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Mammographic Density Phenotypes and Risk of Breast Cancer: A Meta-analysis

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OXFORD UNIV PRESS INC
DOI: 10.1093/jnci/dju078

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  1. National Cancer Institute at the National Institutes of Health [R01 CA124865, R01 CA131332, P01 CA87969, R01 CA50385, R01 CA085265, R03 CA135699, R37 CA054281, R01 CA140286, R01 CA128931, R01 CA97396, P50 CA116201]
  2. Department of Defense grant DAMD [17-00-1-0331]
  3. National Institutes of Health [R25 CA098566]
  4. Marit and Hans Rausing's Initiative Against Breast Cancer
  5. United States Department of Defense Breast Cancer Research Program
  6. Office of the Congressionally Directed Medical Research Programs
  7. Agency for Science, Technology and Research
  8. Swedish Cancer Society [5128-B07-01PAF]
  9. National Cancer Institute of Canada
  10. SingHealth Foundation [SHF/FG450S/2009]
  11. National Medical Research Council [NMRC/0711/2002]
  12. National University Cancer Institute, Singapore [NMRC/CG/NCIS/2010]
  13. MammoGrid Project
  14. Victorian Breast Cancer Consortium
  15. National Breast Cancer Foundation
  16. Cancer Council Victoria
  17. National Health and Medical Research Council [251533, 209057, 504711, 454671]
  18. Dutch Cancer Society [KWF 2008-4071, KWF h1-4348]
  19. 'Europe against Cancer' program of the European Commission (SANCO)
  20. Dutch Ministry of Health, Welfare and Sports (WVS)
  21. ZonMW
  22. Breast Cancer Campaign [2007MayPR23]
  23. [W81XWH-05-1-0314]
  24. Cancer Research UK [14565] Funding Source: researchfish
  25. National Breast Cancer Foundation [PF-11-20] Funding Source: researchfish

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Background Fibroglandular breast tissue appears dense on mammogram, whereas fat appears nondense. It is unclear whether absolute or percentage dense area more strongly predicts breast cancer risk and whether absolute nondense area is independently associated with risk. Methods We conducted a meta-analysis of 13 case-control studies providing results from logistic regressions for associations between one standard deviation (SD) increments in mammographic density phenotypes and breast cancer risk. We used random-effects models to calculate pooled odds ratios and 95% confidence intervals (CIs). All tests were two-sided with P less than .05 considered to be statistically significant. Results Among premenopausal women (n = 1776 case patients; n = 2834 control subjects), summary odds ratios were 1.37 (95% CI = 1.29 to 1.47) for absolute dense area, 0.78 (95% CI = 0.71 to 0.86) for absolute nondense area, and 1.52 (95% CI = 1.39 to 1.66) for percentage dense area when pooling estimates adjusted for age, body mass index, and parity. Corresponding odds ratios among postmenopausal women (n = 6643 case patients; n = 11 187 control subjects) were 1.38 (95% CI = 1.31 to 1.44), 0.79 (95% CI = 0.73 to 0.85), and 1.53 (95% CI = 1.44 to 1.64). After additional adjustment for absolute dense area, associations between absolute nondense area and breast cancer became attenuated or null in several studies and summary odds ratios became 0.82 (95% CI = 0.71 to 0.94; P-heterogeneity = .02) for premenopausal and 0.85 (95% CI = 0.75 to 0.96; P-heterogeneity < .01) for postmenopausal women. Conclusions The results suggest that percentage dense area is a stronger breast cancer risk factor than absolute dense area. Absolute nondense area was inversely associated with breast cancer risk, but it is unclear whether the association is independent of absolute dense area.

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