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Review
. 2014 May 10;106(5):dju078.
doi: 10.1093/jnci/dju078.

Mammographic density phenotypes and risk of breast cancer: a meta-analysis

Andreas Pettersson  1 , Rebecca E Graff  1 , Giske Ursin  1 , Isabel Dos Santos Silva  1 , Valerie McCormack  1 , Laura Baglietto  1 , Celine Vachon  1 , Marije F Bakker  1 , Graham G Giles  1 , Kee Seng Chia  1 , Kamila Czene  1 , Louise Eriksson  1 , Per Hall  1 , Mikael Hartman  1 , Ruth M L Warren  1 , Greg Hislop  1 , Anna M Chiarelli  1 , John L Hopper  1 , Kavitha Krishnan  1 , Jingmei Li  1 , Qing Li  1 , Ian Pagano  1 , Bernard A Rosner  1 , Chia Siong Wong  1 , Christopher Scott  1 , Jennifer Stone  1 , Gertraud Maskarinec  1 , Norman F Boyd  1 , Carla H van Gils  1 , Rulla M Tamimi  1
Affiliations
Review

Mammographic density phenotypes and risk of breast cancer: a meta-analysis

Andreas Pettersson et al. J Natl Cancer Inst. .

Abstract

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 = 11187 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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Figures

Figure 1.
Figure 1.
Odds ratios (ORs) and 95% confidence intervals (CIs) for mammographic density phenotypes and risk of breast cancer among women who were premenopausal at the time of mammography. Random effects models. All statistical tests were two-sided. Additional analytical details are in Supplementary Table 2 (available online). AGE = UK AGE Trial nested case–control study; CAHRES = Cancer and Hormones Replacement in Sweden study; CBDS = Canadian Breast Density Study; CC = craniocaudal; EPIC–NL = Dutch contribution to the European Prospective Investigation into Cancer and Nutrition study; HRT = hormone replacement therapy; MCCS = Melbourne Collaborative Cohort Study; MCMAM = Mayo Clinic Mammography Study; MEC = Hawaii component of the Multiethnic Cohort Study; ML = mediolateral oblique; MMHS = Mayo Mammography Health Study; NHS1 = Nurses’ Health Study 1; NHS2 = Nurses’ Health Study 2; SBSP = Singapore Breast Cancer Screening Project; UK NHS = Norwich & Cambridge UK NHS Breast Cancer Screening Program; USC = University of Southern California mammographic density study.
Figure 2.
Figure 2.
Odds ratios (ORs) and 95% confidence intervals (CIs) for mammographic density phenotypes and risk of breast cancer among women who were postmenopausal at the time of mammography. Random effects models. All statistical tests were two-sided. Additional analytical details are in Supplementary Table 4 (available online). AGE = UK AGE Trial nested case–control study; CAHRES = Cancer and Hormones Replacement in Sweden study; CBDS = Canadian Breast Density Study; CC = craniocaudal; EPIC–NL = Dutch contribution to the European Prospective Investigation into Cancer and Nutrition study; HRT = hormone replacement therapy; MCCS = Melbourne Collaborative Cohort Study; MCMAM = Mayo Clinic Mammography Study; MEC = Hawaii component of the Multiethnic Cohort Study; ML = mediolateral oblique; MMHS = Mayo Mammography Health Study; NHS1 = Nurses’ Health Study 1; NHS2 = Nurses’ Health Study 2; SBSP = Singapore Breast Cancer Screening Project; UK NHS = Norwich & Cambridge UK NHS Breast Cancer Screening Program; USC = University of Southern California mammographic density study.
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References

    1. McCormack VA, dos Santos Silva I. Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis. Cancer Epidemiol Biomarkers Prev. 2006;15(6):1159–1169. - PubMed
    1. Trichopoulos D, Lipman RD. Mammary gland mass and breast cancer risk. Epidemiology. 1992;3(6):523–526. - PubMed
    1. Kato I, Beinart C, Bleich A, Su S, Kim M, Toniolo PG. A nested case–control study of mammographic patterns, breast volume, and breast cancer. Cancer Causes Control. 1995;6(5):431–438. - PubMed
    1. Boyd N, Martin L, Gunasekara A, et al. Mammographic density and breast cancer risk: evaluation of a novel method of measuring breast tissue volumes. Cancer Epidemiol Biomarkers Prev. 2009;18(6):1754–1762. - PubMed
    1. Lokate M, Peeters PH, Peelen LM, Haars G, Veldhuis WB, van Gils CH. Mammographic density and breast cancer risk: the role of the fat surrounding the fibroglandular tissue. Breast Cancer Res. 2011;13(5):R103. - PMC - PubMed

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