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Using Clinical Factors and Mammographic Breast Density to Estimate Breast Cancer Risk: Development and Validation of a New Predictive Model

Jeffrey A. Tice, MD; Steven R. Cummings, MD; Rebecca Smith-Bindman, MD; Laura Ichikawa, MS; William E. Barlow, PhD; and Karla Kerlikowske, MD
[+] Article, Author, and Disclosure Information

From University of California, San Francisco, San Francisco, California, and Cancer Research and Biostatistics and University of Washington, Seattle, Washington.

Acknowledgment: The authors thank the BCSC investigators, participating mammography facilities, and radiologists for the data they provided for the study. A list of the BCSC investigators and procedures for requesting BCSC data for research purposes are available at http://breastscreening.cancer.gov/.

Grant Support: By the National Cancer Institute–funded Breast Cancer Surveillance Consortium cooperative agreement (grants U01CA63740, U01CA86076, U01CA86082, U01CA63736, U01CA70013, U01CA69976, U01CA63731, and U01CA70040) and a Building Interdisciplinary Research Careers in Women's Health faculty development grant (K12 AR47659).

Potential Financial Conflicts of Interest:Consultancies: S.R. Cummings (Eli Lilly). Honoraria: S.R. Cummings (Eli Lilly).

Grants received: J.A. Tice (Building Interdisciplinary Careers in Women's Health [career development award]), S.R. Cummings (Eli Lilly, Lilly Foundation). Grants pending: S.R. Cummings (Eli Lilly, Lilly Foundation).

Reproducible Research Statement: The data set is available through the BCSC Web site (available at http://breastscreening.cancer.gov/).

Requests for Single Reprints: Jeffrey A. Tice, MD, Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, 1701 Divisadero Street, Suite 554, San Francisco, CA 94143-1732; e-mail, jtice@medicine.ucsf.edu.

Current Author Addresses: Dr. Tice: Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, 1701 Divisadero Street, Suite 554, San Francisco, CA 94143-1732.

Dr. Cummings: San Francisco Coordinating Center, 185 Berry Street, Lobby 4, Suite 5700, San Francisco, CA 94107.

Dr. Smith-Bindman: University of California, San Francisco, 185 Berry Street, Suite 350, San Francisco, CA 94143.

Ms. Ichikawa: The Center for Health Studies, 1730 Minor Avenue, Suite 1600, Seattle, WA 98101-1448.

Dr. Barlow: Cancer Research and Biostatistics, 1730 Minor Avenue, Suite 1900, Seattle, WA 98101.

Dr. Kerlikowske: University of California, San Francisco, 4150 Clement Street, San Francisco, CA 94121.

Author Contributions: Conception and design: J.A. Tice, S.R. Cummings, W.E. Barlow, K. Kerlikowske.

Analysis and interpretation of the data: J.A. Tice, S.R. Cummings, W.E. Barlow, K. Kerlikowske.

Drafting of the article: J.A. Tice, K. Kerlikowske.

Critical revision of the article for important intellectual content: J.A. Tice, S.R. Cummings, L. Ichikawa, K. Kerlikowske.

Final approval of the article: J.A. Tice, S.R. Cummings, L. Ichikawa, W.E. Barlow, K. Kerlikowske.

Provision of study materials or patients: K. Kerlikowske.

Statistical expertise: J.A. Tice, W.E. Barlow.

Obtaining of funding: J.A. Tice, W.E. Barlow, K. Kerlikowske.

Administrative, technical, or logistic support: S.R. Cummings, K. Kerlikowske.

Collection and assembly of data: L. Ichikawa, W.E. Barlow, K. Kerlikowske.

Ann Intern Med. 2008;148(5):337-347. doi:10.7326/0003-4819-148-5-200803040-00004
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At the time of their earliest mammogram in the BCSC, 46% of women in our study were younger than age 50 years (Table 1). The majority of women were white (71%), but more than 25 000 women represented each of the black, Asian, and Hispanic groups. During a median follow-up of 5.3 years, 14 766 women developed invasive breast cancer. As expected, older age, non-Hispanic white race or ethnicity, a family history of breast cancer, a personal history of breast biopsies, and high breast density were all associated with the development of breast cancer (Table 1).

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Appendix Figure.
The Breast Cancer Surveillance Consortium breast density model algorithm.

BI-RADS = Breast Imaging Reporting and Data System; SEER = Surveillance, Epidemiology, and End Results.

Grahic Jump Location




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Submit a Comment/Letter
Estimating Hormone Receptor Positive Breast Cancer Risk
Posted on March 28, 2008
Rowan T Chlebowski
Conflict of Interest: None Declared

We agree with the argument presented by Tice and colleagues [1] that an efficient approach to breast cancer risk stratification could start with a simple model. In separate Women's Health Initiative cohorts, [2] we have recently developed a risk prediction model that includes only three variables and evaluated its performance for predicting development of estrogen receptor positive breast cancer in postmenopausal women. [2] Women who were 55 years or older with either a previous breast biopsy or a family history of breast cancer in first degree relatives had a five-year breast cancer risk of > 1.67%, one threshold for chemoprevention consideration. This WHI model was evaluated as being nearly as accurate as the National Cancer Institute Breast Cancer Risk Assessment tool (the Gail model). [3] Its use would facilitate rapid pre-screening for breast cancer risk in clinical settings. Since agents either approved (tamoxifen, raloxifene) [4] or under evaluation (aromatase inhibitors) [5] for breast cancer risk reduction almost exclusively target hormone receptor positive cancers, has the model of Tice and colleagues been similarly evaluated for risk prediction of hormone receptor positive breast cancers, particularly in postmenopausal women?

1. Tice JA, Cummings SR, Smith-Bindman , et al. Using clinical factors and mammmographic breast density to estimate breast cancer risk: development and validation of a new predictive model. Ann Intern Med 2008;148: 337-347.

2. Chlebowski RT, Anderson GL, Lane DS, et al. Predicting risk of breast cancer in postmenopausal women by hormone receptor status. J Natl Cancer Inst 2007; 99: 1695-705.

3. http://www.cancer.gov/bcrisktool/ (accessed March 24, 2008).

4. Vogel VG, Costantino JP, Wickerham DL, et al. Effects of tamoxifen vs raloxifene on the risk of developing invasive breast cancer and other disease outcomes: the NSABP Study of Tamoxifen and Raloxifene (STAR) P-2 Trial. JAMA 2006; 295(23): 2727-41.

5. Goss PE, Richardson H, Chlebowski RT, et al. National Cancer Institute of Canada Clinical Trials Group MAP.3 Trial: evaluation of exemestane to prevent breast cancer in postmenopausal women at risk. Clin Breast Cancer 2007;7(11):895-900.

Conflict of Interest:

None declared

Submit a Comment/Letter

Summary for Patients

Using Breast Density to Predict Breast Cancer Risk

The summary below is from the full report titled “Using Clinical Factors and Mammo-graphic Breast Density to Estimate Breast Cancer Risk: Development and Validation of a New Predictive Model.” It is in the 4 March 2008 issue of Annals of Internal Medicine (volume 148, pages 337-347). The authors are J.A. Tice, S.R. Cummings, R. Smith-Bindman, L. Ichikawa, W.E. Barlow, and K. Kerlikowske.


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