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A nested case-control study of mammographic patterns, breast volume, and breast cancer (New York City, NY, United States)

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The relations of Wolfe mammographic patterns, quantitative mammographic densities, and mammographically estimated breast size to breast cancer risk were investigated prospectively in a case-control study nested in the New York University Women's Health Study, a cohort of 14,291 women in New York City, NY (United States). The archived mammograms of 197 breast cancer cases who were identified during the first 5.5 years of the study and of 521 individually matched controls from the same cohort were retrieved and classified according to Wolfe parenchymal patterns and mammographic densities by two expert radiologists. Breast size and volume were estimated on the mammogram's cranio-caudal projection. In both premenopausal and postmenopausal subjects, the risk of breast cancer increased progressively with increasing density and percent density area. A significantly increased risk was found also for Wolfe pattern DY in premenopausal women and P2 pattern in postmenopausal subjects. In premenopausal women, mammographically determined breast volume and breast height also were associated positively with breast cancer risk. Although the results of the present study confirmed that mammographic parenchymal patterns and densities were important predictors of breast cancer risk, their practical use in screening seems limited due to the high prevalence of high risk patterns.

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References

  1. Shapiro, S, Venet, W, Strax, P, Venet, L, Roeser, R. Ten- to fourteen-year effect of screening on breast cancer mortality. JNCI 1982; 69: 349–55.

    Google Scholar 

  2. Tabár, L, Fagerberg, CJG, Gad, A, et al. Reduction in mortality from breast cancer after mass screening with mammography: randomized trial from the Breast Cancer Screening Working Group of the Swedish National Board of Health and Welfare. Lancet 1985; 1: 829–32.

    Google Scholar 

  3. Baker, LH. Breast cancer detection demonstration project: five-year summary report. CA 1982; 32: 194–225.

    Google Scholar 

  4. Wolfe, JM. Risk for breast cancer development determined by mammographic parenchymal pattern. Cancer 1976; 37: 2486–92.

    Google Scholar 

  5. Wolfe, JN. Breast patterns as an index of risk for developing breast cancer. AJR 1976; 126: 1130–9.

    Google Scholar 

  6. Saftlas, AF, Szklo, M. Mammographic parenchymal patterns and breast cancer risk. Epi Rev 1987; 9: 146–74.

    Google Scholar 

  7. Oza, AM, Boyd, NF. Mammographic parenchymal patterns: a marker of breast cancer risk. Epi Rev 1993; 15: 196–208.

    Google Scholar 

  8. Albanes, D, Winick, M. Are cell number and cell proliferation risk factors for cancer? JNCI 1988; 80: 772–4.

    Google Scholar 

  9. Wynder, EL, Bross, IJ, Hirayama, T. A study of the epidemiology of cancer of the breast. Cancer 1960; 13: 559–601.

    Google Scholar 

  10. Valaoras, VG, MacMahon, B, Trichopoulos, D, Polychronopoulou, A. Lactation and reproductive histories of breast cancer patients in greater Athens, 1965–67. Int J Cancer 1969; 4: 350–63.

    Google Scholar 

  11. Soini, I. Risk factors of breast cancer in Finland. Int J Epidemiol 1977; 6: 365–73.

    Google Scholar 

  12. Hirohata, T, Nomura, AMY, Kolonel, LN. Breast size and cancer. Br Med J 1977; 2: 641.

    Google Scholar 

  13. Dupont, WD, Page, DL. Breast cancer risk associated with proliferative disease, age at first birth, and a family history of breast cancer. Am J Epidemiol 1987; 125: 769–79.

    Google Scholar 

  14. Katariya, RN, Forrest, APM, Gravelle, IH. Breast volumes in cancer of the breast. Br J Cancer 1974; 29: 270–3.

    Google Scholar 

  15. Hsieh, C-c, Trichopoulos, D. Breast size, handedness and breast cancer risk. Eur J Cancer 1991; 27: 131–5.

    Google Scholar 

  16. Senie, RT, Saftlas, AF, Brinton, LA, Hoover, RN. Is breast size a predictor of breast cancer risk or the laterality of the tumor? Cancer Causes Control 1993; 4: 203–8.

    Google Scholar 

  17. Toniolo, PG, Pasternack, BS, Shore, RE, Sonnenschein, E, Koenig, KL, Rosenberg, C, et al. Endogenous hormones and breast cancer: a prospective study. Breast Cancer Res Treat 1991; 18: S23–6.

    Google Scholar 

  18. Toniolo, P, Riboli, E, Shore, RE, Pasternack, BS. Consumption of meat, animal products, protein, and fat and risk of breast cancer: a prospective cohort study in New York. Epidemiology 1994; 5: 391–7.

    Google Scholar 

  19. Toniolo, PG, Levitz, M, Zeleniuch-Jacquotte, A, et al. A prospective study of endogenous estrogens and breast cancer in postmenopausal women. JNCI 1995; 87: 190–7.

    Google Scholar 

  20. SAS/Stat User's Guide. Volume 2 (The GLIM Procedure), Version 6 Fourth Edition. Cary, NC (USA): SAS Institute INC, 1990.

  21. Breslow, NE, Day, NE. Conditional logistic regression for matched sets. In: Statistical Methods in Cancer Research. Vol. 1. The Analysis of Case-Control Studies. Lyon, France: International Agency for Research on Cancer, 1980: 248–79.

    Google Scholar 

  22. Wolfe, JN, Saftlas, AF, Salane, M. Mammographic parenchymal patterns and quantitative evaluation of mammographic densities: a case-control study. AJR 1987; 148: 1087–92.

    Google Scholar 

  23. Saftlas, AF, Hoover, RN, Brinton, LA, et al. Mammographic densities and risk of breast cancer. Cancer 1991; 67: 2833–8.

    Google Scholar 

  24. Boyd, NF, O'Sullivan, B, Campbell, JE, et al. Mammographic signs as risk factors for breast cancer. Br J Cancer 1982; 45: 185–93.

    Google Scholar 

  25. Brisson, J, Merletti, F, Sadowsky, NL, Twaddle, JA, Morrison, AS, Cole, P. Mammographic features of the breast and breast cancer risk. Am J Epidemiol 1982; 115: 428–37.

    Google Scholar 

  26. Brisson, J, Morrison, AS, Kopans, DB, et al. Height and weight, mammographic features of breast tissue, and breast cancer risk. Am J Epidemiol 1984; 119: 371–81.

    Google Scholar 

  27. Brisson, J, Verreault, R, Morrison, AS, Tennina, S, Meyer, F. Diet, mammographic features of breast tissue, and breast cancer risk. Am J Epidemiol 1989; 130: 14–24.

    Google Scholar 

  28. Boyd, NF, Byng, JW, Jong, RA, et al. Quantitative classification of mammographic densities and breast cancer risk: results from the Canadian National Breast Screening Study. JNCI 1995; 87: 670–5.

    Google Scholar 

  29. Ma, L, Fishell, E, Wright, B, Hanna, W, Allan, S, Boyd, NF. Case-control study of factors associated with failure to detect breast cancer by mammography. JNCI 1992; 84: 781–5.

    Google Scholar 

  30. Goodwin, PJ, Boyd, NF. Mammographic parenchymal pattern and breast cancer risk: a critical appraisal of the evidence. Am J Epidemiol 1988: 127: 1097–108.

    Google Scholar 

  31. Toniolo, P, Bleich, AR, Beinart, C, Koenig, KL. Reproducibility of Wolfe's classification of mammographic parenchymal patterns. Prev Med 1992; 21: 1–7.

    Google Scholar 

  32. Grove, JS, Goodman, MJ, Gilbert, FI, Russell, H. Wolfe's mammographic classification and breast cancer risk: the effect of misclassification on apparent risk ratios. Br J Radiol 1985; 58: 15–9.

    Google Scholar 

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Authors and Affiliations

  1. Nelson Institute of Environmental Medicine, New York University, School of Medicine, USA

    Ikuko Kato, Shaun Su, Mimi Kim & Paolo G. Toniolo

  2. Guttman Breast Diagnostic Institute, New York, NY, USA

    Clifford Beinart & Alan Bleich

Authors
  1. Ikuko Kato
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  2. Clifford Beinart
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  3. Alan Bleich
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  4. Shaun Su
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  5. Mimi Kim
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  6. Paolo G. Toniolo
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Additional information

This work was supported by Grants CA51921, CA34588, CA13343, and CA16087 from the US National Cancer Institute and by Grant ES00260 from the National Institute of Environmental Health Sciences.

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Kato, I., Beinart, C., Bleich, A. et al. A nested case-control study of mammographic patterns, breast volume, and breast cancer (New York City, NY, United States). Cancer Causes Control 6, 431–438 (1995). https://doi.org/10.1007/BF00052183

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  • DOI: https://doi.org/10.1007/BF00052183

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