Risk stratification of women with false-positive test results in mammography screening based on mammographic morphology and density: a case control study

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Risk stratification of women with false-positive test results in mammography screening based on mammographic morphology and density : a case control study. / Winkel, Rikke Rass; von Euler-Chelpin, My Catarina; Lynge, Elsebeth; Diao, Pengfei; Lillholm, Martin; Kallenberg, Michiel; Forman, Julie Lyng; Nielsen, Michael Bachmann; Uldall, Wei Yao; Nielsen, Mads; Vejborg, Ilse Merete Munk.

In: Cancer Epidemiology, Vol. 49, 08.2017, p. 53-60.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Winkel, RR, von Euler-Chelpin, MC, Lynge, E, Diao, P, Lillholm, M, Kallenberg, M, Forman, JL, Nielsen, MB, Uldall, WY, Nielsen, M & Vejborg, IMM 2017, 'Risk stratification of women with false-positive test results in mammography screening based on mammographic morphology and density: a case control study', Cancer Epidemiology, vol. 49, pp. 53-60. https://doi.org/10.1016/j.canep.2017.05.006

APA

Winkel, R. R., von Euler-Chelpin, M. C., Lynge, E., Diao, P., Lillholm, M., Kallenberg, M., ... Vejborg, I. M. M. (2017). Risk stratification of women with false-positive test results in mammography screening based on mammographic morphology and density: a case control study. Cancer Epidemiology, 49, 53-60. https://doi.org/10.1016/j.canep.2017.05.006

Vancouver

Winkel RR, von Euler-Chelpin MC, Lynge E, Diao P, Lillholm M, Kallenberg M et al. Risk stratification of women with false-positive test results in mammography screening based on mammographic morphology and density: a case control study. Cancer Epidemiology. 2017 Aug;49:53-60. https://doi.org/10.1016/j.canep.2017.05.006

Author

Winkel, Rikke Rass ; von Euler-Chelpin, My Catarina ; Lynge, Elsebeth ; Diao, Pengfei ; Lillholm, Martin ; Kallenberg, Michiel ; Forman, Julie Lyng ; Nielsen, Michael Bachmann ; Uldall, Wei Yao ; Nielsen, Mads ; Vejborg, Ilse Merete Munk. / Risk stratification of women with false-positive test results in mammography screening based on mammographic morphology and density : a case control study. In: Cancer Epidemiology. 2017 ; Vol. 49. pp. 53-60.

Bibtex

@article{7be9f7b45d704e07861d2592fb03aaa9,
title = "Risk stratification of women with false-positive test results in mammography screening based on mammographic morphology and density: a case control study",
abstract = "Background:The long-term risk of breast cancer is increased in women with false-positive (FP) mammography screening results. We investigated whether mammographic morphology and/or density can be used to stratify these women according to their risk of future breast cancerMethods:We undertook a case-control study nested in the population-based screening programme in Copenhagen, Denmark. We included 288 cases and 288 controls based on a cohort of 4743 women with at least one FP-test result in 1991–2005 who were followed up until 17 April 2008. Film-based mammograms were assessed using the Breast Imaging-Reporting and Data System (BI-RADS) density classification, the Tab{\'a}r classification, and two automated techniques quantifying percentage mammographic density (PMD) and mammographic texture (MTR), respectively. The association with breast cancer was estimated using binary logistic regression calculating Odds Ratios (ORs) and the area under the receiver operating characteristic (ROC) curves (AUCs) adjusted for birth year and age and invitation round at the FP-screenResults:Significantly increased ORs were seen for BI-RADS D(density)2-D4 (OR 1.94; 1.30-2.91, 2.36; 1.51-3.70 and 4.01; 1.67-9.62, respectively), Tab{\'a}r’s P(pattern)IV (OR 1.83; 1.16-2.89), PMD Q(quartile)2-Q4 (OR 1.71; 1.02-2.88, 1.97; 1.16-3.35 and 2.43; 1.41-4.19, respectively) and MTR Q4 (1.97; 1.12-3.46) using the lowest/fattiest category as referenceConclusion: All four methods, capturing either mammographic morphology or density, could segregate women with FP-screening results according to their risk of future breast cancer − using already available screening mammograms. Our findings need validation on digital mammograms, but may inform potential future risk stratification and tailored screening strategiesAbbreviations:ACRthe American College of RadiologyAUCarea under the ROC curveBI-RADSBreast Imaging Reporting and Data SystemCCcraniocaudalDCISductal carcinoma in situFPfalse-positiveHRThormone replacement treatmentMLOmediolateral obliqueMTRmammographic texture resemblancePMDPercentage Mammographic DensityROCreceiver-operating characteristic",
keywords = "Breast cancer risk, Mammography screening, False positive, Mammographic density, Texture, BI-RADS, Tabar",
author = "Winkel, {Rikke Rass} and {von Euler-Chelpin}, {My Catarina} and Elsebeth Lynge and Pengfei Diao and Martin Lillholm and Michiel Kallenberg and Forman, {Julie Lyng} and Nielsen, {Michael Bachmann} and Uldall, {Wei Yao} and Mads Nielsen and Vejborg, {Ilse Merete Munk}",
year = "2017",
month = "8",
doi = "10.1016/j.canep.2017.05.006",
language = "English",
volume = "49",
pages = "53--60",
journal = "Cancer Epidemiology",
issn = "1877-7821",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Risk stratification of women with false-positive test results in mammography screening based on mammographic morphology and density

T2 - a case control study

AU - Winkel, Rikke Rass

AU - von Euler-Chelpin, My Catarina

AU - Lynge, Elsebeth

AU - Diao, Pengfei

AU - Lillholm, Martin

AU - Kallenberg, Michiel

AU - Forman, Julie Lyng

AU - Nielsen, Michael Bachmann

AU - Uldall, Wei Yao

AU - Nielsen, Mads

AU - Vejborg, Ilse Merete Munk

PY - 2017/8

Y1 - 2017/8

N2 - Background:The long-term risk of breast cancer is increased in women with false-positive (FP) mammography screening results. We investigated whether mammographic morphology and/or density can be used to stratify these women according to their risk of future breast cancerMethods:We undertook a case-control study nested in the population-based screening programme in Copenhagen, Denmark. We included 288 cases and 288 controls based on a cohort of 4743 women with at least one FP-test result in 1991–2005 who were followed up until 17 April 2008. Film-based mammograms were assessed using the Breast Imaging-Reporting and Data System (BI-RADS) density classification, the Tabár classification, and two automated techniques quantifying percentage mammographic density (PMD) and mammographic texture (MTR), respectively. The association with breast cancer was estimated using binary logistic regression calculating Odds Ratios (ORs) and the area under the receiver operating characteristic (ROC) curves (AUCs) adjusted for birth year and age and invitation round at the FP-screenResults:Significantly increased ORs were seen for BI-RADS D(density)2-D4 (OR 1.94; 1.30-2.91, 2.36; 1.51-3.70 and 4.01; 1.67-9.62, respectively), Tabár’s P(pattern)IV (OR 1.83; 1.16-2.89), PMD Q(quartile)2-Q4 (OR 1.71; 1.02-2.88, 1.97; 1.16-3.35 and 2.43; 1.41-4.19, respectively) and MTR Q4 (1.97; 1.12-3.46) using the lowest/fattiest category as referenceConclusion: All four methods, capturing either mammographic morphology or density, could segregate women with FP-screening results according to their risk of future breast cancer − using already available screening mammograms. Our findings need validation on digital mammograms, but may inform potential future risk stratification and tailored screening strategiesAbbreviations:ACRthe American College of RadiologyAUCarea under the ROC curveBI-RADSBreast Imaging Reporting and Data SystemCCcraniocaudalDCISductal carcinoma in situFPfalse-positiveHRThormone replacement treatmentMLOmediolateral obliqueMTRmammographic texture resemblancePMDPercentage Mammographic DensityROCreceiver-operating characteristic

AB - Background:The long-term risk of breast cancer is increased in women with false-positive (FP) mammography screening results. We investigated whether mammographic morphology and/or density can be used to stratify these women according to their risk of future breast cancerMethods:We undertook a case-control study nested in the population-based screening programme in Copenhagen, Denmark. We included 288 cases and 288 controls based on a cohort of 4743 women with at least one FP-test result in 1991–2005 who were followed up until 17 April 2008. Film-based mammograms were assessed using the Breast Imaging-Reporting and Data System (BI-RADS) density classification, the Tabár classification, and two automated techniques quantifying percentage mammographic density (PMD) and mammographic texture (MTR), respectively. The association with breast cancer was estimated using binary logistic regression calculating Odds Ratios (ORs) and the area under the receiver operating characteristic (ROC) curves (AUCs) adjusted for birth year and age and invitation round at the FP-screenResults:Significantly increased ORs were seen for BI-RADS D(density)2-D4 (OR 1.94; 1.30-2.91, 2.36; 1.51-3.70 and 4.01; 1.67-9.62, respectively), Tabár’s P(pattern)IV (OR 1.83; 1.16-2.89), PMD Q(quartile)2-Q4 (OR 1.71; 1.02-2.88, 1.97; 1.16-3.35 and 2.43; 1.41-4.19, respectively) and MTR Q4 (1.97; 1.12-3.46) using the lowest/fattiest category as referenceConclusion: All four methods, capturing either mammographic morphology or density, could segregate women with FP-screening results according to their risk of future breast cancer − using already available screening mammograms. Our findings need validation on digital mammograms, but may inform potential future risk stratification and tailored screening strategiesAbbreviations:ACRthe American College of RadiologyAUCarea under the ROC curveBI-RADSBreast Imaging Reporting and Data SystemCCcraniocaudalDCISductal carcinoma in situFPfalse-positiveHRThormone replacement treatmentMLOmediolateral obliqueMTRmammographic texture resemblancePMDPercentage Mammographic DensityROCreceiver-operating characteristic

KW - Breast cancer risk

KW - Mammography screening

KW - False positive

KW - Mammographic density

KW - Texture

KW - BI-RADS

KW - Tabar

U2 - 10.1016/j.canep.2017.05.006

DO - 10.1016/j.canep.2017.05.006

M3 - Journal article

VL - 49

SP - 53

EP - 60

JO - Cancer Epidemiology

JF - Cancer Epidemiology

SN - 1877-7821

ER -

ID: 183636475