Karla Kerlikowske, MD; Christopher G. Scott, MS; Amir P. Mahmoudzadeh, MScEng; Lin Ma, MS; Stacey Winham, PhD; Matthew R. Jensen, BS; Fang Fang Wu, BS; Serghei Malkov, PhD; V. Shane Pankratz, PhD; Steven R. Cummings, MD; John A. Shepherd, PhD; Kathleen R. Brandt, MD; Diana L. Miglioretti, PhD; Celine M. Vachon, PhD
Acknowledgment: The authors thank the study participants, mammography facilities, and radiologists for the data they provided for this study.
Grant Support: In part by grants R01 CA177150, P01 2CA154292, and R01 CA207085 from the National Institutes of Health, National Cancer Institute.
Disclosures: Dr. Miglioretti reports grants from the National Institutes of Health during the conduct of the study, and personal and travel fees from Hologic outside the submitted work. Dr. Vachon reports grants from the National Cancer Institute during the conduct of the study and funding from Grail outside the submitted work. Authors not named here have disclosed no conflicts of interest. Disclosures can also be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M17-3008.
Editors' Disclosures: Christine Laine, MD, MPH, Editor in Chief, reports that her spouse has stock options/holdings with Targeted Diagnostics and Therapeutics. Darren B. Taichman, MD, PhD, Executive Editor, reports that he has no financial relationships or interests to disclose. Cynthia D. Mulrow, MD, MSc, Senior Deputy Editor, reports that she has no relationships or interests to disclose. Deborah Cotton, MD, MPH, Deputy Editor, reports that she has no financial relationships or interest to disclose. Jaya K. Rao, MD, MHS, Deputy Editor, reports that she has stock holdings/options in Eli Lilly and Pfizer. Sankey V. Williams, MD, Deputy Editor, reports that he has no financial relationships or interests to disclose. Catharine B. Stack, PhD, MS, Deputy Editor for Statistics, reports that she has stock holdings in Pfizer and Johnson & Johnson.
Reproducible Research Statement:Study protocol and statistical code: Available from Mr. Scott (e-mail, scott.christopher@mayo.edu). Data set: Available after study aims of funded grants are addressed and with appropriate contracts.
Requests for Single Reprints: Karla Kerlikowske, MD, San Francisco Veterans Affairs Medical Center, General Internal Medicine Section, 111A1, 4150 Clement Street, San Francisco, CA 94121; e-mail, Karla.Kerlikowske@ucsf.edu.
Current Author Addresses: Dr. Kerlikowske: San Francisco Veterans Affairs Medical Center, General Internal Medicine Section, 111A1, 4150 Clement Street, San Francisco, CA 94121.
Mr. Scott, Dr. Winham, Mr. Jensen, Ms. Wu, Dr. Brandt, and Dr. Vachon: 200 First Street Southwest, Rochester, MN 55905.
Mr. Mahmoudzadeh: 1 Irving Street, Suite AC109, San Francisco, CA 94143.
Ms. Ma: Kaiser Permanente Division of Research, 2000 Broadway, Oakland, CA 94612.
Dr. Malkov: Applied Materials, 3100 Bowers Avenue, Santa Clara, CA 95054.
Dr. Pankratz: MSC 04-2785, 1 University of New Mexico, Albuquerque, NM 87131.
Dr. Cummings: Mission Hall, Box 0560, 550 16th Street, 2nd Floor, San Francisco, CA 94143.
Dr. Shepherd: University of Hawaii Cancer Center, 701 Ilalo Street, Suite 431, Honolulu, HI 96813.
Dr. Miglioretti: One Shields Avenue, Med Sci 1C, Room 144, Davis, CA 95616.
Author Contributions: Conception and design: K. Kerlikowske, C.M. Vachon.
Analysis and interpretation of the data: K. Kerlikowske, C.G. Scott, A.P. Mahmoudzadeh, S. Winham, M.R. Jensen, V.S. Pankratz, S.R. Cummings, K.R. Brandt, D.L. Miglioretti.
Drafting of the article: K. Kerlikowske, C.G. Scott, S. Winham, J.A. Shepherd.
Critical revision for important intellectual content: K. Kerlikowske, C.G. Scott, S. Winham, V.S. Pankratz, S.R. Cummings, K.R. Brandt, D.L. Miglioretti, C.M. Vachon.
Final approval of the article: K. Kerlikowske, C.G. Scott, A.P. Mahmoudzadeh, L. Ma, S. Winham, M.R. Jensen, F.F. Wu, S. Malkov, V.S. Pankratz, S.R. Cummings, J.A. Shepherd, K.R. Brandt, D.L. Miglioretti, C.M. Vachon.
Provision of study materials or patients: K. Kerlikowske, C.M. Vachon.
Statistical expertise: C.G. Scott, S. Winham, M.R. Jensen, V.S. Pankratz, D.L. Miglioretti.
Obtaining of funding: K. Kerlikowske, S.R. Cummings, C.M. Vachon.
Administrative, technical, or logistic support: K. Kerlikowske, L. Ma, F.F. Wu, S. Malkov.
Collection and assembly of data: K. Kerlikowske, C.G. Scott, A.P. Mahmoudzadeh, L. Ma, M.R. Jensen, S. Malkov, S.R. Cummings, J.A. Shepherd, C.M. Vachon.
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.
To determine whether breast cancer risk and detection are similar for automated and clinical BI-RADS density measures.
Case–control.
San Francisco Mammography Registry and Mayo Clinic.
1609 women with screen-detected cancer, 351 women with interval invasive cancer, and 4409 matched control participants.
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.
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 screen-detected 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.
Neither automated nor clinical BI-RADS density was assessed on tomosynthesis, an emerging breast screening method.
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.
National Cancer Institute.
Kerlikowske K, Scott CG, Mahmoudzadeh AP, et al. Automated and Clinical Breast Imaging Reporting and Data System Density Measures Predict Risk for Screen-Detected and Interval Cancers: A Case–Control Study. Ann Intern Med. 2018;168:757–765. [Epub ahead of print 1 May 2018]. doi: https://doi.org/10.7326/M17-3008
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© 2020
Published: Ann Intern Med. 2018;168(11):757-765.
DOI: 10.7326/M17-3008
Published at www.annals.org on 1 May 2018
Cancer Screening/Prevention, Hematology/Oncology, Prevention/Screening.
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