BRIEF COMMUNICATION

Mammographic Breast Density and Family History of Breast Cancer

Elad Ziv, John Shepherd, Rebecca Smith-Bindman, Karla Kerlikowske

Affiliations of authors: E. Ziv (Division of General Internal Medicine and Department of Medicine), J. Shepherd (Department of Radiology), R. Smith-Bindman (Departments of Medicine and Radiology), K. Kerlikowske (General Internal Medicine Section, Department of Veterans Affairs and Departments of Medicine and Epidemiology and Biostatistics), University of California, San Francisco.

Correspondence to: Elad Ziv, M.D., UCSF Women’s Health Clinical Research Center, 1635 Divisadero St., Suite 600, San Francisco, CA 94115 (e-mail: eziv{at}itsa.ucsf.edu).

ABSTRACT

The association between mammographic breast density and breast cancer risk may be the result of genetic and/or environmental factors that determine breast density. We reasoned that if the genetic factors that underlie breast density increase breast cancer risk, then breast density should be associated with family history of breast cancer. Therefore, we determined the association between mammographic density and family history of breast cancer among women in the San Francisco Mammography Registry. Mammographic density was classified using the four BI-RADS criteria: 1 = almost entirely fatty, 2 = scattered fibroglandular tissue, 3 = heterogeneously dense, and 4 = extremely dense. We adjusted for age, body mass index, hormone replacement therapy use, menopause status, and personal history of breast cancer. Compared with women with BI-RADS 1 readings, women with higher breast density were more likely to have first-degree relatives with breast cancer (BI-RADS 2, odds ratio [OR] = 1.37, 95% confidence interval [CI] = 0.96 to 1.89; BI-RADS 3, OR = 1.70, 95% CI = 1.19 to 2.40; BI-RADS 4, OR = 1.70, 95% CI = 1.05 to 2.71). Thus, the genetic factors that determine breast density may determine breast cancer risk.


Several studies have demonstrated that women with higher breast density on mammography are at increased risk of developing breast cancer (1,2). Breast density has been shown to have a heritable component and may serve as a marker of genetic risk for breast cancer (3,4). Breast density is also affected by exogenous estrogens (58), reproductive history (5,9), and dietary factors (10,11), suggesting that it may be a marker of exposure to environmental factors that predispose women to breast cancer. Thus, the association between breast cancer and breast density may be the result of genetic factors, environmental factors, or both.

To determine whether the association between breast density and breast cancer is, at least in part, determined by genetic factors, we examined the association between breast density and a woman’s report of family history of breast cancer. We reasoned that if the genetic factors that determine breast density also increase the risk of breast cancer, then a woman’s own breast density measurement would be associated with breast cancer risk in her first-degree relatives. Therefore, we examined the association between mammographic breast density among participants in the National Institutes of Health-funded San Francisco Mammography Registry and a history of breast cancer among first-degree relatives.

The San Francisco Mammography Registry includes 13 radiology facilities in the city of San Francisco and has been operating since 1995. Demographic, clinical, and risk factor information, mammographic interpretations, and cancer outcomes obtained through linkage with the regional population-based Surveillance, Epidemiology, and End Results (SEER)1 program are collected for all women undergoing screening or diagnostic mammography in San Francisco. For this study, we included women who had mammography between January 1997 and July 2001, had at least two mammographic density readings during the study period, and responded to questions about family history of breast cancer and height and weight. To reduce the variability of the breast density measurement, we further restricted the study population to women whose density reading did not differ between the first and second reading. Of the 164 971 women who had mammograms during the time period, 8665 met the eligibility requirements by having data on family history, mammographic breast density, and body mass index (BMI), and by having had at least two mammograms. We excluded 2519 women whose mammographic density readings were inconsistent over time, leaving 6146 women in the analysis. The study was approved by the institutional review board.

Breast density was classified by radiologists at the time of mammography according to the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) (12) categories of 1 (almost entirely fatty), 2 (scattered fibroglandular tissue), 3 (heterogeneously dense), and 4 (extremely dense). At each screening examination, demographic information and a breast health history were obtained by questionnaire, which included questions about personal history of breast cancer, menopause status, history of breast cancer in first-degree relatives (including age at diagnosis), current hormone replacement therapy (HRT) use, height, and weight. Women were considered to be "current HRT users" if they self-reported HRT use at either of the two screening examinations used in this analysis.

We determined whether BI-RADS readings were associated with other variables by using chi-square tests (for HRT, personal history of breast cancer, menopause status) or analysis of variance (ANOVA; for age and BMI). We used multivariable logistic regression models to evaluate the association between breast density and family history of breast cancer. Covariates included in the models were selected on the basis of reported or suspected association with family history of breast cancer or breast density. Because personal history of breast cancer is known to be associated with both increased risk of family history of breast cancer and increased breast density, it may be a confounder in our analysis and was therefore treated as a covariate in our models. We also performed alternative analyses in which data from only those women without a personal history of breast cancer were analyzed. Analyses were performed using Stata, version 6 (Stata Corp., College Station, TX). All statistical tests were two-sided.

Breast density was associated with age, menopause status, BMI, and HRT use (Table 1Go). Women with the highest breast density were more likely to be younger, to be premenopausal, and to have lower BMI compared with women with the lowest breast density. Compared with women with BI-RADS 1 readings, HRT use was more common among women with BI-RADS 2 and 3 readings and less common among women with BI-RADS 4 readings. Women with BI-RADS 4 readings were the youngest and least likely to use HRT compared with women in all other groups. Restricting comparisons to women aged 50 years or older, women with BI-RADS 4 readings were statistically significantly more likely to have used HRT compared with women with BI-RADS 1 readings. Breast density was only nominally associated with personal history of breast cancer in unadjusted analysis (Table 1Go), but after adjustment for age, there was a statistically significantly increased risk of breast cancer for women with higher breast density (P<.001).


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Table 1. Predictors of breast density among women in the San Francisco Mammography Registry*
 
Women with higher breast density were more likely to have a first-degree relative who had breast cancer than women with low breast density (BI-RADS 1). Compared with women who had BI-RADS 1 readings, the risk of having an affected first-degree relative was statistically significantly increased among those with a BI-RADS 3 reading (odds ratio [OR] = 1.70, 95% confidence interval [CI] = 1.19 to 2.40) or a BI-RADS 4 reading (OR = 1.70, 95% CI = 1.05 to 2.71) and had a trend toward increasing probability for women with a BI-RADS 2 reading (OR = 1.37, 95% CI = 0.96 to 1.89) (Fig. 1Go). Similarly, there was an association between breast density and mother’s history of breast cancer and sister’s history of breast cancer (most comparisons were statistically significant or bordered on statistical significance). In analyses that included only women without a personal history of breast cancer, the association between breast density and family history of breast cancer remained statistically significant (data not shown). In analyses that included only women who had screening mammograms, we also found a consistent association between breast density and family history of breast cancer (data not shown).



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Fig. 1. Association between breast density and family history of breast cancer among women in the San Francisco Mammography Registry. Association between breast density and history of breast cancer in first-degree relatives determined by multivariable logistic regression models. The analyses were adjusted for age, hormone replacement therapy use, body mass index, menopause status, and personal history of breast cancer. Breast density was determined from mammograms using the Breast Imaging Reporting and Data System (BI-RADS) classification criteria: 1 = almost entirely fatty, 2 = scattered fibroglandular tissue, 3 = heterogeneously dense, 4 = extremely dense. Vertical lines represent the 95% confidence intervals (CI). Odds ratios are in comparison to women with BI-RADS 1 readings.

 
We found a statistically significant association between increased breast density, as determined by BI-RADS criteria, and history of a first-degree relative with breast cancer, even after adjusting for multiple potential confounders. We identified an association that may be the result of shared genetic and/or environmental factors among family members that affect breast density and breast cancer risk. However, a recent study of twins suggests that most of the variation in breast density appears to be related to genetic factors (3). In our analysis, we adjusted for known nongenetic factors that affect breast density and found that the association was robust to these adjustments. If the association between family members’ breast density and breast cancer risk is a result of similar parity or HRT use patterns for example, then adjustment for these factors should have attenuated the effect. Thus, our analysis is consistent with the possibility of there being a gene or genes that affect both breast density and the risk of breast cancer. Although breast density may serve as a useful intermediate marker in identifying other breast cancer susceptibility genes, genes that account for the association between breast density and breast cancer risk have yet to be identified.

A preliminary linkage study (13) identified two regions on chromosomes 6 and 20 that were suggestive of linkage with breast density. Haiman et al. (14) identified an association between polymorphisms in the genes encoding catechol-O-methyltransferase (COMT) and aromatase (CYP19) and breast density. However, because the association between these genes and breast cancer has not been proven (15), there may be other genes that are responsible for the association between breast density and breast cancer.

Our study used BI-RADS, a qualitative measurement of mammographic breast density. A more extensive analysis of the association between family history of breast cancer risk and quantitative measurements of breast density may provide additional information about the strength of this association.

NOTES

Supported in part by cooperative agreement U01CA63740 from the Breast Cancer Surveillance Consortium of the National Cancer Institute, National Institutes of Health, Department of Health and Human Services; CRTG 02-084-01-CCE (to E. Ziv) from the American Cancer Society; and by a K12 grant from the University of California, San Francisco.

1 Editor’s note: SEER is a set of geographically defined, population-based, central cancer registries in the United States, operated by local nonprofit organizations under contract to the National Cancer Institute (NCI). Registry data are submitted electronically without personal identifiers to the NCI on a biannual basis, and the NCI makes the data available to the public for scientific research. Back

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Manuscript received August 12, 2002; revised January 8, 2003; accepted January 16, 2003.


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