Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Clinical and epidemiological issues in mammographic density

Abstract

High mammographic density is associated with an increased risk of breast cancer, and of all known breast cancer risk factors has the greatest attributable fraction. Mammographic density is estimated to account for 16% of all breast cancers, but can be altered by endogenous and exogenous hormonal factors, and generally declines with age. Confounding factors such as age, parity, menopausal status and BMI make the interpretation of mammographic density particularly challenging. Furthermore, none of the established means of measuring mammographic density are entirely satisfactory because they are time consuming or subjective. It is hoped that by adding information regarding mammographic density to existing models of breast cancer risk assessment, the accuracy of individual risk assessments can be improved. Although mammographic density has clearly been shown to be a powerful factor for predicting the risk of developing breast cancer, its potential role in assessing hormonal preventive regimens and helping to tailor screening algorithms cannot be fully realized until we have more-precise, simple and reproducible density measures.

Key Points

  • Mammographic density appears as white areas on a mammogram and it comprises fibroglandular tissue, stroma and epithelium within the breast

  • The current ways of measuring mammographic density are time consuming and subjective

  • Mammographic density is one of the most important indicators of breast cancer risk; the greater the mammographic density the greater the breast cancer risk

  • Mammographic density can be altered by endogenous and exogenous hormonal factors, and generally declines with age

  • Models to predict a woman's risk of breast cancer from her mammographic density and other risk factors are currently being developed

  • Mammographic density has considerable potential in risk stratification and in monitoring the effects of interventions in risk alteration, but further work on measuring density and risk prediction is required

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Mammograms of a breast with very low and high density.
Figure 2: A schematic representation of some of the methods for assessing mammographic density.

Similar content being viewed by others

References

  1. Wolfe, J. N. Breast patterns as an index of risk for developing breast cancer. AJR Am. J. Roentgenol. 126, 1130–1137 (1976).

    Article  CAS  PubMed  Google Scholar 

  2. McCormack, V. A. & dos Santos Silva, I. Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis. Cancer Epidemiol. Biomarkers Prev. 15, 1159–1169 (2006).

    Article  PubMed  Google Scholar 

  3. Are You Dense. Are you dense? Exposing the best-kept secret [online], (2012).

  4. Gram, I. T., Funkhouser, E. & Tabar, L. The Tabar classification of mammographic parenchymal patterns. Eur. J. Radiol. 24, 131–136 (1997).

    Article  CAS  PubMed  Google Scholar 

  5. D'Orsi, C. J. et al. Breast imaging reporting and data system: ACR BI-RADS. Breast Imaging Atlas, Reston, VA American College of Radiology (2003).

    Google Scholar 

  6. Boyd, N. F. et al. Body size, mammographic density, and breast cancer risk. Cancer Epidemiol. Biomarkers Prev. 15, 2086–2092 (2006).

    Article  PubMed  Google Scholar 

  7. Boyd, N. F. et al. Mammographic density and the risk and detection of breast cancer. N. Engl. J. Med. 356, 227–236 (2007).

    Article  CAS  PubMed  Google Scholar 

  8. Cuzick, J. et al. Tamoxifen-induced reduction in mammographic density and breast cancer risk reduction: a nested case-control study. J. Natl. Cancer Inst. 103, 744–752 (2011).

    Article  CAS  PubMed  Google Scholar 

  9. Duffy, S. W. et al. Visually assessed breast density, breast cancer risk and the importance of the craniocaudal view. Breast Cancer Res. 10, R64 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Wolfe, J. N., Saftlas, A. F. & Salane, M. Mammographic parenchymal patterns and quantitative evaluation of mammographic densities: a case-control study. AJR Am. J. Roentgenol. 148, 1087–1092 (1987).

    Article  CAS  PubMed  Google Scholar 

  11. Byng, J. W. et al. Analysis of mammographic density and breast cancer risk from digitized mammograms. Radiographics 18, 1587–1598 (1998).

    Article  CAS  PubMed  Google Scholar 

  12. Heine, J. J. et al. An automated approach for estimation of breast density. Cancer Epidemiol. Biomarkers Prev. 17, 3090–3097 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Yaffe, M. J. Mammographic density. Measurement of mammographic density. Breast Cancer Res. 10, 209 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Diffey, J., Hufton, A. & Astley, S. in 8th international workshop on digital mammography (eds Astley, S., Brady M. & Zwiggelaar, R.) 1–10 (Manchester, 2006).

    Book  Google Scholar 

  15. Aitken, Z. et al. Screen-film mammographic density and breast cancer risk: a comparison of the volumetric standard mammogram form and the interactive threshold measurement methods. Cancer Epidemiol. Biomarkers Prev. 19, 418–428 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Jeffreys, M., Warren, R., Highnam, R. & Davey Smith, G. Breast cancer risk factors and a novel measure of volumetric breast density: cross-sectional study. Br. J. Cancer 98, 210–216 (2008).

    Article  CAS  PubMed  Google Scholar 

  17. Hartman, K., Highnam, R., Warren, R. & Jackson, V. in Digital Mammography, lecture notes in computer science (Ed Krupinski, E. A.) 5116, 33–39 (2008).

    Google Scholar 

  18. Malkov, S., Wang, J., Kerlikowske, K., Cummings, S. R. & Shepherd, J. A. Single x-ray absorptiometry method for the quantitative mammographic measure of fibroglandular tissue volume. Medical Phys. 36, 5525–5536 (2009).

    Article  Google Scholar 

  19. Pawluczyk, O. et al. A volumetric method for estimation of breast density on digitized screen-film mammograms. Med Phys. 30, 352–364 (2003).

    Article  PubMed  Google Scholar 

  20. Kaufhold J., Thomas, J. A., Eberhard, J. W., Galbo, C. E. & Trotter, D. E. A calibration approach to glandular tissue composition estimation in digital mammography. Med Phys. 29, 1867–1880 (2002).

    Article  CAS  PubMed  Google Scholar 

  21. Gao, J., Warren, R., Warren-Forward, H. & Forbes, J. F. Reproducibility of visual assessment on mammographic density. Breast Cancer Res. Treat. 108, 121–127 (2008).

    Article  PubMed  Google Scholar 

  22. Byrne, C. et al. Mammographic features and breast cancer risk: effects with time, age, and menopause status. J. Natl Cancer Inst. 87, 1622–1629 (1995).

    Article  CAS  PubMed  Google Scholar 

  23. Warner, E., Lockwood, G., Tritchler, D. & Boyd, N. F. The risk of breast cancer associated with mammographic parenchymal patterns: a meta-analysis of the published literature to examine the effect of method of classification. Cancer Detect. Prev. 16, 67–72 (1992).

    CAS  PubMed  Google Scholar 

  24. Ursin, G., Hovanessian-Larsen, L., Parisky, Y. R., Pike, M. C. & Wu, A. H. Greatly increased occurrence of breast cancers in areas of mammographically dense tissue. Breast Cancer Res. 7, 605–608 (2005).

    Article  Google Scholar 

  25. Boyd, N. et al. Mammographic density and breast cancer risk: evaluation of a novel method of measuring breast tissue volumes. Cancer Epidemiol. Biomarkers Prev. 18, 1754–1762 (2009).

    Article  PubMed  Google Scholar 

  26. Cuzick, J. Assessing risk for breast cancer. Breast Cancer Res. 10 (Suppl 4), 13 (2008).

    Article  Google Scholar 

  27. Boyd, N. et al. A longitudinal study of the effects of menopause on mammographic features. Cancer Epidemiol. Biomarkers Prev. 11, 1048–1053 (2002).

    PubMed  Google Scholar 

  28. Vachon, C. M. et al. Mammographic density, breast cancer risk and risk prediction. Breast Cancer Res. 9, 217 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Mandelson, M. T. et al. Breast density as a predictor of mammographic detection: comparison of interval-detected and screen-detected cancers. J. Natl Cancer Inst. 92, 1081–1087 (2000).

    Article  CAS  PubMed  Google Scholar 

  30. van Gils, C. H., Otten, J. D., Verbeek, A. L. & Hendriks, J. H. Mammographic breast density and risk of breast cancer: masking bias or causality? Eur. J. Epidemiol. 14, 315–320 (1998).

    Article  CAS  PubMed  Google Scholar 

  31. Ma, L. et al. Case-control study of factors associated with failure to detect breast cancer by mammography. J. Natl Cancer Inst. 84, 781–785 (1992).

    Article  CAS  PubMed  Google Scholar 

  32. Boyd, N. F. et al. Quantitative classification of mammographic densities and breast cancer risk: results from the Canadian National Breast Screening Study. J. Natl Cancer Inst. 87, 670–675 (1995).

    Article  CAS  PubMed  Google Scholar 

  33. Boyd N. F. et al. Effects at two years of a low-fat high-carbohydrate diet on radiological features of the breast: results from randomized trial. J. Natl Cancer Inst. 89, 488–496 (1997).

    Article  CAS  PubMed  Google Scholar 

  34. Duffy, S. W. in Epidemiology of Female Breast Cancer (ed. Michell, M. J.). 1–12 (Cambridge University Press, Cambridge, 2010).

    Google Scholar 

  35. Cuzick, J., Warwick, J., Pinney, E., Warren, R. M. & Duffy, S. W. Tamoxifen and breast density in women at increased risk of breast cancer. J. Natl Cancer Inst. 96, 621–628 (2004).

    Article  CAS  PubMed  Google Scholar 

  36. Vachon, C. M., Kuni, C. C., Anderson, K., Anderson, V. E. & Sellers, T. A. Association of mammographically defined percent breast density with epidemiologic risk factors for breast cancer (United States). Cancer Causes Control 11, 653–662 (2000).

    Article  CAS  PubMed  Google Scholar 

  37. Wong, C. S. et al. Mammographic density and its interaction with other breast cancer risk factors in an Asian population. Br. J. Cancer 104, 871–874 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Stone, J., Ding, J., Warren, R. M., Duffy, S. W. & Hopper, J. L. Using mammographic density to predict breast cancer risk: dense area or percentage dense area. Breast Cancer Res. 12, R97 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Woolcott, C. G. et al. Associations of overall and abdominal adiposity with area and volumetric mammographic measures among postmenopausal women. Int. J. Cancer 129, 440–448 (2011).

    Article  CAS  PubMed  Google Scholar 

  40. Vachon, C. M. et al. Mammographic breast density as a general marker of breast cancer risk. Cancer Epidemiol. Biomarkers Prev. 16, 43–49 (2007).

    Article  PubMed  Google Scholar 

  41. Hutson, S. W., Cowen, P. N. & Bird, C. C. Morphometric studies of age related changes in normal human breast and their significance for evolution of mammary cancer. J. Clin. Pathol. 38, 281–287 (1985).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Johnson, K. H. & Millard, P. S. Oral contraceptives and breast cancer. J. Fam. Pract. 43, 340–341 (1996).

    CAS  PubMed  Google Scholar 

  43. Sala, E. et al. High-risk mammographic parenchymal patterns, hormone replacement therapy and other risk factors: a case-control study. Int. J. Epidemiol. 29, 629–636 (2000).

    Article  CAS  PubMed  Google Scholar 

  44. Vacek, P. M. & Geller, B. M. A prospective study of breast cancer risk using routine mammographic breast density measurements. Cancer Epidemiol. Biomarkers Prev. 13, 715–722 (2004).

    PubMed  Google Scholar 

  45. Boyd, N. F. et al. Mammographic density as a surrogate marker for the effects of hormone therapy on risk of breast cancer. Cancer Epidemiol. Biomarkers Prev. 15, 961–966 (2006).

    Article  CAS  PubMed  Google Scholar 

  46. Greendale, G. A. et al. Postmenopausal hormone therapy and change in mammographic density. J. Natl Cancer Inst. 95, 30–37 (2003).

    Article  CAS  PubMed  Google Scholar 

  47. Vachon, C. M., Sellers, T. A., Vierkant, R. A., Wu, F. F. & Brandt, K. R. Case-control study of increased mammographic breast density response to hormone replacement therapy. Cancer Epidemiol. Biomarkers Prev. 11, 1382–1388 (2002).

    CAS  PubMed  Google Scholar 

  48. Rutter, C. M., Mandelson, M. T., Laya, M. B., Seger, D. J. & Taplin, S. Changes in breast density associated with initiation, discontinuation, and continuing use of hormone replacement therapy. JAMA 285, 171–176 (2001).

    Article  CAS  PubMed  Google Scholar 

  49. Boyd, N. F. et al. The association of breast mitogens with mammographic densities. Br. J. Cancer 87, 876–882 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Narod, S. Hormone replacement therapy and the risk of breast cancer. Nat. Rev. Clin. Oncol. 8, 669–676 (2011).

    Article  CAS  PubMed  Google Scholar 

  51. Eng-Wong J. et al. Effect of raloxifene on mammographic density and breast magnetic resonance imaging in premenopausal women at increased risk for breast cancer. Cancer Epidemiol. Biomarkers Prev. 17, 1696–1701 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Eilertsen, A. L., Karssemeijer, N., Skaane, P., Qvigstad, E, Sandset P. M. Differential impact of conventional and low-dose oral hormone therapy, tibolone and raloxifene on mammographic breast density, assessed by an automated quantitative method. BJOG 115, 773–779 (2008).

    Article  CAS  PubMed  Google Scholar 

  53. Freedman, M. et al. Digitized mammography: a clinical trial of postmenopausal women randomly assigned to receive raloxifene, estrogen, or placebo. J. Natl Cancer Inst. 93, 51–56 (2001).

    Article  CAS  PubMed  Google Scholar 

  54. Vachon, C. M. et al. Pilot study of the impact of letrozole vs. placebo on breast density in women completing 5 years of tamoxifen. The Breast 16, 204–210 (2007).

    Article  CAS  PubMed  Google Scholar 

  55. Cigler, T. et al. A randomized, placebo controlled trial (NCIC CTG MAP1) examining the effects of letrozole on mammographic breast density and other end organs on postmenopausal women. Breast Cancer Res. Treat. 120, 427–435 (2010).

    Article  CAS  PubMed  Google Scholar 

  56. Cigler, T. et al. A randomized, placebo controlled trial (NCIC CTG MAP2) examining the effects of exemestane on mammographic breast density, bone density, markers of bone metabolism and serum lipid levels in postmenopausal women. Breast Cancer Res. Treat. 120, 427–435 (2010).

    Article  CAS  PubMed  Google Scholar 

  57. McCormack, V. A. et al. Sex steroids, growth factors and mammographic density: a cross-sectional study of UK postmenopausal Caucasian and Afro-Caribbean women. Breast Cancer Res. 11, R38 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  58. Tamimi, R. M., Hankinson, S. E., Colditz, G. A. & Byrne, C. Endogenous sex hormone levels and mammographic density among postmenopausal women. Cancer Epidemiol. Biomarkers Prev. 14, 2641–2647 (2005).

    Article  CAS  PubMed  Google Scholar 

  59. Tamimi, R. M., Byrne, C., Colditz, G. A. & Hankinson, S. E. Endogenous hormone levels, mammographic density, and subsequent risk of breast cancer in postmenopausal women. J. Natl Cancer Inst. 99, 1178–1187 (2007).

    Article  CAS  PubMed  Google Scholar 

  60. Ziv, E. et al. Mammographic density and estrogen receptor status of breast cancer. Cancer Epidemiol. Biomarkers Prev. 13, 2090–2095 (2004).

    CAS  PubMed  Google Scholar 

  61. Ma, H. et al. Is there a difference in the association between percent mammographic density and subtypes of breast cancer? Luminal A and triple-negative breast cancer. Cancer Epidemiol. Biomarkers Prev. 18, 479–485 (2009).

    Article  CAS  PubMed  Google Scholar 

  62. Yaghjyan L. et al. Mammographic breast density and subsequent risk of breast cancer in postmenopausal women according to tumor characteristics. J. Natl Cancer Inst. 103, 1–11 (2011).

    Article  Google Scholar 

  63. Ding, J., Warren, R., Girling, A. Thompson, D. & Easton, D. Mammographic density, estrogen receptor status and other breast cancer tumor characteristics. Breast J. 16, 279–289 (2010).

    Article  PubMed  Google Scholar 

  64. Conroy, S. M., Pagano, I., Kolonel, L. N. & Maskarinec, G. Mammographic density and hormone receptor expression in breast cancer: the multietnic cohort study. Cancer Epidemiol. 35, 448–452 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Pasqualini, J. R. et al. Concentrations of estrone, estradiol, and estrone sulfate and evaluation of sulfatase and aromatase activities in pre- and postmenopausal breast cancer patients. J. Clin. Endocrinol. Metab. 81, 1460–1464 (1996).

    CAS  PubMed  Google Scholar 

  66. Boyd, N. F. et al. Heritability of mammographic density, a risk factor for breast cancer. N. Engl. J. Med. 347, 886–894 (2002).

    Article  PubMed  Google Scholar 

  67. Pankow, J. S. et al. Genetic analysis of mammographic breast density in adult women: evidence of a gene effect. J. Natl. Cancer Inst. 89, 549–556 (1997).

    Article  CAS  PubMed  Google Scholar 

  68. Ursin, G. et al. The relative importance of genetics and environment on mammographic density. Cancer Epidemiol. Biomarkers Prev. 18, 102–112 (2009).

    Article  PubMed  Google Scholar 

  69. Kelemen, L. E., Sellers, T. A. & Vachon, C. M. Can genes for mammographic density inform cancer aetiology? Nat. Rev. Cancer 8, 812–823 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Easton, D. F. et al. Genome-wide association study identifies novel breast cancer susceptibility loci. Nature 447, 1087–1093 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Odefrey, F. et al. Common genetic variants associated with breast cancer and mammographic density measures that predict disease. Cancer Res. 70, 1449–1458 (2010).

    Article  CAS  PubMed  Google Scholar 

  72. Lindstrom, S. et al. Common variants in ZNF365 are associated with both mammographic density and breast cancer risk. Nat. Genet. 43, 185–187 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  73. Byrne, C. et al. Effects of mammographic density and benign breast disease on breast cancer risk (United States). Cancer Causes Control 12, 103–110 (2001).

    Article  CAS  PubMed  Google Scholar 

  74. Hartmann, L. C. et al. Benign breast disease and the risk of breast cancer, N. Engl. J. Med. 353, 229–237 (2005).

    Article  CAS  PubMed  Google Scholar 

  75. Carter, C. L., Corle, D. K., Micozzi, M. S., Schatzkin, A. & Taylor, P. R. A prospective study of the development of breast cancer in 16,692 women with benign breast disease. Am. J. Epidemiol. 128, 467–477 (1988).

    Article  CAS  PubMed  Google Scholar 

  76. Degnim, A. C. et al. Stratification of breast cancer risk in women with atypia: a Mayo cohort study. J. Clin. Oncol. 25, 2671–2677 (2007).

    Article  PubMed  Google Scholar 

  77. Boyd, N. F. et al. Mammographic densities and the prevalence and incidence of histological types of benign breast disease. Eur. J. Cancer Prev. 9, 15–24 (2000).

    Article  CAS  PubMed  Google Scholar 

  78. Boyd, N. F., Lockwood, G. A., Byng, J. W., Tritchler, D. L. & Yaffe, M. J. Mammographic densities and breast cancer risk. Cancer Epidemiol. Biomarkers Prev. 7, 1133–1144 (1998).

    CAS  PubMed  Google Scholar 

  79. Cuzick, J., Berridge, D. & Whitehead, J. Mammographic dysplasia as entry criterion for breast cancer prevention trials. Lancet 337, 1225 (1991).

    Article  CAS  PubMed  Google Scholar 

  80. Tyrer, J., Duffy, S. W. & Cuzick, J. A breast cancer prediction model incorporating familial and personal risk factors. Stat. Med. 23, 1111–1130 (2004).

    Article  PubMed  Google Scholar 

  81. Chen, J. et al. Projecting absolute invasive breast cancer risk in white women with a model that includes mammographic density. J. Natl Cancer Inst. 98, 1215–1226 (2006).

    Article  PubMed  Google Scholar 

  82. Sala, E. et al. Mammographic parenchymal patterns and mode of detection: implications for the breast screening programme. J. Med. Screen 5, 207–212 (1998).

    Article  CAS  PubMed  Google Scholar 

  83. Chiu, S. Y. et al. Effect of baseline breast density on breast cancer incidence, stage, mortality, and screening parameters: 25-year follow-up of a Swedish mammographic screening. Cancer Epidemiol. Biomarkers Prev. 19, 1219–1228 (2010).

    Article  PubMed  Google Scholar 

  84. Corsetti, V. et al. Evidence of the effect of adjunct ultrasound screening in women with mammography-negative dense breasts: interval breast cancers at 1 year follow-up. Eur. J. Cancer 47, 1021–1026 (2011).

    Article  PubMed  Google Scholar 

  85. Kelly, K. M., Dean, J. Comulada, W S. & Lee, S. J. Breast cancer detection using automated whole breast ultrasound and mammography in radiologically dense breasts. Eur. Radiol. 20, 734–742 (2010).

    Article  PubMed  Google Scholar 

  86. Warner, E. et al. Prospective study of breast cancer incidence in women with a BRCA1 or BRCA2 mutation under surveillance with and without magnetic resonance imaging. J. Clin. Oncol. 29, 1664–1669 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  87. Rijnsburger, A. J. et al. BRCA1-associated breast cancers present differently from BRCA2-associated and familial cases: long-term follow-up of the Dutch MRISC Screening Study. J. Clin. Oncol. 28, 5265–5273 (2010).

    Article  CAS  PubMed  Google Scholar 

  88. Leach, M. O. et al. Screening with magnetic resonance imaging and mammography of a UK population at high familial risk of breast cancer: a prospective multicentre cohort study (MARIBS). Lancet 365, 1769–1778 (2005).

    Article  CAS  PubMed  Google Scholar 

  89. Bigenwald, R. Z. et al. Is mammography adequate for screening women with inherited BRCA mutations and low breast density? Cancer Epidemiol. Biomarkers Prev. 17, 706–711 (2008).

    Article  CAS  PubMed  Google Scholar 

  90. Helvie, M. A., Roubidoux, M. A., Weber, B. L. & Merajver, S. D. Mammography of breast carcinoma in women who have mutations of the breast cancer gene BRCA1: initial experience. Am. J. Roentgenol. 168, 1599–1602 (1997).

    Article  CAS  Google Scholar 

  91. Chang, J., Yang, W. T. & Choo, H. F. Mammography in Asian patients with BRCA1 mutations. Lancet 353, 2070–2071 (1999).

    Article  CAS  PubMed  Google Scholar 

  92. Huo, Z. et al. Computerized analysis of digitized mammograms of BRCA1 and BRCA2 gene mutation carriers. Radiology, 225, 519–526 (2002).

    Article  PubMed  Google Scholar 

  93. Tilanus-Linthorst, M. et al. A BRCA 1/2 mutation, high breast density and prominent pushing margins of a tumor independently contribute to a frequent false-negative mammography. Int. J. Cancer 102, 91–95 (2002).

    Article  CAS  PubMed  Google Scholar 

  94. Mitchell, G. et al. Mammographic density and breast cancer risk in BRCA1 and BRCA2 mutation carriers. Cancer Res. 66, 1866–1872 (2006).

    Article  CAS  PubMed  Google Scholar 

  95. Wenkel, E. et al. Automated breast ultrasound: lesion detection and BI-RADS classification—a pilot study. Rofo 180, 804–808 (2008).

    Article  CAS  PubMed  Google Scholar 

  96. Pisano, E. D. et al. Diagnostic performance of digital versus film mammography for breast-cancer screening. N. Engl. J. Med. 353, 1773–1783 (2005).

    Article  CAS  PubMed  Google Scholar 

  97. Gail, M. H. et al. Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. J. Natl Cancer Inst. 81, 1879–1886 (1989).

    Article  CAS  PubMed  Google Scholar 

  98. Costantino, J. P. et al. Validation studies for models projecting the risk of invasive and total breast cancer incidence. J. Natl Cancer Inst. 91, 1541–1548 (1999).

    Article  CAS  PubMed  Google Scholar 

  99. Claus, E. B., Risch, N. & Thompson, W. D. Autosommal dominant inheritance of early onset breast cancer. Cancer 73, 643–651 (1994).

    Article  CAS  PubMed  Google Scholar 

  100. Claus, E. B., Risch, N., & Thompson, W. D. The calculation of breast cancer risk for women with a first degree family history of ovarian cancer. Breast Cancer Res. Treat. 28, 115–120 (1993).

    Article  CAS  PubMed  Google Scholar 

  101. van Asperen C. J. et al. Risk estimation for healthy women from breast cancer families: new insights and new strategies. Cancer Epidemiol. Biomarkers Prev. 13, 87–93 (2004).

    Article  PubMed  Google Scholar 

  102. Ford, D., Easton, D. F., Bishop, D. T., Narod, S. A. & Goldgar, D. E. Risk of cancer in BRCA-1 mutation carriers. Breast Cancer Linkage Consortium. Lancet 343, 692–695 (1994).

    Article  CAS  PubMed  Google Scholar 

  103. Amir, E. et al. Evaluation of breast cancer risk assessment packages in the family history evaluation and screening programme. J. Med. Genet. 40, 807–814 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Schonfeld, S. et al. Effect of changing breast cancer incidence rates on the calibration of the gail model. J. Clin. Oncol. 28, 2411–2417 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  105. Boughey, J. C. et al. Evaluation of the Tyrer-Cuzick (International Breast Cancer Intervention Study) model for breast cancer risk prediction in women with atypical hyperplasia. J. Clin. Oncol. 28, 3591–3596 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  106. Pankratz V. S. et al. Assessment of the accuracy of the Gail model in women with atypical hyperplasia. J Clin. Oncol. 26, 5374–5379 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  107. Tice, J. A., Cummings, S. R., Ziv, E. & Kerlikowske, K. Mammographic breast density and the Gail model for breast cancer risk prediction in a screening population. Breast Cancer Res. Treat. 94, 115–122 (2005).

    Article  PubMed  Google Scholar 

  108. Barlow, W. E. et al. Prospective breast cancer risk prediction model for women undergoing screening mammography. J. Natl Cancer Inst. 98, 1204–1214 (2006).

    Article  PubMed  Google Scholar 

  109. Tice, J. A. et al. Using clinical factors and mammographic density to estimate breast cancer risk: development and validation of a new predictive model. Ann. Intern Med. 148, 337–347 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  110. Visvanathan, K. et al. American Society of Clinical Oncology clinical practice guideline update on the use of pharmacologic interventions including tamoxifen, raloxifene, and aromatase inhibition for breast cancer risk reduction. J. Clin. Oncol. 27, 3235–3258 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Familial breast cancer: the classification and care of women at risk of familial breast cancer in primary, secondary and tertiary care (partial update of CG14). National Institute for Health and Clinical Excellence (NICE) [online], (2006).

  112. PROCAS study. University Hospital of South Manchester [online].

  113. NHS Breast Screening Programme Annual Review 2010, NHS Breast Screening Programme [online] (2011).

  114. Large national study of breast cancer (available only in Swedish: Stora nationella bröstcancerstudien). Karma [online], (2011).

Download references

Acknowledgements

V. Assi is supported by a PhD studentship from Cancer Research UK.

Author information

Authors and Affiliations

Authors

Contributions

J. Warwick and S. Duffy researched the data for the article, provided a substantial contribution to discussions of the content, wrote the article and edited the manuscript before submission. V. Assi contributed to researching the data for the article, discussions of the content and writing the article and J. Cuzick contributed to discussions of the content and editing the manuscript before submission.

Corresponding author

Correspondence to Stephen W. Duffy.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Assi, V., Warwick, J., Cuzick, J. et al. Clinical and epidemiological issues in mammographic density. Nat Rev Clin Oncol 9, 33–40 (2012). https://doi.org/10.1038/nrclinonc.2011.173

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrclinonc.2011.173

This article is cited by

Search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer