Number needed to biopsy ratio and diagnostic accuracy for melanoma detection.
NNB
diagnostic accuracy
melanoma
melanoma positive predictive value
melanoma screening
melanoma sensitivity
melanoma specificity
number needed to biopsy
Journal
Journal of the American Academy of Dermatology
ISSN: 1097-6787
Titre abrégé: J Am Acad Dermatol
Pays: United States
ID NLM: 7907132
Informations de publication
Date de publication:
Sep 2020
Sep 2020
Historique:
received:
13
12
2019
revised:
03
04
2020
accepted:
20
04
2020
pubmed:
4
5
2020
medline:
26
2
2021
entrez:
4
5
2020
Statut:
ppublish
Résumé
The number needed to biopsy (NNB) ratio for melanoma diagnosis is calculated by dividing the total number of biopsies by the number of biopsied melanomas. It is the inverse of positive predictive value (PPV), which is calculated by dividing the number of biopsied melanomas by the total number of biopsies. NNB is increasingly used as a metric to compare the diagnostic accuracy of health care practitioners. To investigate the association of NNB with the standard statistical measures of sensitivity and specificity. We extracted published diagnostic accuracy data from 5 cross-sectional skin cancer reader studies (median [min-max] readers/study was 29 [8-511]). Because NNB is a ratio, we converted it to PPV. Four studies showed no association and 1 showed a negative association between PPV and sensitivity. All 5 studies showed a positive association between PPV and specificity. Reader study data. An individual health care practitioner with a lower NNB is likely to have a higher specificity than one with a higher NNB, assuming they practice under similar conditions; no conclusions can be made about their relative sensitivities. We advocate for additional research to define quality metrics for melanoma detection and caution when interpreting NNB.
Sections du résumé
BACKGROUND
BACKGROUND
The number needed to biopsy (NNB) ratio for melanoma diagnosis is calculated by dividing the total number of biopsies by the number of biopsied melanomas. It is the inverse of positive predictive value (PPV), which is calculated by dividing the number of biopsied melanomas by the total number of biopsies. NNB is increasingly used as a metric to compare the diagnostic accuracy of health care practitioners.
OBJECTIVE
OBJECTIVE
To investigate the association of NNB with the standard statistical measures of sensitivity and specificity.
METHODS
METHODS
We extracted published diagnostic accuracy data from 5 cross-sectional skin cancer reader studies (median [min-max] readers/study was 29 [8-511]). Because NNB is a ratio, we converted it to PPV.
RESULTS
RESULTS
Four studies showed no association and 1 showed a negative association between PPV and sensitivity. All 5 studies showed a positive association between PPV and specificity.
LIMITATIONS
CONCLUSIONS
Reader study data.
CONCLUSIONS
CONCLUSIONS
An individual health care practitioner with a lower NNB is likely to have a higher specificity than one with a higher NNB, assuming they practice under similar conditions; no conclusions can be made about their relative sensitivities. We advocate for additional research to define quality metrics for melanoma detection and caution when interpreting NNB.
Identifiants
pubmed: 32360723
pii: S0190-9622(20)30725-8
doi: 10.1016/j.jaad.2020.04.109
pmc: PMC7484328
mid: NIHMS1609160
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
780-787Subventions
Organisme : NCI NIH HHS
ID : P30 CA008748
Pays : United States
Informations de copyright
Copyright © 2020 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.
Références
JAMA Dermatol. 2018 Oct 1;154(10):1229
pubmed: 30046801
JAMA Dermatol. 2018 May 1;154(5):569-573
pubmed: 29710082
J Am Acad Dermatol. 2020 Jan;82(1):110-116
pubmed: 31408683
JAMA Dermatol. 2015 Aug;151(8):899-902
pubmed: 25806897
J Am Acad Dermatol. 2015 Nov;73(5):769-76
pubmed: 26386631
Lancet Oncol. 2019 Jul;20(7):938-947
pubmed: 31201137
Arch Dermatol. 2011 Feb;147(2):188-94
pubmed: 20956633
Dermatol Surg. 2019 Aug;45(8):1035-1041
pubmed: 30640783
J Drugs Dermatol. 2016 May 1;15(5):527-32
pubmed: 27168261
Behav Modif. 2016 May;40(3):396-413
pubmed: 26611466
JAMA Dermatol. 2019 Jul 10;:
pubmed: 31290958
J Am Acad Dermatol. 2013 Mar;68(3):517-9
pubmed: 23394922
Br J Dermatol. 2010 Feb 1;162(2):267-73
pubmed: 19785607
Br J Dermatol. 2012 Jun;166(6):1213-20
pubmed: 22283805
JAMA Dermatol. 2016 Aug 1;152(8):952-3
pubmed: 27532358
J Am Acad Dermatol. 2012 Jul;67(1):54-9
pubmed: 21982636
JAMA Dermatol. 2016 Apr;152(4):371-2
pubmed: 26746782
J Clin Oncol. 2017 Jan;35(1):63-71
pubmed: 28034073
J Am Acad Dermatol. 2018 Feb;78(2):270-277.e1
pubmed: 28969863
J Am Acad Dermatol. 2020 Mar;82(3):622-627
pubmed: 31306724
Am J Prev Med. 2015 Feb;48(2):183-187
pubmed: 25442229