Mammographic density is an established breast cancer risk factor within many ethnically different populations. The distribution of mammographic density has been shown to be significantly lower in Western Australian Aboriginal women compared to age- and screening location-matched non-Aboriginal women. Whether mammographic density is a predictor of breast cancer risk in Aboriginal women is unknown.
We measured mammographic density from 103 Aboriginal breast cancer cases and 327 Aboriginal controls, 341 non-Aboriginal cases, and 333 non-Aboriginal controls selected from the BreastScreen Western Australia database using the Cumulus software program. Logistic regression was used to examine the associations of percentage dense area and absolute dense area with breast cancer risk for Aboriginal and non-Aboriginal women separately, adjusting for covariates.
Both percentage density and absolute dense area were strongly predictive of risk in Aboriginal women with odds per adjusted standard deviation (OPERAS) of 1.36 (95% CI 1.09, 1.69) and 1.36 (95% CI 1.08, 1.71), respectively. For non-Aboriginal women, the OPERAS were 1.22 (95% CI 1.03, 1.46) and 1.26 (95% CI 1.05, 1.50), respectively.
Whilst mean mammographic density for Aboriginal women is lower than non-Aboriginal women, density measures are still higher in Aboriginal women with breast cancer compared to Aboriginal women without breast cancer. Thus, mammographic density strongly predicts breast cancer risk in Aboriginal women. Future efforts to predict breast cancer risk using mammographic density or standardize risk-associated mammographic density measures should take into account Aboriginal status when applicable.
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The datasets generated and analysed during the current study are not publically available but can be made available upon request (and pending approval) from Western Australia’s Department of Health Data Linkage Branch and BreastScreen Western Australia.
Accessibility/remoteness index of Australia
Body mass index
Full-field digital mammogram
Odds per adjusted standard deviation
Percent dense area
Socio-economic indexes for areas
Total area (of the breast)
Hopper JL (2015) Odds per adjusted standard deviation: comparing strengths of associations for risk factors measured on different scales and across diseases and populations. Am J Epidemiol 182(10):863–867. https://doi.org/10.1093/aje/kwv193
McCormack VA, dos Santos Silva I (2006) Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis. Cancer Epidemiol Biomark Prev 15(6):1159–1169. https://doi.org/10.1158/1055-9965.EPI-06-0034
Evans DG, Astley S, Stavrinos P, Harkness E, Donnelly LS, Dawe S, Jacob I, Harvie M, Cuzick J, Brentnall A, Wilson M, Harrison F, Payne K, Howell A (2016) In: Improvement in risk prediction, early detection and prevention of breast cancer in the NHS Breast Screening Programme and family history clinics: a dual cohort study. Programme Grants for Applied Research. Southampton (UK). https://doi.org/10.3310/pgfar04110
Evans DG, Donnelly LS, Harkness EF, Astley SM, Stavrinos P, Dawe S, Watterson D, Fox L, Sergeant JC, Ingham S, Harvie MN, Wilson M, Beetles U, Buchan I, Brentnall AR, French DP, Cuzick J, Howell A (2016) Breast cancer risk feedback to women in the UK NHS breast screening population. Br J Cancer 114(9):1045–1052. https://doi.org/10.1038/bjc.2016.56
Stone J (2018) Should breast cancer screening programs routinely measure mammographic density? J Med Imaging Radiat Oncol 62(2):151–158. https://doi.org/10.1111/1754-9485.12652
Burton A, Maskarinec G, Perez-Gomez B, Vachon C, Miao H, Lajous M, Lopez-Ridaura R, Rice M, Pereira A, Garmendia ML, Tamimi RM, Bertrand K, Kwong A, Ursin G, Lee E, Qureshi SA, Ma H, Vinnicombe S, Moss S, Allen S, Ndumia R, Vinayak S, Teo SH, Mariapun S, Fadzli F, Peplonska B, Bukowska A, Nagata C, Stone J, Hopper J, Giles G, Ozmen V, Aribal ME, Schuz J, Van Gils CH, Wanders JOP, Sirous R, Sirous M, Hipwell J, Kim J, Lee JW, Dickens C, Hartman M, Chia KS, Scott C, Chiarelli AM, Linton L, Pollan M, Flugelman AA, Salem D, Kamal R, Boyd N, Dos-Santos-Silva I, McCormack V (2017) Mammographic density and ageing: a collaborative pooled analysis of cross-sectional data from 22 countries worldwide. PLoS Med 14(6):e1002335. https://doi.org/10.1371/journal.pmed.1002335
McLean K, Darcey E, Cadby G, Lund H, Pilkington L, Redfern A, Thompson S, Saunders C, Wylie E, Stone J (2019) The distribution and determinants of mammographic density measures in Western Australian aboriginal women. Breast Cancer Res 21(1):33. https://doi.org/10.1186/s13058-019-1113-4
Roder D, Webster F, Zorbas H, Sinclair S (2012) Breast screening and breast cancer survival in aboriginal and torres strait Islander women of Australia. Asian Pacific J Cancer Prev 13(1):147–155
Christensen D, Davis G, Draper G, Mitrou F, McKeown S, Lawrence D, McAullay D, Pearson G, Rikkers W, Zubrick SR (2016) Evidence for the use of an algorithm in resolving inconsistent and missing indigenous status in administrative data collections. Aust J Soc Issues 49(4):423–443
Statistics ABo (2018). http://www.abs.gov.au/websitedbs/censushome.nsf/home/seifa
Statistics ABo (2018). http://www.abs.gov.au/websitedbs/d3310114.nsf/home/remoteness+structure
Byng JW, Boyd NF, Fishell E, Jong RA, Yaffe MJ (1994) The quantitative analysis of mammographic densities. Phys Med Biol 39(10):1629–1638
Stone J, Ding J, Warren RM, Duffy SW, Hopper JL (2010) Using mammographic density to predict breast cancer risk: dense area or percentage dense area. Breast Cancer Res 12(6):R97. https://doi.org/10.1186/bcr2778
Burton A, Byrnes G, Stone J, Tamimi RM, Heine J, Vachon C, Ozmen V, Pereira A, Garmendia ML, Scott C, Hipwell JH, Dickens C, Schuz J, Aribal ME, Bertrand K, Kwong A, Giles GG, Hopper J, Perez Gomez B, Pollan M, Teo SH, Mariapun S, Taib NA, Lajous M, Lopez-Riduara R, Rice M, Romieu I, Flugelman AA, Ursin G, Qureshi S, Ma H, Lee E, Sirous R, Sirous M, Lee JW, Kim J, Salem D, Kamal R, Hartman M, Miao H, Chia KS, Nagata C, Vinayak S, Ndumia R, van Gils CH, Wanders JO, Peplonska B, Bukowska A, Allen S, Vinnicombe S, Moss S, Chiarelli AM, Linton L, Maskarinec G, Yaffe MJ, Boyd NF, Dos-Santos-Silva I, McCormack VA (2016) Mammographic density assessed on paired raw and processed digital images and on paired screen-film and digital images across three mammography systems. Breast Cancer Res 18(1):130. https://doi.org/10.1186/s13058-016-0787-0
Meijer M, Bloomfield K, Engholm G (2013) Neighbourhoods matter too: the association between neighbourhood socioeconomic position, population density and breast, prostate and lung cancer incidence in Denmark between 2004 and 2008. J Epidemiol Community Health 67(1):6–13. https://doi.org/10.1136/jech-2011-200192
Robert SA, Strombom I, Trentham-Dietz A, Hampton JM, McElroy JA, Newcomb PA, Remington PL (2004) Socioeconomic risk factors for breast cancer: distinguishing individual- and community-level effects. Epidemiology 15(4):442–450
Webster TF, Hoffman K, Weinberg J, Vieira V, Aschengrau A (2008) Community- and individual-level socioeconomic status and breast cancer risk: multilevel modeling on Cape Cod, Massachusetts. Environ Health Perspect 116(8):1125–1129. https://doi.org/10.1289/ehp.10818
The authors would like to acknowledge BreastScreen Western Australia, The Aboriginal Women’s Reference Group and the Government of Western Australia Department of Health Data Linkage Branch.
This work was supported by Cancer Council Western Australia and Cancer Australia (APP1085750). Author JS is a National Breast Cancer Foundation Research Fellow.
Conflict of interest
The authors declare that they have no conflict of interest.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee (Western Australian Department of Health Human Research Ethics Committee (Project #2014/50) and the Western Australian Aboriginal Health Ethics Committee (Project 581)) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
A waiver of informed consent was received to obtain access to de-identified linked data.
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Darcey, E., Lloyd, R., Cadby, G. et al. The association between mammographic density and breast cancer risk in Western Australian Aboriginal women. Breast Cancer Res Treat 176, 235–242 (2019). https://doi.org/10.1007/s10549-019-05225-9
- Breast cancer risk
- Mammographic breast density
- Aboriginal women
- Mammographic screening