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Original Research |

Tailoring Breast Cancer Screening Intervals by Breast Density and Risk for Women Aged 50 Years or Older: Collaborative Modeling of Screening OutcomesRisk-Based Breast Cancer Screening Intervals ONLINE FIRST

Amy Trentham-Dietz, PhD*; Karla Kerlikowske, MD, MS*; Natasha K. Stout, PhD; Diana L. Miglioretti, PhD; Clyde B. Schechter, MD, MA; Mehmet Ali Ergun, MSc; Jeroen J. van den Broek, MS; Oguzhan Alagoz, PhD; Brian L. Sprague, PhD; Nicolien T. van Ravesteyn, PhD; Aimee M. Near, MPH; Ronald E. Gangnon, PhD; John M. Hampton, MS; Young Chandler, DrPH, MS, MPH; Harry J. de Koning, MD, PhD; Jeanne S. Mandelblatt, MD, MPH; Anna N.A. Tosteson, ScD, on behalf of the Breast Cancer Surveillance Consortium and Cancer Intervention and Surveillance Modeling Network§
[+] Article, Author, and Disclosure Information

This article was published at www.annals.org on 23 August 2016.

* Drs. Trentham-Dietz and Kerlikowske are co-first authors.

† Drs. Trentham-Dietz, Kerlikowske, Stout, Mandelblatt, and Tosteson were on the writing committee.

‡ Drs. Mandelblatt and Tosteson are co-senior authors.

§ For members of the Breast Cancer Surveillance Consortium and Cancer Intervention and Surveillance Modeling Network, see the Appendix.


From the University of Wisconsin–Madison, Madison, Wisconsin; University of California, San Francisco, San Francisco, California; Harvard Medical School, Boston, Massachusetts; University of California Davis School of Medicine, Sacramento, California; Albert Einstein College of Medicine, Bronx, New York; Erasmus Medical Center, Rotterdam, the Netherlands; University of Vermont, Burlington, Vermont; Georgetown University Medical Center, Washington, DC; and Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire.

Note: This work was done by 3 independent modeling teams from Erasmus Medical Center (principal investigator, Dr. de Koning); Georgetown University Medical Center, Lombardi Comprehensive Cancer Center, and Albert Einstein College of Medicine (principal investigators, Drs. Mandelblatt and Schechter); and University of Wisconsin–Madison, Harvard Medical School, and Harvard Pilgrim Health Care (principal investigators, Drs. Trentham-Dietz, Alagoz, and Stout).

Acknowledgment: The authors thank Rocky Feuer, Sandra Lee, Hui Huang, Donald Berry, Kathleen Cronin, Eveline A. Heijnsdijk, Allison Kurian, and Donald Weaver for their advice on this project.

Grant Support: This work was supported by the National Institutes of Health (NIH) under National Cancer Institute (NCI) grants P01 CA154292, P30 CA014520, and U01 CA152958. Data collection for model inputs from the Breast Cancer Surveillance Consortium (BCSC) was supported by the NCI grants P01 CA154292 and U54 CA163303 and contract HSN261201100031C. The collection of BCSC cancer and vital status data used in this study was supported in part by several state public health departments and cancer registries throughout the United States. For a full description of these sources, please see http://www.bcsc-research.org/work/acknowledgement.html.

Disclosures: Dr. Trentham-Dietz reports grants from NCI during the conduct of the study. Dr. Stout reports grants from NIH/NCI during the conduct of the study. Dr. Miglioretti reports grants from NCI during the conduct of the study. Dr. Schechter reports grants from NCI during the conduct of the study and personal fees from the American Society of Breast Surgeons outside the submitted work. Dr. Alagoz reports grants from the NIH/NCI during the conduct of the study and personal fees from Renaissance Rx and Ally Clinical Diagnostics outside the submitted work. Dr. Sprague reports grants from NIH during the conduct of the study. Dr. van Ravesteyn reports grants from NIH/NCI during the conduct of the study. Dr. Gangnon reports grants from NCI during the conduct of the study. Dr. de Koning reports grants from the Netherlands National Institute for Public Health and the Environment during the conduct of the study and grants from SCOR Global Risk Center and Genomic Health Canada outside the submitted work. Dr. Tosteson reports grants from NIH/NCI during the conduct of the study. Authors not named here have disclosed no conflicts of interest. Disclosures can also be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M16-0476.

Editors' Disclosures: Christine Laine, MD, MPH, Editor in Chief, reports that she has no financial relationships or interests to disclose. Darren B. Taichman, MD, PhD, Executive Deputy 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: Not available. Statistical code: Detailed information about the models is available online at http://cisnet.cancer.gov/breast/profiles.html and in reference 14. Data set: Input and output data from the models are available at reference 14 and by contacting Dr. Trentham-Dietz (e-mail, trentham@wisc.edu).

Requests for Single Reprints: Amy Trentham-Dietz, PhD, University of Wisconsin–Madison Carbone Cancer Center, 610 Walnut Street, WARF Room 307, Madison, WI 53726; e-mail, trentham@wisc.edu.

Current Author Addresses: Dr. Trentham-Dietz and Mr. Hampton: University of Wisconsin Carbone Cancer Center, 610 Walnut Street, WARF Room 307, Madison, WI 53726.

Dr. Kerlikowske: 4150 Clement Street, VAMC (111A1), San Francisco, CA 94121.

Dr. Stout: Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Landmark Center, 401 Park Drive, Suite 401, Boston, MA 02215.

Dr. Miglioretti: Department of Public Health Sciences, University of California Davis School of Medicine, One Shields Avenue, Med-Sci 1C, Room 145, Davis, CA 95616.

Dr. Schechter: Department of Family and Social Medicine, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Block Building 406, Bronx, NY 10461.

Mr. Ergun and Dr. Alagoz: Department of Industrial and Systems Engineering, University of Wisconsin–Madison, 1513 University Avenue, Madison, WI 53706.

Mr. van den Broek and Drs. van Ravesteyn and de Koning: Erasmus Medical Center, University Medical Center Rotterdam, P.O. Box 2040, 3000 CA, Rottterdam, the Netherlands.

Dr. Sprague: University of Vermont, Office of Health Promotion Research, 1 South Prospect Street, Burlington, VT 05401.

Ms. Near and Drs. Chandler and Mandelblatt: Lombardi Comprehensive Cancer Center, Georgetown University, 3300 Whitehaven Street Northwest, Suite 4100, Washington, DC 20007.

Dr. Gangnon: University of Wisconsin–Madison, Department of Population Health Sciences, 610 Walnut Street, Madison, WI 53726.

Dr. Tosteson: Geisel School of Medicine at Dartmouth, One Medical Center Drive (HB7505), Lebanon, NH 03756.

Author Contributions: Conception and design: A. Trentham-Dietz, K. Kerlikowske, N.K. Stout, D.L. Miglioretti, C.B. Schechter, O. Alagoz, B.L. Sprague, H.J. de Koning, J.S. Mandelblatt, A.N.A. Tosteson.

Analysis and interpretation of the data: A. Trentham-Dietz, K. Kerlikowske, N.K. Stout, D.L. Miglioretti, C.B. Schechter, van den Broek, O. Alagoz, B.L. Sprague, N.T. van Ravesteyn, R.E. Gangnon, J.M. Hampton, Y. Chandler, H.J. de Koning, J.S. Mandelblatt, A.N.A. Tosteson.

Drafting of the article: A. Trentham-Dietz, K. Kerlikowske, N.K. Stout, van den Broek, O. Alagoz, J.S. Mandelblatt, A.N.A. Tosteson.

Critical revision of the article for important intellectual content: A. Trentham-Dietz, K. Kerlikowske, N.K. Stout, D.L. Miglioretti, C.B. Schechter, van den Broek, O. Alagoz, B.L. Sprague, N.T. van Ravesteyn, R.E. Gangnon, H.J. de Koning, J.S. Mandelblatt, A.N.A. Tosteson.

Final approval of the article: A. Trentham-Dietz, K. Kerlikowske, N.K. Stout, D.L. Miglioretti, C.B. Schechter, M.A. Ergun, van den Broek, O. Alagoz, B.L. Sprague, N.T. van Ravesteyn, A.M. Near, R.E. Gangnon, J.M. Hampton, Y. Chandler, H.J. de Koning, J.S. Mandelblatt, A.N.A. Tosteson.

Provision of study materials or patients: K. Kerlikowske.

Statistical expertise: A. Trentham-Dietz, N.K. Stout, D.L. Miglioretti, C.B. Schechter, van den Broek, R.E. Gangnon, A.N.A. Tosteson.

Obtaining of funding: A. Trentham-Dietz, K. Kerlikowske, D.L. Miglioretti, B.L. Sprague, J.S. Mandelblatt, A.N.A. Tosteson.

Administrative, technical, or logistic support: A. Trentham-Dietz, K. Kerlikowske, M.A. Ergun, A.M. Near, J.S. Mandelblatt, A.N.A. Tosteson.

Collection and assembly of data: A. Trentham-Dietz, K. Kerlikowske, N.K. Stout, D.L. Miglioretti, M.A. Ergun, B.L. Sprague, A.M. Near, J.M. Hampton, J.S. Mandelblatt, A.N.A. Tosteson.


Ann Intern Med. Published online 23 August 2016 doi:10.7326/M16-0476
© 2016 American College of Physicians
Text Size: A A A

Background: Biennial screening is generally recommended for average-risk women aged 50 to 74 years, but tailored screening may provide greater benefits.

Objective: To estimate outcomes for various screening intervals after age 50 years based on breast density and risk for breast cancer.

Design: Collaborative simulation modeling using national incidence, breast density, and screening performance data.

Setting: United States.

Patients: Women aged 50 years or older with various combinations of breast density and relative risk (RR) of 1.0, 1.3, 2.0, or 4.0.

Intervention: Annual, biennial, or triennial digital mammography screening from ages 50 to 74 years (vs. no screening) and ages 65 to 74 years (vs. biennial digital mammography from ages 50 to 64 years).

Measurements: Lifetime breast cancer deaths, life expectancy and quality-adjusted life-years (QALYs), false-positive mammograms, benign biopsy results, overdiagnosis, cost-effectiveness, and ratio of false-positive results to breast cancer deaths averted.

Results: Screening benefits and overdiagnosis increase with breast density and RR. False-positive mammograms and benign results on biopsy decrease with increasing risk. Among women with fatty breasts or scattered fibroglandular density and an RR of 1.0 or 1.3, breast cancer deaths averted were similar for triennial versus biennial screening for both age groups (50 to 74 years, median of 3.4 to 5.1 vs. 4.1 to 6.5 deaths averted; 65 to 74 years, median of 1.5 to 2.1 vs. 1.8 to 2.6 deaths averted). Breast cancer deaths averted increased with annual versus biennial screening for women aged 50 to 74 years at all levels of breast density and an RR of 4.0, and those aged 65 to 74 years with heterogeneously or extremely dense breasts and an RR of 4.0. However, harms were almost 2-fold higher. Triennial screening for the average-risk subgroup and annual screening for the highest-risk subgroup cost less than $100 000 per QALY gained.

Limitation: Models did not consider women younger than 50 years, those with an RR less than 1, or other imaging methods.

Conclusion: Average-risk women with low breast density undergoing triennial screening and higher-risk women with high breast density receiving annual screening will maintain a similar or better balance of benefits and harms than average-risk women receiving biennial screening.

Primary Funding Source: National Cancer Institute.

Figures

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Appendix Figure.

Schema representing breast cancer natural history and screening as simulated in the models.

Sojourn time is the duration of the preclinical, screen-detectable phase of the tumor. Lead time is the interval from screen detection to the time of clinical diagnosis, which is when the tumor would have surfaced without screening. See Appendix Table 2 for the description of the implementation of screening benefit in the 3 simulation models.

Grahic Jump Location
Grahic Jump Location
Figure.

False-positive mammograms per breast cancer death averted.

Data for women aged 50 to 74 y (top) and 65 to 74 years (bottom) are shown according to screening frequency and risk level (relative risk group and breast density level) using an exemplar model (Model E). Values for all screening frequencies were compared with the scenario of no mammography screening. Values for women aged 65 to 74 y assume all women received biennial screening during ages 50 to 64 y. Dashed lines show this value for women with average density and average risk receiving biennial screening (147.7 for women aged 50 to 74 y and 105.8 for women aged 65 to 74 y). Having fewer false-positive mammograms per breast cancer death averted than this level—in other words, a value below the dashed line—would be more favorable.

Grahic Jump Location

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Dilutional Mammographic Screening
Posted on September 14, 2016
Mark A. Helvie, MD
University of Michigan Health System
Conflict of Interest: None Declared
The principal purpose of screening mammography is to save lives from breast cancer, not to save mammograms or needle biopsies. The authors’ data shows that most lives (and life-years) are saved by annual mammography rather than biennial or triennial mammography across all density and risk levels (1). These mortality differences are enormous, which may be a surprise to readers of the narrative. For the common group of women with scattered (low) density and average risk, annual screening saves 80% more life-years (106/1000) than triennial screening (59/1000) and 38% more than biennial screening (77/1000). Similar differences are estimated for the common group of average risk women with heterogeneously dense breast tissue (130/1000 vs. 72/1000 vs. 94/1000 life-years gained).

The implication there is a numeric equivalency of a death averted or a life-year gained with a certain number of mammograms or needle biopsies is a subjective judgement. Women have expressed a high tolerance for recalls and needle biopsies relative to the benefits of mammographic screening and there is no consensus on their value (2, 3). An objective ratio from their data is approximately 0.5-2 life-years are gained for each benign needle biopsy recommendation among women electing annual screening. The authors data also show most (73-88%) women will never be recommended for a (benign) biopsy during the entire 25 years of annual screening. The truth is these false positive biopsies can be a vital source of pathologic information (such as atypical ductal hyperplasia) that determines risk level in the advocated risk-based screening.

All models are limited by underlying assumptions and omissions in their parameters. Especially noteworthy is the potential morbidity reduction benefit with screening (4). Earlier detection with frequent screening may be preferred to later detection and resultant treatment harms even if mortality is similar. The current models do show annual screening provides the greatest mortality benefit across all risk levels and breast densities which is the principle purpose of screening. Women electing such an annual schedule should not face financial risk for their decision.


1. Trentham-Dietz A, Kerlikowske K, Stout NK, Miglioretti DL, Schechter CB, Ergun MA, et al. Tailoring Breast Cancer Screening Intervals by Breast Density and Risk for Women Aged 50 Years or Older: Collaborative Modeling of Screening Outcomes. Ann Intern Med. 2016;Epub ahead of print.
2. Oeffinger KC, Fontham ET, Etzioni R, Herzig A, Michaelson JS, Shih YC, et al. Breast Cancer Screening for Women at Average Risk: 2015 Guideline Update From the American Cancer Society. JAMA. 2015;314(15):1599-614.
3. Schwartz LM, Woloshin S, Sox HC, Fischhoff B, Welch HG. US women's attitudes to false positive mammography results and detection of ductal carcinoma in situ: cross sectional survey. BMJ. 2000;320(7250):1635-40.
4. Coldman AJ, Phillips N, Speers C. A retrospective study of the effect of participation in screening mammography on the use of chemotherapy and breast conserving surgery. Int J Cancer. 2007;120(10):2185-90.

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