Exploring the negative likelihood ratio and how it can be used to minimize false-positives in breast imaging

Wei T. Yang; Jay R. Parikh; Anthony T Stavros; Pam Otto; Greg Maislin

doi:10.2214/AJR.17.18774

Exploring the negative likelihood ratio and how it can be used to minimize false-positives in breast imaging

Wei T. Yang, Jay R. Parikh, Anthony T Stavros, Pam Otto, Greg Maislin

Department of Radiology

Research output: Contribution to journal › Review article › peer-review

11 Scopus citations

Abstract

OBJECTIVE. This article describes the defnition and proposed utilization of negative likelihood ratios (NLRs) as statistical parameters in breast imaging. Examples with calculations are provided using BI-RADS category 4 subcategories. CONCLUSION. By auditing individual performance early and often against American College of Radiology benchmark positive predictive value ranges for the BI-RADS category 4 subcategories, and by fully understanding NLRs and their application in breast imaging, radiologists can minimize false-positive fndings and unnecessary biopsies.

Original language	English (US)
Pages (from-to)	301-306
Number of pages	6
Journal	American Journal of Roentgenology
Volume	210
Issue number	2
DOIs	https://doi.org/10.2214/AJR.17.18774
State	Published - Feb 2018

Keywords

BI-RADS
Bayes theorem
Breast imaging biopsy
Negative likelihood ratio
Posttest probability
Pretest probability

ASJC Scopus subject areas

Radiology Nuclear Medicine and imaging

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title = "Exploring the negative likelihood ratio and how it can be used to minimize false-positives in breast imaging",

abstract = "OBJECTIVE. This article describes the defnition and proposed utilization of negative likelihood ratios (NLRs) as statistical parameters in breast imaging. Examples with calculations are provided using BI-RADS category 4 subcategories. CONCLUSION. By auditing individual performance early and often against American College of Radiology benchmark positive predictive value ranges for the BI-RADS category 4 subcategories, and by fully understanding NLRs and their application in breast imaging, radiologists can minimize false-positive fndings and unnecessary biopsies.",

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AU - Yang, Wei T.

AU - Parikh, Jay R.

AU - Stavros, Anthony T

AU - Otto, Pam

AU - Maislin, Greg

N1 - Publisher Copyright: © American Roentgen Ray Society.

PY - 2018/2

Y1 - 2018/2

N2 - OBJECTIVE. This article describes the defnition and proposed utilization of negative likelihood ratios (NLRs) as statistical parameters in breast imaging. Examples with calculations are provided using BI-RADS category 4 subcategories. CONCLUSION. By auditing individual performance early and often against American College of Radiology benchmark positive predictive value ranges for the BI-RADS category 4 subcategories, and by fully understanding NLRs and their application in breast imaging, radiologists can minimize false-positive fndings and unnecessary biopsies.

AB - OBJECTIVE. This article describes the defnition and proposed utilization of negative likelihood ratios (NLRs) as statistical parameters in breast imaging. Examples with calculations are provided using BI-RADS category 4 subcategories. CONCLUSION. By auditing individual performance early and often against American College of Radiology benchmark positive predictive value ranges for the BI-RADS category 4 subcategories, and by fully understanding NLRs and their application in breast imaging, radiologists can minimize false-positive fndings and unnecessary biopsies.

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KW - Bayes theorem

KW - Breast imaging biopsy

KW - Negative likelihood ratio

KW - Posttest probability

KW - Pretest probability

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Exploring the negative likelihood ratio and how it can be used to minimize false-positives in breast imaging

Abstract

Keywords

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