© The Author 2007. Published by Oxford University Press.
ARTICLES |
Longitudinal Measurement of Clinical Mammographic Breast Density to Improve Estimation of Breast Cancer Risk
For the National Institutes of Health Breast Cancer Surveillance Consortium
Affiliations of authors: Departments of Epidemiology and Biostatistics (KK, RSB) and Radiology (RSB), and General Internal Medicine Section, Department of Veterans Affairs (KK), University of California, San Francisco, CA; Group Health Center for Health Studies, Seattle, WA (LI, DLM, DSMB); Department of Biostatistics, University of Washington, Seattle, WA (DLM); Departments of Medical Biostatistics and Pathology, University of Vermont, College of Medicine, Burlington, VT (PMV); Department of Radiology, University of North Carolina, Chapel Hill, NC (BY); Departments of Family Medicine and Public Health and Preventive Medicine, Oregon Health and Science University, Portland, OR (PAC); Applied Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD (RBB)
Correspondence to: Karla Kerlikowske, MD, General Internal Medicine Section, San Francisco Veterans Affairs Medical Center, 111A1, 4150 Clement St, San Francisco, CA 94121 (e-mail: karla.kerlikowske{at}ucsf.edu).
Background: Whether a change over time in clinically measured mammographic breast density influences breast cancer risk is unknown.
Methods: From January 1993 to December 2003, data that included American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) breast density categories (1–4 in order of increasing density) were collected prospectively on 301 955 women aged 30 and older who were not using postmenopausal hormone replacement therapy and underwent at least two screening mammography examinations; 2639 of the women were diagnosed with breast cancer within 1 year of the last examination. Women's first and last BI-RADS breast density (average 3.2 years apart) and logistic regression were used to model the odds of having invasive breast cancer or ductal carcinoma in situ diagnosed within 12 months of the last examination by change in BI-RADS category. Rates of breast cancer adjusted for age, mammography registry, and time between screening examinations were estimated from this model. All statistical tests were two-sided.
Results: The rate (breast cancers per 1000 women) of breast cancer was higher if BI-RADS breast density category increased from 1 to 2 (5.6, 95% confidence interval [CI] = 4.7 to 6.9) or 1 to 3 (9.9, 95% CI = 6.4 to 15.5) compared to when it remained at BI-RADS density of 1 (3.0, 95% CI = 2.3 to 3.9; P<.001 for trend). Similar and statistically significant trends between increased or decreased density and increased or decreased risk of breast cancer, respectively, were observed for women whose breast density category was initially 2 or 3 and changed categories. BI-RADS density of 4 on the first examination was associated with a high rate of breast cancer (range 9.1–13.4) that remained high even if breast density decreased.
Conclusion: An increase in BI-RADS breast density category within 3 years may be associated with an increase in breast cancer risk and a decrease in density category with a decrease in risk compared to breast cancer risk in women in whom breast density category remains unchanged. Two longitudinal measures of BI-RADS breast density may better predict a woman's risk of breast cancer than a single measure.
| CONTEXT AND CAVEATS Prior knowledge High mammographic breast density as measured by the radiologist in the clinic is strongly associated with an increased risk of breast cancer. It was not known whether temporal increases or decreases in a woman's breast density affects her risk of developing breast cancer. Study design The risk of breast cancer was estimated from clinical breast density data that was collected prospectively from registries linked to state tumor registries or regional SEER program data on breast cancer incidence. Contribution This study showed that two breast density measurements separated by an average of 3 years predicted the odds that a women would develop breast cancer more accurately than one measure. Implications Both current and previous breast density measurements should be used by clinicians when evaluating risk with patients. Limitations Further study will be required to determine the relative contributions of the increased accuracy provided by two measures on the one hand and real changes in breast density on the other to the apparent association of temporal changes in breast density and breast cancer risk.
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Manuscript received June 16, 2006; revised December 19, 2006; accepted January 6, 2007.
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J Natl Cancer Inst 2007 99: 337.
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