
Pancreas. 2013 Jul;42(5):729-39
pubmed: 23648843
Stat Methods Med Res. 2017 Jun;26(3):1429-1442
pubmed: 25911331
Stat Med. 2017 Nov 20;36(26):4230-4240
pubmed: 28809042
Biometrics. 2002 Sep;58(3):657-64
pubmed: 12230001
BMC Bioinformatics. 2012 Jun 26;13:147
pubmed: 22734592
Stat Methods Med Res. 2017 Feb;26(1):113-123
pubmed: 24986857
Clin Cancer Res. 2011 May 1;17(9):2955-66
pubmed: 21385931
J Clin Oncol. 2008 Nov 1;26(31):5060-6
pubmed: 18794547
CA Cancer J Clin. 2017 Jan;67(1):7-30
pubmed: 28055103
BMC Bioinformatics. 2008 Oct 03;9:410
pubmed: 18834513