Mammographic density, parity and age at first birth, and risk of breast cancer: an analysis of four case–control studies
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Mammographic density is strongly and consistently associated with breast cancer risk. To determine if this association was modified by reproductive factors (parity and age at first birth), data were combined from four case–control studies conducted in the United States and Japan. To overcome the issue of variation in mammographic density assessment among the studies, a single observer re-read all the mammograms using one type of interactive thresholding software. Logistic regression was used to estimate odds ratios (OR) while adjusting for other known breast cancer risk factors. Included were 1,699 breast cancer cases and 2,422 controls, 74% of whom were postmenopausal. A positive association between mammographic density and breast cancer risk was evident in every group defined by parity and age at first birth (OR per doubling of percent mammographic density ranged between 1.20 and 1.39). Nonetheless, the association appeared to be stronger among nulliparous than parous women (OR per doubling of percent mammographic density = 1.39 vs. 1.24; P interaction = 0.054). However, when examined by study location, the effect modification by parity was apparent only in women from Hawaii and when examined by menopausal status, it was apparent in postmenopausal, but not premenopausal, women. Effect modification by parity was not significant in subgroups defined by body mass index or ethnicity. Adjusting for mammographic density did not attenuate the OR for the association between parity and breast cancer risk by more than 16.4%, suggesting that mammographic density explains only a small proportion of the reduction in breast cancer risk associated with parity. In conclusion, this study did not support the hypothesis that parity modifies the breast cancer risk attributed to mammographic density. Even though an effect modification was found in Hawaiian women, no such thing was found in women from the other three locations.
KeywordsBreast neoplasms Mammographic density Reproductive factors Epidemiology Risk factor Effect modification
This research was supported by the National Cancer Institute, the US Department of Health and Human Services, grant number R03 CA 135699. CGW and SMC were supported for the completion of the study on this project through postdoctoral fellowships on grant number R25 CA 90956.
Conflict of Interest
Dr. Martin Yaffe is one of the founders of Matakina Technology, a manufacturer of software for the assessment of mammographic density. However, the software was not used in the present research, and neither the results nor the way the research was conducted has been influenced by Dr. Yaffe’s involvement in Matakina Technology.
- 3.Conroy SM, Woolcott CG, Byrne C, Nagata C, Ursin G, Vachon CM, Yaffe MJ, Koga K, Pagano I, Maskarinec G (2011) Mammographic density and risk of breast cancer by adiposity: an analysis of four case–control studies. Int J Cancer. doi: 10.1002/ijc.26205
- 12.Collaborative Group on Hormonal Factors in Breast Cancer (2002) Breast cancer and breastfeeding: collaborative reanalysis of individual data from 47 epidemiological studies in 30 countries, including 50302 women with breast cancer and 96973 women without the disease. Lancet 360(9328):187–195CrossRefGoogle Scholar
- 16.Warren R, Skinner J, Sala E, Denton E, Dowsett M, Folkerd E, Healey CS, Dunning A, Doody D, Ponder B, Luben RN, Day NE, Easton D (2006) Associations among mammographic density, circulating sex hormones, and polymorphisms in sex hormone metabolism genes in postmenopausal women. Cancer Epidemiol Biomark Prev 15(8):1502–1508CrossRefGoogle Scholar
- 22.Ursin G, Ma H, Wu AH, Bernstein L, Salane M, Parisky YR, Astrahan M, Siozon CC, Pike MC (2003) Mammographic density and breast cancer in three ethnic groups. Cancer Epidemiol Biomark Prev 12(4):332–338Google Scholar
- 26.Desquilbet L, Mariotti F (2010) Dose–response analyses using restricted cubic spline functions in public health research. Stat Med 29(9):1037–1057Google Scholar
- 27.Szklo M, Nieto FJ (2000) Epidemiology: beyond the basics. Aspen Publishers, GaithersburgGoogle Scholar
- 28.Russo J, Hu YF, Yang X, Russo IH (2000) Developmental, cellular, and molecular basis of human breast cancer. J Natl Cancer Inst Monogr 2000(27):17–37Google Scholar
- 34.Vacek PM, Geller BM (2004) A prospective study of breast cancer risk using routine mammographic breast density measurements. Cancer Epidemiol Biomark Prev 13(5):715–722Google Scholar
- 42.Ghosh K, Brandt KR, Reynolds CA (2009) Histologic markers of mammographic breast density: core-needle biopsy tissue from healthy volunteers. Cancer Res 69(Suppl 2):263SGoogle Scholar