Automated and clinical breast imaging reporting and data system density measures predict risk for screen-detected and interval cancers

A case-control study

Karla Kerlikowske, Christopher G. Scott, Amir P. Mahmoudzadeh, Lin Ma, Stacey Winham, Matthew R. Jensen, Fang Fang Wu, Serghei Malkov, V. Shane Pankratz, Steven R. Cummings, John A. Shepherd, Kathleen R. Brandt, Diana L Miglioretti, Celine M. Vachon

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

Background: In 30 states, women who have had screening mammography are informed of their breast density on the basis of Breast Imaging Reporting and Data System (BI-RADS) density categories estimated subjectively by radiologists. Variation in these clinical categories across and within radiologists has led to discussion about whether automated BI-RADS density should be reported instead. Objective: To determine whether breast cancer risk and detection are similar for automated and clinical BI-RADS density measures. Design: Case-control. Setting: San Francisco Mammography Registry and Mayo Clinic. Participants: 1609 women with screen-detected cancer, 351 women with interval invasive cancer, and 4409 matched control participants. Measurements: Automated and clinical BI-RADS density assessed on digital mammography at 2 time points from September 2006 to October 2014, interval and screen-detected breast cancer risk, and mammography sensitivity. Results: Of women whose breast density was categorized by automated BI-RADS more than 6 months to 5 years before diagnosis, those with extremely dense breasts had a 5.65-fold higher interval cancer risk (95% CI, 3.33 to 9.60) and a 1.43-fold higher screen-detected risk (CI, 1.14 to 1.79) than those with scattered fibroglandular densities. Associations of interval and screendetected cancer with clinical BI-RADS density were similar to those with automated BI-RADS density, regardless of whether density was measured more than 6 months to less than 2 years or 2 to 5 years before diagnosis. Automated and clinical BI-RADS density measures had similar discriminatory accuracy, which was higher for interval than screen-detected cancer (c-statistics: 0.70 vs. 0.62 [P < 0.001] and 0.72 vs. 0.62 [P < 0.001], respectively). Mammography sensitivity was similar for automated and clinical BI-RADS categories: fatty, 93% versus 92%; scattered fibroglandular densities, 90% versus 90%; heterogeneously dense, 82% versus 78%; and extremely dense, 63% versus 64%, respectively. Limitation: Neither automated nor clinical BI-RADS density was assessed on tomosynthesis, an emerging breast screening method. Conclusion: Automated and clinical BI-RADS density similarly predict interval and screen-detected cancer risk, suggesting that either measure may be used to inform women of their breast density.

Original languageEnglish (US)
Pages (from-to)757-765
Number of pages9
JournalAnnals of Internal Medicine
Volume168
Issue number11
DOIs
StatePublished - Jun 5 2018

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Information Systems
Case-Control Studies
Breast
Neoplasms
Mammography
Breast Neoplasms
San Francisco
Registries

ASJC Scopus subject areas

  • Internal Medicine

Cite this

Automated and clinical breast imaging reporting and data system density measures predict risk for screen-detected and interval cancers : A case-control study. / Kerlikowske, Karla; Scott, Christopher G.; Mahmoudzadeh, Amir P.; Ma, Lin; Winham, Stacey; Jensen, Matthew R.; Wu, Fang Fang; Malkov, Serghei; Pankratz, V. Shane; Cummings, Steven R.; Shepherd, John A.; Brandt, Kathleen R.; Miglioretti, Diana L; Vachon, Celine M.

In: Annals of Internal Medicine, Vol. 168, No. 11, 05.06.2018, p. 757-765.

Research output: Contribution to journalArticle

Kerlikowske, K, Scott, CG, Mahmoudzadeh, AP, Ma, L, Winham, S, Jensen, MR, Wu, FF, Malkov, S, Pankratz, VS, Cummings, SR, Shepherd, JA, Brandt, KR, Miglioretti, DL & Vachon, CM 2018, 'Automated and clinical breast imaging reporting and data system density measures predict risk for screen-detected and interval cancers: A case-control study', Annals of Internal Medicine, vol. 168, no. 11, pp. 757-765. https://doi.org/10.7326/M17-3008
Kerlikowske, Karla ; Scott, Christopher G. ; Mahmoudzadeh, Amir P. ; Ma, Lin ; Winham, Stacey ; Jensen, Matthew R. ; Wu, Fang Fang ; Malkov, Serghei ; Pankratz, V. Shane ; Cummings, Steven R. ; Shepherd, John A. ; Brandt, Kathleen R. ; Miglioretti, Diana L ; Vachon, Celine M. / Automated and clinical breast imaging reporting and data system density measures predict risk for screen-detected and interval cancers : A case-control study. In: Annals of Internal Medicine. 2018 ; Vol. 168, No. 11. pp. 757-765.
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title = "Automated and clinical breast imaging reporting and data system density measures predict risk for screen-detected and interval cancers: A case-control study",
abstract = "Background: In 30 states, women who have had screening mammography are informed of their breast density on the basis of Breast Imaging Reporting and Data System (BI-RADS) density categories estimated subjectively by radiologists. Variation in these clinical categories across and within radiologists has led to discussion about whether automated BI-RADS density should be reported instead. Objective: To determine whether breast cancer risk and detection are similar for automated and clinical BI-RADS density measures. Design: Case-control. Setting: San Francisco Mammography Registry and Mayo Clinic. Participants: 1609 women with screen-detected cancer, 351 women with interval invasive cancer, and 4409 matched control participants. Measurements: Automated and clinical BI-RADS density assessed on digital mammography at 2 time points from September 2006 to October 2014, interval and screen-detected breast cancer risk, and mammography sensitivity. Results: Of women whose breast density was categorized by automated BI-RADS more than 6 months to 5 years before diagnosis, those with extremely dense breasts had a 5.65-fold higher interval cancer risk (95{\%} CI, 3.33 to 9.60) and a 1.43-fold higher screen-detected risk (CI, 1.14 to 1.79) than those with scattered fibroglandular densities. Associations of interval and screendetected cancer with clinical BI-RADS density were similar to those with automated BI-RADS density, regardless of whether density was measured more than 6 months to less than 2 years or 2 to 5 years before diagnosis. Automated and clinical BI-RADS density measures had similar discriminatory accuracy, which was higher for interval than screen-detected cancer (c-statistics: 0.70 vs. 0.62 [P < 0.001] and 0.72 vs. 0.62 [P < 0.001], respectively). Mammography sensitivity was similar for automated and clinical BI-RADS categories: fatty, 93{\%} versus 92{\%}; scattered fibroglandular densities, 90{\%} versus 90{\%}; heterogeneously dense, 82{\%} versus 78{\%}; and extremely dense, 63{\%} versus 64{\%}, respectively. Limitation: Neither automated nor clinical BI-RADS density was assessed on tomosynthesis, an emerging breast screening method. Conclusion: Automated and clinical BI-RADS density similarly predict interval and screen-detected cancer risk, suggesting that either measure may be used to inform women of their breast density.",
author = "Karla Kerlikowske and Scott, {Christopher G.} and Mahmoudzadeh, {Amir P.} and Lin Ma and Stacey Winham and Jensen, {Matthew R.} and Wu, {Fang Fang} and Serghei Malkov and Pankratz, {V. Shane} and Cummings, {Steven R.} and Shepherd, {John A.} and Brandt, {Kathleen R.} and Miglioretti, {Diana L} and Vachon, {Celine M.}",
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TY - JOUR

T1 - Automated and clinical breast imaging reporting and data system density measures predict risk for screen-detected and interval cancers

T2 - A case-control study

AU - Kerlikowske, Karla

AU - Scott, Christopher G.

AU - Mahmoudzadeh, Amir P.

AU - Ma, Lin

AU - Winham, Stacey

AU - Jensen, Matthew R.

AU - Wu, Fang Fang

AU - Malkov, Serghei

AU - Pankratz, V. Shane

AU - Cummings, Steven R.

AU - Shepherd, John A.

AU - Brandt, Kathleen R.

AU - Miglioretti, Diana L

AU - Vachon, Celine M.

PY - 2018/6/5

Y1 - 2018/6/5

N2 - Background: In 30 states, women who have had screening mammography are informed of their breast density on the basis of Breast Imaging Reporting and Data System (BI-RADS) density categories estimated subjectively by radiologists. Variation in these clinical categories across and within radiologists has led to discussion about whether automated BI-RADS density should be reported instead. Objective: To determine whether breast cancer risk and detection are similar for automated and clinical BI-RADS density measures. Design: Case-control. Setting: San Francisco Mammography Registry and Mayo Clinic. Participants: 1609 women with screen-detected cancer, 351 women with interval invasive cancer, and 4409 matched control participants. Measurements: Automated and clinical BI-RADS density assessed on digital mammography at 2 time points from September 2006 to October 2014, interval and screen-detected breast cancer risk, and mammography sensitivity. Results: Of women whose breast density was categorized by automated BI-RADS more than 6 months to 5 years before diagnosis, those with extremely dense breasts had a 5.65-fold higher interval cancer risk (95% CI, 3.33 to 9.60) and a 1.43-fold higher screen-detected risk (CI, 1.14 to 1.79) than those with scattered fibroglandular densities. Associations of interval and screendetected cancer with clinical BI-RADS density were similar to those with automated BI-RADS density, regardless of whether density was measured more than 6 months to less than 2 years or 2 to 5 years before diagnosis. Automated and clinical BI-RADS density measures had similar discriminatory accuracy, which was higher for interval than screen-detected cancer (c-statistics: 0.70 vs. 0.62 [P < 0.001] and 0.72 vs. 0.62 [P < 0.001], respectively). Mammography sensitivity was similar for automated and clinical BI-RADS categories: fatty, 93% versus 92%; scattered fibroglandular densities, 90% versus 90%; heterogeneously dense, 82% versus 78%; and extremely dense, 63% versus 64%, respectively. Limitation: Neither automated nor clinical BI-RADS density was assessed on tomosynthesis, an emerging breast screening method. Conclusion: Automated and clinical BI-RADS density similarly predict interval and screen-detected cancer risk, suggesting that either measure may be used to inform women of their breast density.

AB - Background: In 30 states, women who have had screening mammography are informed of their breast density on the basis of Breast Imaging Reporting and Data System (BI-RADS) density categories estimated subjectively by radiologists. Variation in these clinical categories across and within radiologists has led to discussion about whether automated BI-RADS density should be reported instead. Objective: To determine whether breast cancer risk and detection are similar for automated and clinical BI-RADS density measures. Design: Case-control. Setting: San Francisco Mammography Registry and Mayo Clinic. Participants: 1609 women with screen-detected cancer, 351 women with interval invasive cancer, and 4409 matched control participants. Measurements: Automated and clinical BI-RADS density assessed on digital mammography at 2 time points from September 2006 to October 2014, interval and screen-detected breast cancer risk, and mammography sensitivity. Results: Of women whose breast density was categorized by automated BI-RADS more than 6 months to 5 years before diagnosis, those with extremely dense breasts had a 5.65-fold higher interval cancer risk (95% CI, 3.33 to 9.60) and a 1.43-fold higher screen-detected risk (CI, 1.14 to 1.79) than those with scattered fibroglandular densities. Associations of interval and screendetected cancer with clinical BI-RADS density were similar to those with automated BI-RADS density, regardless of whether density was measured more than 6 months to less than 2 years or 2 to 5 years before diagnosis. Automated and clinical BI-RADS density measures had similar discriminatory accuracy, which was higher for interval than screen-detected cancer (c-statistics: 0.70 vs. 0.62 [P < 0.001] and 0.72 vs. 0.62 [P < 0.001], respectively). Mammography sensitivity was similar for automated and clinical BI-RADS categories: fatty, 93% versus 92%; scattered fibroglandular densities, 90% versus 90%; heterogeneously dense, 82% versus 78%; and extremely dense, 63% versus 64%, respectively. Limitation: Neither automated nor clinical BI-RADS density was assessed on tomosynthesis, an emerging breast screening method. Conclusion: Automated and clinical BI-RADS density similarly predict interval and screen-detected cancer risk, suggesting that either measure may be used to inform women of their breast density.

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