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Lloyd R, Pirikahu S, Walter J, Cadby G, Warrington N, Perera D, Hickey M, Saunders C, Hackmann M, Sampson DD, Shepherd J, Lilge L, Stone J. The Prospective Association between Early Life Growth and Breast Density in Young Adult Women. Cancers (Basel) 2024; 16:2418. [PMID: 39001479 PMCID: PMC11240569 DOI: 10.3390/cancers16132418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Revised: 06/24/2024] [Accepted: 06/26/2024] [Indexed: 07/16/2024] Open
Abstract
Breast density is a strong intermediate endpoint to investigate the association between early-life exposures and breast cancer risk. This study investigates the association between early-life growth and breast density in young adult women measured using Optical Breast Spectroscopy (OBS) and Dual X-ray Absorptiometry (DXA). OBS measurements were obtained for 536 female Raine Cohort Study participants at ages 27-28, with 268 completing DXA measurements. Participants with three or more height and weight measurements from ages 8 to 22 were used to generate linear growth curves for height, weight and body mass index (BMI) using SITAR modelling. Three growth parameters (size, velocity and timing) were examined for association with breast density measures, adjusting for potential confounders. Women who reached their peak height rapidly (velocity) and later in adolescence (timing) had lower OBS-breast density. Overall, women who were taller (size) had higher OBS-breast density. For weight, women who grew quickly (velocity) and later in adolescence (timing) had higher absolute DXA-breast density. Overall, weight (size) was also inversely associated with absolute DXA-breast density, as was BMI. These findings provide new evidence that adolescent growth is associated with breast density measures in young adult women, suggesting potential mediation pathways for breast cancer risk in later life.
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Affiliation(s)
- Rachel Lloyd
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, Perth, WA 6009, Australia
| | - Sarah Pirikahu
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, Perth, WA 6009, Australia
| | - Jane Walter
- University Health Network, Toronto, ON M5G 2C4, Canada
| | - Gemma Cadby
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, Perth, WA 6009, Australia
| | - Nicole Warrington
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4067, Australia
- The Frazer Institute, The University of Queensland, Woolloongabba, QLD 4102, Australia
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, NO-7491 Trondheim, Norway
| | - Dilukshi Perera
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, Perth, WA 6009, Australia
| | - Martha Hickey
- Department of Obstetrics and Gynaecology, University of Melbourne and the Royal Women's Hospital, Melbourne, VIC 3052, Australia
| | - Christobel Saunders
- Department of Surgery, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Michael Hackmann
- School of Human Sciences, The University of Western Australia, Crawley, WA 6009, Australia
| | - David D Sampson
- School of Computer Science and Electronic Engineering, The University of Surrey, Guildford, Surrey GU2 7XH, UK
| | - John Shepherd
- Epidemiology and Population Sciences in the Pacific Program, University of Hawaii Cancer Center, Honolulu, HI 96813, USA
| | - Lothar Lilge
- University Health Network, Toronto, ON M5G 2C4, Canada
- Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada
| | - Jennifer Stone
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, Perth, WA 6009, Australia
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Perera D, Pirikahu S, Walter J, Cadby G, Darcey E, Lloyd R, Hickey M, Saunders C, Hackmann M, Sampson DD, Shepherd J, Lilge L, Stone J. The distribution of breast density in women aged 18 years and older. Breast Cancer Res Treat 2024; 205:521-531. [PMID: 38498102 PMCID: PMC11101556 DOI: 10.1007/s10549-024-07269-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 01/24/2024] [Indexed: 03/20/2024]
Abstract
PURPOSE Age and body mass index (BMI) are critical considerations when assessing individual breast cancer risk, particularly for women with dense breasts. However, age- and BMI-standardized estimates of breast density are not available for screen-aged women, and little is known about the distribution of breast density in women aged < 40. This cross-sectional study uses three different modalities: optical breast spectroscopy (OBS), dual-energy X-ray absorptiometry (DXA), and mammography, to describe the distributions of breast density across categories of age and BMI. METHODS Breast density measures were estimated for 1,961 Australian women aged 18-97 years using OBS (%water and %water + %collagen). Of these, 935 women had DXA measures (percent and absolute fibroglandular dense volume, %FGV and FGV, respectively) and 354 had conventional mammographic measures (percent and absolute dense area). The distributions for each breast density measure were described across categories of age and BMI. RESULTS The mean age was 38 years (standard deviation = 15). Median breast density measures decreased with age and BMI for all three modalities, except for DXA-FGV, which increased with BMI and decreased after age 30. The variation in breast density measures was largest for younger women and decreased with increasing age and BMI. CONCLUSION This unique study describes the distribution of breast density measures for women aged 18-97 using alternative and conventional modalities of measurement. While this study is the largest of its kind, larger sample sizes are needed to provide clinically useful age-standardized measures to identify women with high breast density for their age or BMI.
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Affiliation(s)
- Dilukshi Perera
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Perth, WA, 6009, Australia
| | - Sarah Pirikahu
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Perth, WA, 6009, Australia
| | - Jane Walter
- University Health Network, Toronto, ON, Canada
| | - Gemma Cadby
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Perth, WA, 6009, Australia
| | - Ellie Darcey
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Perth, WA, 6009, Australia
| | - Rachel Lloyd
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Perth, WA, 6009, Australia
| | - Martha Hickey
- Department of Obstetrics and Gynaecology, University of Melbourne and the Royal Women's Hospital, Melbourne, VIC, Australia
| | - Christobel Saunders
- Department of Surgery, Royal Melbourne Hospital, The University of Melbourne, Melbourne, VIC, Australia
| | - Michael Hackmann
- School of Human Sciences, The University of Western Australia, Perth, WA, Australia
- Optical and Biomedical Engineering Laboratory School of Electrical, Electronic and Computer Engineering, The University of Western Australia, Perth, WA, Australia
| | - David D Sampson
- Surry Biophotonics, Advanced Technology Institute and School of Biosciences and Medicine, The University of Surrey, Guildford, Surrey, UK
| | - John Shepherd
- Epidemiology and Population Sciences in the Pacific Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Lothar Lilge
- University Health Network, Toronto, ON, Canada
- Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Jennifer Stone
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Perth, WA, 6009, Australia.
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Lloyd R, Pirikahu S, Walter J, Cadby G, Darcey E, Perera D, Hickey M, Saunders C, Karnowski K, Sampson DD, Shepherd J, Lilge L, Stone J. Alternative methods to measure breast density in younger women. Br J Cancer 2023; 128:1701-1709. [PMID: 36828870 PMCID: PMC10133329 DOI: 10.1038/s41416-023-02201-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 01/19/2023] [Accepted: 02/06/2023] [Indexed: 02/26/2023] Open
Abstract
BACKGROUND Breast density is a strong and potentially modifiable breast cancer risk factor. Almost everything we know about breast density has been derived from mammography, and therefore, very little is known about breast density in younger women aged <40. This study examines the acceptability and performance of two alternative breast density measures, Optical Breast Spectroscopy (OBS) and Dual X-ray Absorptiometry (DXA), in women aged 18-40. METHODS Breast tissue composition (percent water, collagen, and lipid content) was measured in 539 women aged 18-40 using OBS. For a subset of 169 women, breast density was also measured via DXA (percent fibroglandular dense volume (%FGV), absolute dense volume (FGV), and non-dense volume (NFGV)). Acceptability of the measurement procedures was assessed using an adapted validated questionnaire. Performance was assessed by examining the correlation and agreement between the measures and their associations with known determinants of mammographic breast density. RESULTS Over 93% of participants deemed OBS and DXA to be acceptable. The correlation between OBS-%water + collagen and %FGV was 0.48. Age and BMI were inversely associated with OBS-%water + collagen and %FGV and positively associated with OBS-%lipid and NFGV. CONCLUSIONS OBS and DXA provide acceptable and viable alternative methods to measure breast density in younger women aged 18-40 years.
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Affiliation(s)
- Rachel Lloyd
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, Perth, WA, Australia
| | - Sarah Pirikahu
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, Perth, WA, Australia
| | - Jane Walter
- University Health Network, Toronto, ON, Canada
| | - Gemma Cadby
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, Perth, WA, Australia
| | - Ellie Darcey
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, Perth, WA, Australia
| | - Dilukshi Perera
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, Perth, WA, Australia
| | - Martha Hickey
- Department of Obstetrics and Gynaecology, University of Melbourne and the Royal Women's Hospital, Melbourne, VIC, Australia
| | - Christobel Saunders
- Department of Surgery, Royal Melbourne Hospital, The University of Melbourne, Melbourne, VIC, Australia
| | - Karol Karnowski
- Optical and Biomedical Engineering Laboratory School of Electrical, Electronic and Computer Engineering, The University of Western Australia, Perth, WA, Australia
| | - David D Sampson
- Surry Biophotonics, Advanced Technology Institute and School of Biosciences and Medicine, The University of Surrey, Guildford, Surrey, UK
| | - John Shepherd
- Epidemiology and Population Sciences in the Pacific Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Lothar Lilge
- University Health Network, Toronto, ON, Canada.,Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Jennifer Stone
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, Perth, WA, Australia.
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