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

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

Journal: Journal of the National Cancer Institute 2014;106(5):dju078

PMID: 24816206

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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.

Address: Affiliations of authors: Department of Epidemiology (AP, REG, RMT), and Department of Biostatistics (BAR), Harvard School of Public Health, Boston, MA; Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway (GU); Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA (GU); Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK (IdSS); Section of Environment and Radiation, International Agency for Research on Cancer, Lyon, France (VM); Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia (LB, GGG, KK); Centre for Molecular, Environmental, Genetic and Analytical Epidemiology, University of Melbourne, Melbourne, Australia (LB, GGG, JLH, KK, JS); Division of Epidemiology (CV) and Division of Biomedical Statistics and Informatics (CS), Department of Health Sciences Research, Mayo Clinic, Rochester, MN; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands (MFB, CHvG); Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia (GGG); Saw Swee Hock School of Public Health (KSC, MH, CSW), and Department of Surgery, Yong Loo Lin School of Medicine (MH), National University of Singapore, National University Health System, Singapore, Singapore; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (KC, LE, PH, MH); Department of Radiology, Addenbrooke's Hospital, Cambridge, UK (RMLW); School of Population and Public Health, University of British Columbia, Vancouver, BC , Canada (GH); Prevention and Cancer Control, Cancer Care, Toronto, ON, Canada (AMC); Human Genetics, Genome Institute of Singapore, Singapore, Singapore (JL); Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, Toronto, ON, Canada (QL, NFB); University of Hawaii Cancer Center, Honolu

DOI: 10.1093/jnci/dju078