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Barnes I, Garcia-Closas M, Gathani T, Sweetland S, Floud S, Reeves GK. A comparative analysis of risk factor associations with interval and screen-detected breast cancers: A large UK prospective study. Int J Cancer 2024; 155:979-987. [PMID: 38669116 DOI: 10.1002/ijc.34968] [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: 09/09/2023] [Revised: 02/28/2024] [Accepted: 03/22/2024] [Indexed: 04/28/2024]
Abstract
The associations of certain factors, such as age and menopausal hormone therapy, with breast cancer risk are known to differ for interval and screen-detected cancers. However, the extent to which associations of other established breast cancer risk factors differ by mode of detection is unclear. We investigated associations of a wide range of risk factors using data from a large UK cohort with linkage to the National Health Service Breast Screening Programme, cancer registration, and other health records. We used Cox regression to estimate adjusted relative risks (RRs) and 95% confidence intervals (CIs) for associations between risk factors and breast cancer risk. A total of 9421 screen-detected and 5166 interval cancers were diagnosed in 517,555 women who were followed for an average of 9.72 years. We observed the following differences in risk factor associations by mode of detection: greater body mass index (BMI) was associated with a smaller increased risk of interval (RR per 5 unit increase 1.07, 95% CI 1.03-1.11) than screen-detected cancer (RR 1.27, 1.23-1.30); having a first-degree family history was associated with a greater increased risk of interval (RR 1.81, 1.68-1.95) than screen-detected cancer (RR 1.52, 1.43-1.61); and having had previous breast surgery was associated with a greater increased risk of interval (RR 1.85, 1.72-1.99) than screen-detected cancer (RR 1.34, 1.26-1.42). As these differences in associations were relatively unchanged after adjustment for tumour grade, and are in line with the effects of these factors on mammographic density, they are likely to reflect the effects of these risk factors on screening sensitivity.
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Affiliation(s)
- Isobel Barnes
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | | | - Toral Gathani
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Siân Sweetland
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Sarah Floud
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Gillian K Reeves
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
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Kim S, Mai Tran TX, Kim MK, Chung MS, Lee EH, Lee W, Park B. Associations between breast cancer risk factors and mammographic breast density in a large cross-section of Korean women. Eur J Cancer Prev 2024; 33:407-413. [PMID: 38375880 DOI: 10.1097/cej.0000000000000878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
BACKGROUND We investigated the association between established risk factors for breast cancer and mammographic breast density in Korean women. METHODS This large cross-sectional study included 8 460 928 women aged >40 years, who were screened for breast cancer between 2009 and 2018. Breast density was assessed using the Breast Imaging Reporting and Data System. This study used multiple logistic regression analyses of age, BMI, age at menarche, menopausal status, menopausal age, parity, breastfeeding status, oral contraceptive use, family history of breast cancer, physical activity, smoking, drinking and hormone replacement therapy use to investigate their associations with mammographic breast density. Analyses were performed using SAS software. RESULTS Of 8 460 928 women, 4 139 869 (48.9%) had nondense breasts and 4 321 059 (51.1%) had dense breasts. Factors associated with dense breasts were: earlier age at menarche [<15 vs. ≥15; adjusted odds ratio (aOR), 1.18; 95% confidence interval (CI), 1.17-1.18], premenopausal status (aOR, 2.01; 95% CI, 2.00-2.02), later age at menopause (≥52 vs. <52; aOR, 1.23; 95% CI, 1.22-1.23), nulliparity (aOR, 1.64; 95% CI, 1.63-1.65), never breastfed (aOR, 1.23; 95% CI, 1.23-1.24) and use of hormone replacement therapy (aOR, 1.29; 95% CI, 1.28-1.29). Women with a higher BMI and the use of oral contraceptives were more likely to have nondense breasts. CONCLUSION Lower BMI, reproductive health and behavioral factors were associated with dense breasts in Korean women. Additional research should investigate the relationship between mammographic breast density, breast cancer risk factors and breast cancer risk.
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Affiliation(s)
- Soyeoun Kim
- Department of Preventive Medicine, Hanyang University College of Medicine
- Institute for Health and Society, Hanyang University
| | - Thi Xuan Mai Tran
- Department of Preventive Medicine, Hanyang University College of Medicine
- Institute for Health and Society, Hanyang University
| | - Mi Kyung Kim
- Department of Preventive Medicine, Hanyang University College of Medicine
- Institute for Health and Society, Hanyang University
| | - Min Sung Chung
- Department of Surgery, Hanyang University College of Medicine, Seoul
| | - Eun Hye Lee
- Department of Radiology, Soonchunhyang University Hospital Bucheon, Soonchunhyang University College of Medicine, Bucheon
| | - Woojoo Lee
- Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul, Republic of Korea
| | - Boyoung Park
- Department of Preventive Medicine, Hanyang University College of Medicine
- Institute for Health and Society, Hanyang University
- Hanyang Institute of Bioscience and Biotechnology, Hanyang University, Seoul, Republic of Korea
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Bendinelli B, Caini S, Assedi M, Ermini I, Pastore E, Facchini L, Gilio MA, Duroni G, Fontana M, Querci A, Ambrogetti D, Saieva C, Masala G. Cigarette smoking and mammographic breast density in post-menopausal women from the EPIC Florence cohort. Front Oncol 2024; 14:1335645. [PMID: 38515572 PMCID: PMC10955064 DOI: 10.3389/fonc.2024.1335645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 02/12/2024] [Indexed: 03/23/2024] Open
Abstract
Introduction Cigarette smoking has been recognized as a risk factor for breast cancer (BC) also if the biological mechanism remains poorly understood. High mammographic breast density (MBD) is associated with BC risk and many BC risk factors, such as genetic, anthropometric, reproductive and lifestyle factors and age, are also able to modulate MBD. The aim of the present study was to prospectively explore, in post-menopausal women, the association between smoking habits and MBD, assessed using an automated software, considering duration and intensity of smoking. Methods The analysis was carried out in 3,774 women enrolled in the European Prospective Investigation into Cancer and Nutrition (EPIC) Florence cohort in 1993-98, participating in the 2004-06 follow up (FU) and with at least one full-field digital mammography (FFDM) performed after FU. For each woman, detailed information on smoking habits, anthropometry, lifestyle and reproductive history was collected at enrollment and at FU. Smoking information at baseline and at FU was integrated. The fully automated Volpara™ software was used to obtain total breast volume (cm3), absolute breast dense volume (DV, cm3) and volumetric percent density (VPD, %) from the first available FFDM (average 5.3 years from FU). Multivariable linear regression models were applied to evaluate the associations between smoking habits and VPD or DV. Results An inverse association between smoking exposure and VPD emerged (Diff% -7.96%, p <0.0001 for current smokers and -3.92%, p 0.01 for former smokers, compared with non-smokers). An inverse dose-response relationship with number of cigarettes/day, years of smoking duration and lifetime smoking exposure (pack-years) and a direct association with time since smoking cessation among former smokers emerged. Similar associations, with an attenuated effect, emerged when DV was considered as the outcome variable. Discussion This longitudinal study confirms the inverse association between active smoking, a known risk factor for BC, and MBD among post-menopausal women. The inclusion of smoking habits in the existing BC risk prediction models could be evaluated in future studies.
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Affiliation(s)
- Benedetta Bendinelli
- Clinical Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Saverio Caini
- Cancer Risk Factors and Lifestyle Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Melania Assedi
- Cancer Risk Factors and Lifestyle Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Ilaria Ermini
- Cancer Risk Factors and Lifestyle Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Elisa Pastore
- Clinical Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Luigi Facchini
- Cancer Risk Factors and Lifestyle Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Maria Antonietta Gilio
- Breast Cancer Screening Branch, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Giacomo Duroni
- Clinical Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Miriam Fontana
- Clinical Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Andrea Querci
- Cancer Risk Factors and Lifestyle Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Daniela Ambrogetti
- Breast Cancer Screening Branch, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Calogero Saieva
- Cancer Risk Factors and Lifestyle Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Giovanna Masala
- Clinical Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
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Sun D, Huang Z, Dong W, Zhao X, Liu C, Sheng Y. Effects of bariatric surgery on breast density in adult obese women: systematic review and meta-analysis. Front Immunol 2023; 14:1160809. [PMID: 37325648 PMCID: PMC10264659 DOI: 10.3389/fimmu.2023.1160809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 05/19/2023] [Indexed: 06/17/2023] Open
Abstract
Introduction Bariatric surgery is one of the most effective methods for treating obesity. It can effectively reduce body weight and reduce the incidence of obesity-related breast cancer. However, there are different conclusions about how bariatric surgery changes breast density. The purpose of this study was to clarify the changes in breast density from before to after bariatric surgery. Methods The relevant literature was searched through PubMed and Embase to screen for studies. Meta-analysis was used to clarify the changes in breast density from before to after bariatric surgery. Results A total of seven studies were included in this systematic review and meta-analysis, including a total of 535 people. The average body mass index decreased from 45.3 kg/m2 before surgery to 34.4 kg/m2 after surgery. By the Breast Imaging Reporting and Data System score, the proportion of grade A breast density from before to after bariatric surgery decreased by 3.83% (183 vs. 176), grade B (248 vs. 263) increased by 6.05%, grade C (94 vs. 89) decreased by 5.32%, and grade D (1 vs. 4) increased by 300%. There was no significant change in breast density from before to after bariatric surgery (OR=1.27, 95% confidence interval (CI) [0.74, 2.20], P=0.38). By the Volpara density grade score, postoperative volumetric breast density increased (standardized mean difference = -0.68, 95% CI [-1.08, -0.27], P = 0.001). Discussions Breast density increased significantly after bariatric surgery, but this depended on the method of detecting breast density. Further randomized controlled studies are needed to validate our conclusions.
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Affiliation(s)
- Dezheng Sun
- Department of Thyroid and Breast Surgery, Changhai Hospital Affiliated to Naval Medical University, Shanghai, China
| | - Zhiping Huang
- Department of Hepatobiliary Surgery and Organ Transplantation, General Hospital of Southern Theater Command of People's Liberation Army of China (PLA), Guangzhou, China
| | - Wenyan Dong
- Department of Thyroid and Breast Surgery, Changhai Hospital Affiliated to Naval Medical University, Shanghai, China
| | - Xiang Zhao
- Department of Thyroid and Breast Surgery, Changhai Hospital Affiliated to Naval Medical University, Shanghai, China
| | - Chaoqian Liu
- Department of Thyroid and Breast Surgery, Changhai Hospital Affiliated to Naval Medical University, Shanghai, China
| | - Yuan Sheng
- Department of Thyroid and Breast Surgery, Changhai Hospital Affiliated to Naval Medical University, Shanghai, China
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Kehm RD, Walter EJ, Oskar S, White ML, Tehranifar P, Herbstman JB, Perera F, Lilge L, Miller RL, Terry MB. Exposure to polycyclic aromatic hydrocarbons during pregnancy and breast tissue composition in adolescent daughters and their mothers: a prospective cohort study. Breast Cancer Res 2022; 24:47. [PMID: 35821060 PMCID: PMC9277813 DOI: 10.1186/s13058-022-01546-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 07/01/2022] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND Polycyclic aromatic hydrocarbons (PAH), which are found in air pollution, have carcinogenic and endocrine disrupting properties that might increase breast cancer risk. PAH exposure might be particularly detrimental during pregnancy, as this is a time when the breast tissue of both the mother and daughter is undergoing structural and functional changes. In this study, we tested the hypothesis that ambient PAH exposure during pregnancy is associated with breast tissue composition, measured one to two decades later, in adolescent daughters and their mothers. METHODS We conducted a prospective analysis using data from a New York City cohort of non-Hispanic Black and Hispanic mother-daughter dyads (recruited 1998-2006). During the third trimester of pregnancy, women wore backpacks containing a continuously operating air sampling pump for two consecutive days that measured ambient exposure to eight carcinogenic higher molecular weight nonvolatile PAH compounds (Σ8 PAH) and pyrene. When daughters (n = 186) and mothers (n = 175) reached ages 11-20 and 29-55 years, respectively, optical spectroscopy (OS) was used to evaluate measures of breast tissue composition (BTC) that positively (water content, collagen content, optical index) and negatively (lipid content) correlate with mammographic breast density, a recognized risk factor for breast cancer. Multivariable linear regression was used to evaluate associations between ambient PAH exposure and BTC, overall and by exposure to household tobacco smoke during pregnancy (yes/no). Models were adjusted for race/ethnicity, age, and percent body fat at OS. RESULTS No overall associations were found between ambient PAH exposure (Σ8 PAH or pyrene) and BTC, but statistically significant additive interactions between Σ8 PAH and household tobacco smoke exposure were identified for water content and optical index in both daughters and mothers (interaction p values < 0.05). Σ8 PAH exposure was associated with higher water content (βdaughters = 0.42, 95% CI = 0.15-0.68; βmothers = 0.32, 95% CI = 0.05-0.61) and higher optical index (βdaughters = 0.38, 95% CI = 0.12-0.64; βmothers = 0.38, 95% CI = 0.12-0.65) in those exposed to household tobacco smoke during pregnancy; no associations were found in non-smoking households (interaction p values < 0.05). CONCLUSIONS Exposure to ambient Σ8 PAH and tobacco smoke during pregnancy might interact synergistically to impact BTC in mothers and daughters. If replicated in other cohorts, these findings might have important implications for breast cancer risk across generations.
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Affiliation(s)
- Rebecca D. Kehm
- grid.21729.3f0000000419368729Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 W 168th St, Room 1605, New York, NY 10032 USA
| | - E. Jane Walter
- grid.231844.80000 0004 0474 0428Princess Margaret Cancer Centre, University Health Network, 101 College St, Toronto, ON M5G 0A3 Canada
| | - Sabine Oskar
- grid.21729.3f0000000419368729Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 W 168th St, Room 1605, New York, NY 10032 USA
| | - Melissa L. White
- grid.21729.3f0000000419368729Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 W 168th St, Room 1605, New York, NY 10032 USA
| | - Parisa Tehranifar
- grid.21729.3f0000000419368729Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 W 168th St, Room 1605, New York, NY 10032 USA ,grid.239585.00000 0001 2285 2675Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY 10032 USA
| | - Julie B. Herbstman
- grid.21729.3f0000000419368729Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032 USA
| | - Frederica Perera
- grid.21729.3f0000000419368729Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032 USA
| | - Lothar Lilge
- grid.231844.80000 0004 0474 0428Princess Margaret Cancer Centre, University Health Network, 101 College St, Toronto, ON M5G 0A3 Canada ,grid.17063.330000 0001 2157 2938Department of Medical Biophysics, University of Toronto, 101 College St, Toronto, ON M5G 0A3 Canada
| | - Rachel L. Miller
- grid.59734.3c0000 0001 0670 2351Division of Clinical Immunology, Department of Medicine, Icahn School of Medicine at Mount Sinai, 1 Gustave L Levy Place, New York, NY 10029 USA
| | - Mary Beth Terry
- grid.21729.3f0000000419368729Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 W 168th St, Room 1605, New York, NY 10032 USA ,grid.239585.00000 0001 2285 2675Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY 10032 USA
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Abstract
In screening for breast cancer (BC), mammographic breast density (MBD) is a powerful risk factor that increases breast carcinogenesis and synergistically reduces the sensitivity of mammography. It also reduces specificity of lesion identification, leading to recalls, additional testing, and delayed and later-stage diagnoses, which result in increased health care costs. These findings provide the foundation for dense breast notification laws and lead to the increase in patient and provider interest in MBD. However, unlike other risk factors for BC, MBD is dynamic through a woman’s lifetime and is modifiable. Although MBD is known to change as a result of factors such as reproductive history and hormonal status, few conclusions have been reached for lifestyle factors such as alcohol, diet, physical activity, smoking, body mass index (BMI), and some commonly used medications. Our review examines the emerging evidence for the association of modifiable factors on MBD and the influence of MBD on BC risk. There are clear associations between alcohol use and menopausal hormone therapy and increased MBD. Physical activity and the Mediterranean diet lower the risk of BC without significant effect on MBD. Although high BMI and smoking are known risk factors for BC, they have been found to decrease MBD. The influence of several other factors, including caffeine intake, nonhormonal medications, and vitamins, on MBD is unclear. We recommend counseling patients on these modifiable risk factors and using this knowledge to help with informed decision making for tailored BC prevention strategies.
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Affiliation(s)
- Sara P Lester
- Corresponding author: Sara P. Lester, MD, Division of General Internal Medicine, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA.
| | - Aparna S Kaur
- Division of General Internal Medicine, Mayo Clinic, Rochester, MN, USA
| | - Suneela Vegunta
- Division of Women’s Health Internal Medicine, Mayo Clinic, Scottsdale, AZ, USA
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Yu T, Ye DM. The epidemiologic factors associated with breast density: A review. JOURNAL OF RESEARCH IN MEDICAL SCIENCES 2022; 27:53. [PMID: 36092490 PMCID: PMC9450246 DOI: 10.4103/jrms.jrms_962_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 01/14/2022] [Accepted: 01/26/2022] [Indexed: 11/04/2022]
Abstract
In recent years, some studies have evaluated the epidemiologic factors associated with breast density. However, the variant and inconsistent results exist. In addition, breast density has been proved to be a significant risk factor associated with breast cancer. Our review summarized the published studies and emphasized the crucial factors including epidemiological factors associated with breast density. In addition, we also discussed the potential reasons for the discrepant results with risk factors. To decrease the incidence and mortality rates for breast cancer, in clinical practice, breast density should be included for clinical risk models in addition to epidemiological factors, and physicians should get more concentrate on those women with risk factors and provide risk-based breast cancer screening regimens.
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Vegunta S, Lester SP, Pruthi S, Mussallem DM. Effects of major lifestyle factors on breast cancer risk: impact of weight, nutrition, physical activity, alcohol and tobacco. BREAST CANCER MANAGEMENT 2020. [DOI: 10.2217/bmt-2020-0033] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Breast cancer (BC) is the most commonly diagnosed cancer and second most common cause of cancer death in US women. Family history and genetics are well-known BC risk factors, but they only account for 15–20% of BC cases. Therefore, in addition to family history, healthcare providers must consider a woman’s modifiable and nonmodifiable personal risk factors that are associated with an increase in BC risk. The World Cancer Research Fund/American Institute for Cancer Research estimate that 30% of BC cases in the US are preventable. Lifestyle education is imperative given the magnitude of BC occurrence. Evidence supports prevention as an effective, long-term strategy for reducing risk. Healthcare providers are key stakeholders in empowering patients to adopt a healthy lifestyle for primary BC prevention. In this paper, we review the available evidence on modifiable BC risk including weight management, nutrition, physical activity, alcohol and tobacco use and provide strategies to counsel patients on lifestyle modifications.
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Affiliation(s)
- Suneela Vegunta
- Division of Women’s Health Internal Medicine, Mayo Clinic, Scottsdale, AZ, USA
| | - Sara P Lester
- Division of General Internal Medicine, Mayo Clinic, Rochester, MN, USA
| | - Sandhya Pruthi
- Division of General Internal Medicine, Mayo Clinic, Rochester, MN, USA
| | - Dawn M Mussallem
- Jacoby Center for Breast Health, Mayo Clinic, Jacksonville, FL, USA
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Menopausal Transition, Body Mass Index, and Prevalence of Mammographic Dense Breasts in Middle-Aged Women. J Clin Med 2020; 9:jcm9082434. [PMID: 32751482 PMCID: PMC7465213 DOI: 10.3390/jcm9082434] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Revised: 07/24/2020] [Accepted: 07/28/2020] [Indexed: 12/12/2022] Open
Abstract
The interrelationship between menopausal stage, excessive adiposity and dense breasts remains unclear. We aimed to investigate the relationship between menopausal stage and dense-breast prevalence in midlife women while considering a possible effect modification of being overweight. The present cross-sectional study comprised 82,677 Korean women, aged 35–65 years, who attended a screening exam. Menopausal stages were categorized based on the Stages of Reproductive Aging Workshop (STRAW + 10) criteria. Mammographic breast density was categorized according to Breast Imaging Reporting and Data System (BI-RADS). Dense breasts were defined as BI-RADS Breast Density category D (extremely dense). The prevalence of dense breasts decreased as menopausal stage increased (p-trend < 0.001), and this pattern was pronounced in overweight women than non-overweight women (p-interaction = 0.016). Compared with pre-menopause, the multivariable-adjusted prevalence ratios (and 95% confidence intervals) for dense breasts were 0.98 (0.96–1.00) in early transition, 0.89 (0.86–0.92) in late transition, and 0.55 (0.52–0.59) in post-menopause, among non-overweight women, while corresponding prevalence ratios were 0.92 (0.87–0.98), 0.83 (0.77–0.90) and 0.36 (0.31–0.41) among overweight women. The prevalence of dense breasts was inversely associated with increasing menopausal stages and significantly decreased from the late menopausal transition, with stronger declines among overweight women.
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Park B, Lim SE, Ahn H, Yoon J, Choi YS. Heterogenous Effect of Risk Factors on Breast Cancer across the Breast Density Categories in a Korean Screening Population. Cancers (Basel) 2020; 12:cancers12061391. [PMID: 32481621 PMCID: PMC7352951 DOI: 10.3390/cancers12061391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 05/14/2020] [Accepted: 05/26/2020] [Indexed: 12/24/2022] Open
Abstract
We evaluated the heterogeneity of the effect of known risk factors on breast cancer development based on breast density by using the Breast Imaging-Reporting and Data System (BI-RADS). In total, 4,898,880 women, aged 40-74 years, who participated in the national breast cancer screening program in 2009-2010 were followed up to December 2018. Increased age showed a heterogeneous association with breast cancer (1-year hazard ratio (HR) = 0.92, 1.00 (reference), 1.03, and 1.03 in women with BI-RADS density category 1, 2, 3, and 4, respectively; P-heterogeneity < 0.001). More advanced age at menopause increased breast cancer risk in all BI-RADS categories. This was more prominent in women with BI-RADS density category 1 but less prominent in women in other BI-RADS categories (P-heterogeneity = 0.009). In postmenopausal women, a family history of breast cancer, body mass index ≥ 25 kg/m2, and smoking showed a heterogeneous association with breast cancer across all BI-RADS categories. Other risk factors including age at menarche, menopause, hormone replacement therapy after menopause, oral contraceptive use, and alcohol consumption did not show a heterogeneous association with breast cancer across the BI-RADS categories. Several known risk factors of breast cancer had a heterogeneous effect on breast cancer development across breast density categories, especially in postmenopausal women.
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Affiliation(s)
- Boyoung Park
- Department of Medicine, Hanyang University College of Medicine, Seoul 04763, Korea; (S.-E.L.); (H.A.)
- Correspondence: ; Tel.: +82-2-2220-0682
| | - Se-Eun Lim
- Department of Medicine, Hanyang University College of Medicine, Seoul 04763, Korea; (S.-E.L.); (H.A.)
| | - HyoJin Ahn
- Department of Medicine, Hanyang University College of Medicine, Seoul 04763, Korea; (S.-E.L.); (H.A.)
| | - Junghyun Yoon
- Graduate School of Public Health, Hanyang University, Seoul 04763, Korea;
| | - Yun Su Choi
- Department of Preventive Medicine, Hanyang University College of Medicine, Seoul 04763, Korea;
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McBride RB, Fei K, Rothstein JH, Alexeeff SE, Song X, Sakoda LC, McGuire V, Achacoso N, Acton L, Liang RY, Lipson JA, Yaffe MJ, Rubin DL, Whittemore AS, Habel LA, Sieh W. Alcohol and Tobacco Use in Relation to Mammographic Density in 23,456 Women. Cancer Epidemiol Biomarkers Prev 2020; 29:1039-1048. [PMID: 32066618 PMCID: PMC7196522 DOI: 10.1158/1055-9965.epi-19-0348] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2019] [Revised: 07/27/2019] [Accepted: 02/07/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Percent density (PD) is a strong risk factor for breast cancer that is potentially modifiable by lifestyle factors. PD is a composite of the dense (DA) and nondense (NDA) areas of a mammogram, representing predominantly fibroglandular or fatty tissues, respectively. Alcohol and tobacco use have been associated with increased breast cancer risk. However, their effects on mammographic density (MD) phenotypes are poorly understood. METHODS We examined associations of alcohol and tobacco use with PD, DA, and NDA in a population-based cohort of 23,456 women screened using full-field digital mammography machines manufactured by Hologic or General Electric. MD was measured using Cumulus. Machine-specific effects were estimated using linear regression, and combined using random effects meta-analysis. RESULTS Alcohol use was positively associated with PD (P trend = 0.01), unassociated with DA (P trend = 0.23), and inversely associated with NDA (P trend = 0.02) adjusting for age, body mass index, reproductive factors, physical activity, and family history of breast cancer. In contrast, tobacco use was inversely associated with PD (P trend = 0.0008), unassociated with DA (P trend = 0.93), and positively associated with NDA (P trend<0.0001). These trends were stronger in normal and overweight women than in obese women. CONCLUSIONS These findings suggest that associations of alcohol and tobacco use with PD result more from their associations with NDA than DA. IMPACT PD and NDA may mediate the association of alcohol drinking, but not tobacco smoking, with increased breast cancer risk. Further studies are needed to elucidate the modifiable lifestyle factors that influence breast tissue composition, and the important role of the fatty tissues on breast health.
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Affiliation(s)
- Russell B McBride
- Institute for Translational Epidemiology, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Kezhen Fei
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Joseph H Rothstein
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Stacey E Alexeeff
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Xiaoyu Song
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Lori C Sakoda
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Valerie McGuire
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California
| | - Ninah Achacoso
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Luana Acton
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Rhea Y Liang
- Department of Radiology, Stanford University School of Medicine, Stanford, California
| | - Jafi A Lipson
- Department of Radiology, Stanford University School of Medicine, Stanford, California
| | - Martin J Yaffe
- Departments of Medical Biophysics and Medical Imaging, University of Toronto, Toronto, Ontario, Canada
| | - Daniel L Rubin
- Department of Radiology, Stanford University School of Medicine, Stanford, California
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California
| | - Alice S Whittemore
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California
| | - Laurel A Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Weiva Sieh
- Institute for Translational Epidemiology, Icahn School of Medicine at Mount Sinai, New York, New York.
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York
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12
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Moran O, Eisen A, Demsky R, Blackmore K, Knight JA, Panchal S, Ginsburg O, Zbuk K, Yaffe M, Metcalfe KA, Narod SA, Kotsopoulos J. Predictors of mammographic density among women with a strong family history of breast cancer. BMC Cancer 2019; 19:631. [PMID: 31242899 PMCID: PMC6595553 DOI: 10.1186/s12885-019-5855-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2018] [Accepted: 06/19/2019] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Mammographic density is one of the strongest risk factors for breast cancer. In the general population, mammographic density can be modified by various exposures; whether this is true for women a strong family history is not known. Thus, we evaluated the association between reproductive, hormonal, and lifestyle risk factors and mammographic density among women with a strong family history of breast cancer but no BRCA1 or BRCA2 mutation. METHODS We included 97 premenopausal and 59 postmenopausal women (age range: 27-68 years). Risk factor data was extracted from the research questionnaire closest in time to the mammogram performed nearest to enrollment. The Cumulus software was used to measure percent density, dense area, and non-dense area for each mammogram. Multivariate generalized linear models were used to evaluate the relationships between breast cancer risk factors and measures of mammographic density, adjusting for relevant covariates. RESULTS Among premenopausal women, those who had two live births had a mean percent density of 28.8% vs. 41.6% among women who had one live birth (P=0.04). Women with a high body weight had a lower mean percent density compared to women with a low body weight among premenopausal (17.6% vs. 33.2%; P=0.0006) and postmenopausal women (8.7% vs. 14.7%; P=0.04). Among premenopausal women, those who smoked for 14 years or longer had a lower mean dense area compared to women who smoked for a shorter duration (25.3cm2 vs. 53.1cm2; P=0.002). Among postmenopausal women, former smokers had a higher mean percent density (19.5% vs. 10.8%; P=0.003) and dense area (26.9% vs. 16.4%; P=0.01) compared to never smokers. After applying the Bonferroni correction, the association between body weight and percent density among premenopausal women remained statistically significant. CONCLUSIONS In this cohort of women with a strong family history of breast cancer, body weight was associated with mammographic density. These findings suggest that mammographic density may explain the underlying relationship between some of these risk factors and breast cancer risk, and lend support for the inclusion of mammographic density into risk prediction models.
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Affiliation(s)
- Olivia Moran
- Women's College Research Institute, Women's College Hospital, 76 Grenville St., 6th Floor, Toronto, ON, Canada.,Department of Nutritional Sciences, University of Toronto, Toronto, ON, Canada
| | - Andrea Eisen
- Toronto-Sunnybrook Regional Cancer Center, Toronto, ON, Canada
| | - Rochelle Demsky
- Division of Gynecologic Oncology, Princess Margaret Hospital, University Health Network, Toronto, ON, Canada.,Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | | | - Julia A Knight
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Seema Panchal
- Mount Sinai Hospital, University of Toronto, Toronto, ON, Canada
| | - Ophira Ginsburg
- Perlmutter Cancer Centre, Department of Population Health, NYU Langone Health, New York, NY, USA
| | - Kevin Zbuk
- Department of Oncology, McMaster University, Hamilton, ON, Canada
| | - Martin Yaffe
- Department of Medical Biophysics, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Kelly A Metcalfe
- Women's College Research Institute, Women's College Hospital, 76 Grenville St., 6th Floor, Toronto, ON, Canada.,Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Toronto, ON, Canada
| | - Steven A Narod
- Women's College Research Institute, Women's College Hospital, 76 Grenville St., 6th Floor, Toronto, ON, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Joanne Kotsopoulos
- Women's College Research Institute, Women's College Hospital, 76 Grenville St., 6th Floor, Toronto, ON, Canada. .,Department of Nutritional Sciences, University of Toronto, Toronto, ON, Canada. .,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
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13
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Characteristics of Mammographic Breast Density and Associated Factors for Chinese Women: Results from an Automated Measurement. JOURNAL OF ONCOLOGY 2019; 2019:4910854. [PMID: 31015834 PMCID: PMC6444251 DOI: 10.1155/2019/4910854] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Revised: 02/01/2019] [Accepted: 02/19/2019] [Indexed: 11/18/2022]
Abstract
Background Characteristics of mammographic density for Chinese women are understudied. This study aims to identify factors associated with mammographic density in China using a quantitative method. Methods Mammographic density was measured for a total of 1071 (84 with and 987 without breast cancer) women using an automatic algorithm AutoDensity. Pearson tests examined relationships between density and continuous variables and t-tests compared differences of mean density values between groupings of categorical variables. Linear models were built using multiple regression. Results Percentage density and dense area were positively associated with each other for cancer-free (r=0.487, p<0.001) and cancer groups (r=0.446, p<0.001), respectively. For women without breast cancer, weight and BMI (p<0.001) were found to be negatively associated (r=-0.237, r=-0.272) with percentage density whereas they were found to be positively associated (r=0.110, r=0.099) with dense area; age at mammography was found to be associated with percentage density (r=-0.202, p<0.001) and dense area (r=-0.086, p<0.001) but did not add any prediction within multivariate models; lower percentage density was found within women with secondary education background or below compared to women with tertiary education. For women with breast cancer, percentage density demonstrated similar relationships with that of cancer-free women whilst breast area was the only factor associated with dense area (r=0.739, p<0.001). Conclusion This is the first time that mammographic density was measured by a quantitative method for women in China and identified associations should be useful to health policy makers who are responsible for introducing effective models of breast cancer prevention and diagnosis.
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14
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White AJ, Weinberg CR, O'Meara ES, Sandler DP, Sprague BL. Airborne metals and polycyclic aromatic hydrocarbons in relation to mammographic breast density. Breast Cancer Res 2019; 21:24. [PMID: 30760301 PMCID: PMC6373138 DOI: 10.1186/s13058-019-1110-7] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2018] [Accepted: 01/25/2019] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Breast density is strongly related to breast cancer. Identifying associations between environmental exposures and density may elucidate relationships with breast cancer. Metals and polycyclic aromatic hydrocarbons (PAHs) may influence breast density via oxidative stress or endocrine disruption. METHODS Study participants (n = 222,581) underwent a screening mammogram in 2011 at a radiology facility in the Breast Cancer Surveillance Consortium. Zip code residential levels of airborne PAHs and metals (arsenic, cadmium, chromium, cobalt, lead, manganese, mercury, nickel, and selenium) were assessed using the 2011 EPA National Air Toxics Assessment. Breast density was measured using the Breast Imaging-Reporting and Data System (BI-RADS) lexicon. Logistic regression was used to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CI) for the individual air toxics and dense breasts (BI-RADS 3 or 4). Weighted quantile sum (WQS) regression was used to model the association between the air toxic mixture and density. RESULTS Higher residential levels of arsenic, cobalt, lead, manganese, nickel, or PAHs were individually associated with breast density. Comparing the highest to the lowest quartile, higher odds of having dense breasts were observed for cobalt (OR = 1.60, 95% CI 1.56-1.64) and lead (OR = 1.56, 95% CI 1.52-1.64). Associations were stronger for premenopausal women. The WQS index was associated with density overall (OR = 1.22, 95% CI 1.20-1.24); the most heavily weighted air toxics were lead and cobalt. CONCLUSIONS In this first study to evaluate the association between air toxics and breast density, women living in areas with higher concentrations of lead and cobalt were more likely to have dense breasts.
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Affiliation(s)
- Alexandra J White
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, 27709-2233, USA.
| | - Clarice R Weinberg
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Ellen S O'Meara
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, 27709-2233, USA
| | - Brian L Sprague
- Departments of Surgery and Radiology, University of Vermont, Burlington, VT, USA
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15
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Ko KP, Kim SJ, Huzarski T, Gronwald J, Lubinski J, Lynch HT, Armel S, Park SK, Karlan B, Singer CF, Neuhausen SL, Narod SA, Kotsopoulos J. The association between smoking and cancer incidence in BRCA1 and BRCA2 mutation carriers. Int J Cancer 2018; 142:2263-2272. [PMID: 29330845 PMCID: PMC6020833 DOI: 10.1002/ijc.31257] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Revised: 11/20/2017] [Accepted: 12/07/2017] [Indexed: 11/06/2022]
Abstract
Tobacco smoke is an established carcinogen, but the association between tobacco smoking and cancer risk in BRCA mutation carriers is not clear. The aim of this study was to evaluate prospectively the association between tobacco smoking and cancer incidence in a cohort of BRCA1 and BRCA2 mutation carriers. The study population consisted of unaffected BRCA mutation carriers. Information on lifestyle including smoking histories, reproductive factors, and past medical histories was obtained through questionnaires. Incident cancers were updated biennially via follow-up questionnaires. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using time-dependent Cox regression models. There were 700 incident cancers diagnosed over 26,711 person-years of follow-up. The most frequent cancers seen in BRCA mutation carriers were breast (n = 428; 61%) and ovarian (n = 109; 15%) cancer. Compared to nonsmokers, (ever) smoking was associated with a modest increased risk of all cancers combined (HR = 1.17; 95%CI 1.01-1.37). Women in the highest group of total pack-years (4.3-9.8) had an increased risk of developing any cancer (HR = 1.27; 95%CI 1.04-1.56), breast cancer (HR = 1.33, 95%CI 1.02-1.75), and ovarian cancer (HR = 1.68; 95%CI 1.06-2.67) compared to never smokers. The associations between tobacco smoking and cancer did not differ by BRCA mutation type or by age at diagnosis. This prospective study suggests that tobacco smoking is associated with a modest increase in the risks of breast and ovarian cancer among women with BRCA1 or BRCA2 mutation.
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Affiliation(s)
- Kwang-Pil Ko
- Department of Preventive Medicine, Gachon University College of Medicine, Incheon, Korea
| | - Shana J Kim
- Women's College Research Institute, Women's College Hospital, Toronto, ON, Canada
| | - Tomasz Huzarski
- International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Jacek Gronwald
- International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Jan Lubinski
- International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Henry T Lynch
- Department of Preventive Medicine and Public Health, Creighton University School of Medicine, Omaha, NE
| | - Susan Armel
- Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, University of Toronto, ON, Canada
| | - Sue K Park
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea
| | - Beth Karlan
- Gynecology Oncology, Cedars Sinai Medical Center, Los Angeles, CA
| | - Christian F Singer
- Department of Obstetrics and Gynecology and Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Susan L Neuhausen
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA
| | - Steven A Narod
- Women's College Research Institute, Women's College Hospital, Toronto, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Joanne Kotsopoulos
- Women's College Research Institute, Women's College Hospital, Toronto, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
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16
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Abstract
Mammographic density is an independent strong risk factor for breast cancer. However, the influence of factors on mammographic density in premenopausal women remains unclear. In the Southern Professional Women Breast Cancer Screening Project, we assessed the associations between mammographic density and its influential factors using multivariate logistic regression in premenopausal women adjusting for BMI, age, duration of breastfeeding, number of live births, and breast size. A total of 1699 premenopausal women aged 27 to 57 years, who had been screened by mammography, were enrolled in this cross-sectional study. Overall, 85.2% were categorized as having dense breasts (BI-RADS density 3 and 4) and 14.8% as having fatty breasts (BI-RADS density 1 and 2). In multivariate and logistic regression analysis, only BMI and age were significantly negatively correlated with mammographic density in premenopausal women (P<0.001). No significant associations between mammographic density and number of deliveries, breastfeeding duration, education level, family history of breast cancer, as well as breast size and sleep quality, were identified in the study. Age and BMI are negatively associated with mammographic density in premenopausal Chinese women. Information on the influential factors of mammographic density in premenopausal women might provide meaningful insights into breast cancer prevention.
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17
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Pereira A, Garmendia ML, Uauy R, Neira P, Lopez-Arana S, Malkov S, Shepherd J. Determinants of volumetric breast density in Chilean premenopausal women. Breast Cancer Res Treat 2017; 162:343-352. [PMID: 28132392 DOI: 10.1007/s10549-017-4126-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2016] [Accepted: 01/18/2017] [Indexed: 10/20/2022]
Abstract
PURPOSE High mammographic breast density (BD) is a strong risk factor of breast cancer; however, little is known in women under 40 years of age. Recently, dual-energy X-ray Absorptiometry (DXA) has been developed as a low-dose method to measure BD in young populations. Thus, our aims were to describe BD in relation to risk factors in Chilean women under 40 years old and to explore the equivalence of DXA to mammography for the measurement of BD. METHODS We selected 192 premenopausal Chilean female participants of the DERCAM study for whom we have anthropometric, sociodemographic, and gyneco-obstetric data. The subjects received both digital mammograms (Hologic) and breast DXA scans (GE iDXA). Mammographic BD was estimated using a fully automated commercial method (VOLPARA®) and BI-RADS. Breast DXA scans were performed using a standardized protocol and the % fibroglandular volume (%FGV) was estimated considering a two-compartment model of adipose and fibroglandular tissue. RESULTS The mean age was 37 years (SD = 6.5) and 31.6% of the subjects were obese. The median %FGV and absolute FGV (AFGV) measured by DXA were 9% and 198.1 cm3 and for VOLPARA®, 8.6% and 58.0 cm3, respectively. The precision for %FGV after reposition was 2.8%. The correlation coefficients for %FGV, AFGV, and breast volume between DXA and mammography were over 0.7. Age and body mass index (BMI) were inversely associated with %FGV, and BMI was positively related to AFGV as estimated with DXA or mammography. We did not observe an association with gyneco-obstetric characteristics, education, and %FGV and AFGV; smoking was only associated with AFGV as measured by VOLPARA®. CONCLUSIONS DXA is an alternative method to measure volumetric BD; thus, it could be used to continuously monitor BD in adult women in follow-up studies or to assess BD in young women.
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Affiliation(s)
- Ana Pereira
- Institute of Nutrition and Food Technology, University of Chile, Av. El Líbano 5524, Macúl, Santiago, 7830490, Chile
| | - Maria Luisa Garmendia
- Institute of Nutrition and Food Technology, University of Chile, Av. El Líbano 5524, Macúl, Santiago, 7830490, Chile.
| | - Ricardo Uauy
- Institute of Nutrition and Food Technology, University of Chile, Av. El Líbano 5524, Macúl, Santiago, 7830490, Chile.,Pediatrics Division, School of Medicine, Pontificia Universidad Catolica de Chile, Santiago, Chile.,London School of Hygiene and Tropical Medicine, London, UK
| | - Paulina Neira
- Imágenes de la mama, Servicio de Radiología, Clínica Las Condes, Santiago, Chile
| | | | - Serghei Malkov
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - John Shepherd
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
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18
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Hart V, Sturgeon SR, Reich N, Sievert LL, Crawford SL, Gold EB, Avis NE, Reeves KW. Menopausal vasomotor symptoms and incident breast cancer risk in the Study of Women's Health Across the Nation. Cancer Causes Control 2016; 27:1333-1340. [PMID: 27680016 DOI: 10.1007/s10552-016-0811-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2016] [Accepted: 09/24/2016] [Indexed: 12/01/2022]
Abstract
PURPOSE Two case-control studies reported a 50 % decreased breast cancer risk among women who experienced menopausal vasomotor symptoms (VMS), but one cohort study found no association. VMS may be triggered by declining estrogen levels during menopause, whereas elevated estrogen levels have been associated with increased breast cancer risk. VMS may thus be indicative of lower susceptibility to breast cancer. METHODS We evaluated this relationship in the longitudinal Study of Women's Health Across the Nation (SWAN), using discrete survival analysis of approximately annual data on VMS and self-reported breast cancer occurrences for up to 13 years of follow-up in 3,098 women who were pre- or early perimenopausal at enrollment. RESULTS Over an average 11.4 years of follow-up, 129 incident breast cancer cases were self-reported, and approximately 50 % of participants experienced VMS. Symptomatic women had a reduced risk of breast cancer compared to non-symptomatic women (adjusted HR 0.63, 95 % CI 0.39, 1.00). The association was stronger in the subgroup of women who fully transitioned to postmenopause during follow-up (n = 67 cases, adjusted HR 0.45, 95 % CI 0.26, 0.77). CONCLUSION VMS appeared to be a marker of reduced breast cancer risk. Future research is needed to understand the biology underlying this relationship.
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Affiliation(s)
- Vicki Hart
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, 411 Arnold House, 715 North Pleasant Street, Amherst, MA, 01003, USA
| | - Susan R Sturgeon
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, 411 Arnold House, 715 North Pleasant Street, Amherst, MA, 01003, USA
| | - Nicholas Reich
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, 411 Arnold House, 715 North Pleasant Street, Amherst, MA, 01003, USA
| | | | - Sybil L Crawford
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA, USA
| | - Ellen B Gold
- Department of Public Health Sciences, School of Medicine, University of California School of Medicine, Davis, CA, USA
| | - Nancy E Avis
- Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Katherine W Reeves
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, 411 Arnold House, 715 North Pleasant Street, Amherst, MA, 01003, USA.
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19
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Wong JYY, Chang PY, Gold EB, Johnson WO, Lee JS. Environmental tobacco smoke and risk of late-diagnosis incident fibroids in the Study of Women's Health across the Nation (SWAN). Fertil Steril 2016; 106:1157-1164. [PMID: 27445196 DOI: 10.1016/j.fertnstert.2016.06.025] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2016] [Revised: 06/08/2016] [Accepted: 06/16/2016] [Indexed: 11/16/2022]
Abstract
OBJECTIVE To assess the longitudinal relationship of environmental tobacco smoke (ETS) exposure during midlife, and its interaction with active smoking, with the risk of late-diagnosis incident uterine fibroids during the menopausal transition. DESIGN Thirteen-year prospective cohort study. SETTING Not applicable. PATIENT(S) Community-based, multiracial/ethnic cohort of 2,575 women aged 42 to 52 years at baseline, undergoing the menopausal transition. INTERVENTION(S) Questionnaire and blood draws. MAIN OUTCOME MEASURE(S) Discrete-time proportional odds models were used to estimate the conditional odds ratio (OR) and 95% confidence interval (CI) of incident fibroids, adjusted for menopausal status, race/ethnicity, study site, age, education, estradiol levels, sex hormone use, body mass index, timing of blood draw, age at menarche, alcohol use, and smoking status and pack-years. RESULT(S) As part of SWAN, at each near-annual study visit, ETS exposure, smoking, and fibroid occurrence were self-reported via questionnaire, and blood draws were collected. Women who were exposed to ETS (≥1 person-hour/week) had 1.28 (95% CI, 1.03, 1.60) times the adjusted odds of incident fibroids in the ensuing year compared the unexposed. The odds were elevated in never smokers (adjusted OR 1.34; 95% CI, 1.06, 1.70) and former smokers (adjusted OR 2.57; 95% CI, 1.05, 7.23). CONCLUSION(S) In midlife, ETS exposure was associated with an increased risk of late-diagnosis incident fibroids in women undergoing the menopausal transition.
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Affiliation(s)
- Jason Y Y Wong
- Division of Endocrinology, Gerontology, and Metabolism, Department of Medicine, and Division of Epidemiology, Department of Health Research and Policy, School of Medicine, Stanford University, Stanford, California.
| | - Po-Yin Chang
- Division of Endocrinology, Gerontology, and Metabolism, Department of Medicine, and Division of Epidemiology, Department of Health Research and Policy, School of Medicine, Stanford University, Stanford, California
| | - Ellen B Gold
- Division of Epidemiology, Department of Public Health Sciences, School of Medicine, University of California-Davis, Davis, California
| | - Wesley O Johnson
- Department of Statistics, University of California-Irvine, Irvine, California
| | - Jennifer S Lee
- Division of Endocrinology, Gerontology, and Metabolism, Department of Medicine, and Division of Epidemiology, Department of Health Research and Policy, School of Medicine, Stanford University, Stanford, California; Medical Services, Veteran Affairs, Palo Alto Health Care System, Palo Alto, California
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20
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McCormack VA, Burton A, dos-Santos-Silva I, Hipwell JH, Dickens C, Salem D, Kamal R, Hartman M, Lee CPL, Chia KS, Ozmen V, Aribal ME, Flugelman AA, Lajous M, Lopez-Riduara R, Rice M, Romieu I, Ursin G, Qureshi S, Ma H, Lee E, van Gils CH, Wanders JOP, Vinayak S, Ndumia R, Allen S, Vinnicombe S, Moss S, Won Lee J, Kim J, Pereira A, Garmendia ML, Sirous R, Sirous M, Peplonska B, Bukowska A, Tamimi RM, Bertrand K, Nagata C, Kwong A, Vachon C, Scott C, Perez-Gomez B, Pollan M, Maskarinec G, Giles G, Hopper J, Stone J, Rajaram N, Teo SH, Mariapun S, Yaffe MJ, Schüz J, Chiarelli AM, Linton L, Boyd NF. International Consortium on Mammographic Density: Methodology and population diversity captured across 22 countries. Cancer Epidemiol 2016; 40:141-51. [PMID: 26724463 PMCID: PMC4738079 DOI: 10.1016/j.canep.2015.11.015] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2015] [Revised: 11/12/2015] [Accepted: 11/30/2015] [Indexed: 12/31/2022]
Abstract
Mammographic density (MD) is a quantitative trait, measurable in all women, and is among the strongest markers of breast cancer risk. The population-based epidemiology of MD has revealed genetic, lifestyle and societal/environmental determinants, but studies have largely been conducted in women with similar westernized lifestyles living in countries with high breast cancer incidence rates. To benefit from the heterogeneity in risk factors and their combinations worldwide, we created an International Consortium on Mammographic Density (ICMD) to pool individual-level epidemiological and MD data from general population studies worldwide. ICMD aims to characterize determinants of MD more precisely, and to evaluate whether they are consistent across populations worldwide. We included 11755 women, from 27 studies in 22 countries, on whom individual-level risk factor data were pooled and original mammographic images were re-read for ICMD to obtain standardized comparable MD data. In the present article, we present (i) the rationale for this consortium; (ii) characteristics of the studies and women included; and (iii) study methodology to obtain comparable MD data from original re-read films. We also highlight the risk factor heterogeneity captured by such an effort and, thus, the unique insight the pooled study promises to offer through wider exposure ranges, different confounding structures and enhanced power for sub-group analyses.
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Affiliation(s)
- Valerie A McCormack
- Section of Environment and Radiation, International Agency for Research on Cancer, Lyon, France.
| | - Anya Burton
- Section of Environment and Radiation, International Agency for Research on Cancer, Lyon, France
| | - Isabel dos-Santos-Silva
- Dept of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - John H Hipwell
- Centre for Medical Image Computing, University College London, UK
| | | | | | - Rasha Kamal
- Woman Imaging Unit, Radiodiagnosis Department, Kasr El Aini, Cairo University Hospitals, Cairo, Egypt
| | - Mikael Hartman
- Department of Surgery, Yong Loo Lin School of Medicine and Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Charmaine Pei Ling Lee
- Department of Surgery, Yong Loo Lin School of Medicine and Saw Swee Hock School of Public Health, National University of Singapore, Singapore; NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore
| | - Kee-Seng Chia
- NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore
| | | | | | | | - Martín Lajous
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, USA; Center for Research on Population Health, Instituto Nacional de Salud Pública, Mexico, Mexico City, Mexico
| | - Ruy Lopez-Riduara
- Center for Research on Population Health, Instituto Nacional de Salud Pública, Mexico, Mexico City, Mexico
| | - Megan Rice
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Isabelle Romieu
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France
| | - Giske Ursin
- Cancer Registry of Norway, Oslo, Norway; Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway; Department of Preventive Medicine, University of Southern California, Los Angeles, California, USA
| | - Samera Qureshi
- Norwegian Center for Minority Health Research (NAKMI), Oslo, Norway
| | - Huiyan Ma
- Department of Population Sciences, Beckman Research Institute, City of Hope, Duarte, USA
| | - Eunjung Lee
- Department of Preventive Medicine, University of Southern California, Los Angeles, California, USA
| | - Carla H van Gils
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands
| | - Johanna O P Wanders
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands
| | | | - Rose Ndumia
- Aga Khan University Hospital, Nairobi, Kenya
| | - Steve Allen
- Department of Imaging, Royal Marsden NHS Foundation Trust, London, UK
| | - Sarah Vinnicombe
- Division of Cancer Research, Ninewells Hospital & Medical School, Dundee, UK
| | - Sue Moss
- Wolfson Institute of Preventive Medicine, Queen Mary University of London, UK
| | | | - Jisun Kim
- Asan Medical Center, Seoul, Republic of Korea
| | - Ana Pereira
- Institute of Nutrition and Food Technology, University of Chile, Chile
| | | | - Reza Sirous
- Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mehri Sirous
- Isfahan University of Medical Sciences, Isfahan, Iran
| | | | | | - Rulla M Tamimi
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | | | | | - Ava Kwong
- Division of Breast Surgery, The University of Hong Kong Faculty of Medicine, and Department of Surgery, Hong Kong Sanatorium and Hospital, Hong Kong, People's Republic of China
| | - Celine Vachon
- Dept Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Christopher Scott
- Dept Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Beatriz Perez-Gomez
- Cancer Epidemiology Unit, Instituto de Salud Carlos III and CIBERESP, Madrid, Spain
| | - Marina Pollan
- Cancer Epidemiology Unit, Instituto de Salud Carlos III and CIBERESP, Madrid, Spain
| | | | - Graham Giles
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia; School of Population and Global Health, The University of Melbourne, Australia
| | - John Hopper
- School of Population and Global Health, The University of Melbourne, Australia
| | - Jennifer Stone
- Centre for Genetic Origins of Health and Disease, University of Western Australia, Australia
| | - Nadia Rajaram
- Breast Cancer Research Group, University Malaya Medical Centre, University Malaya, Kuala Lumpur, Malaysia
| | - Soo-Hwang Teo
- Breast Cancer Research Group, University Malaya Medical Centre, University Malaya, Kuala Lumpur, Malaysia; Cancer Research Malaysia, Subang Jaya, Malaysia
| | - Shivaani Mariapun
- Breast Cancer Research Group, University Malaya Medical Centre, University Malaya, Kuala Lumpur, Malaysia
| | | | - Joachim Schüz
- Section of Environment and Radiation, International Agency for Research on Cancer, Lyon, France
| | - Anna M Chiarelli
- Ontario Breast Screening Program, Cancer Care Ontario, Toronto, Canada
| | - Linda Linton
- Princess Margaret Cancer Centre, Toronto, Canada
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Jacobsen KK, Lynge E, Vejborg I, Tjønneland A, von Euler-Chelpin M, Andersen ZJ. Cigarette smoking and mammographic density in the Danish Diet, Cancer and Health cohort. Cancer Causes Control 2015; 27:271-80. [PMID: 26645565 DOI: 10.1007/s10552-015-0704-3] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2015] [Accepted: 11/26/2015] [Indexed: 10/22/2022]
Abstract
PURPOSE Smoking before first childbirth increases breast cancer risk, but the biological mechanism remains unknown and may involve mammographic density (MD), one of the strongest biomarkers of breast cancer risk. We aimed to examine whether active smoking and passive smoking were associated with MD. METHODS For the 5,356 women (4,489 postmenopausal) from the Danish Diet, Cancer and Health cohort (1993-1997) who attended mammographic screening in Copenhagen (1993-2001), we used MD (mixed/dense or fatty) assessed at the first screening after cohort entry. Active smoking (status, duration, and intensity) and passive smoking were assessed at cohort baseline (1993-1997) via questionnaire, together with other breast cancer risk factors. Logistic regression was used to estimate associations (odds ratios, 95 % confidence intervals) between smoking and MD, adjusting for confounders. RESULTS Two thousand and twenty-six (56.5 %) women had mixed/dense MD, 2,214 (41.4 %) were current, and 1,175 (21.9 %) former smokers. Current smokers had significantly lower odds (0.86, 0.75-0.99) of having mixed/dense MD compared to never smokers, while former smoking was not associated with MD. Inverse association between smoking and MD was strongest in women who initiated smoking before age of 16 years (0.79, 0.64-0.96), smoked ≥15 cigarettes/day (0.83, 0.71-0.98), smoked ≥5 pack-years (0.62, 0.43-0.89), smoked >30 years (0.86, 0.75-0.99), and smoked ≥11 years before first childbirth (0.70, 0.51-0.96). Association between smoking and MD diminished after smoking cessation, with increased odds of having mixed/dense breasts in women who quit smoking >20 years ago as compared to current smokers (1.37, 1.01-1.67). There was no association between passive smoking and MD. CONCLUSIONS We found an inverse association between active smoking and MD.
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Affiliation(s)
- Katja Kemp Jacobsen
- Department of Public Health, Center for Epidemiology and Screening, University of Copenhagen, Øster Farimagsgade 5, 1014, Copenhagen K, Denmark. .,Department of Technology, Faculty of Health and Technology, Metropolitan University College, Copenhagen N, Denmark.
| | - Elsebeth Lynge
- Department of Public Health, Center for Epidemiology and Screening, University of Copenhagen, Øster Farimagsgade 5, 1014, Copenhagen K, Denmark
| | - Ilse Vejborg
- Diagnostic Imaging Centre, Copenhagen University Hospital, Rigshospitalet, Copenhagen K, Denmark
| | - Anne Tjønneland
- Institute of Cancer Epidemiology, Danish Cancer Society, Copenhagen K, Denmark
| | - My von Euler-Chelpin
- Department of Public Health, Center for Epidemiology and Screening, University of Copenhagen, Øster Farimagsgade 5, 1014, Copenhagen K, Denmark
| | - Zorana J Andersen
- Department of Public Health, Center for Epidemiology and Screening, University of Copenhagen, Øster Farimagsgade 5, 1014, Copenhagen K, Denmark
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22
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Huynh S, von Euler-Chelpin M, Raaschou-Nielsen O, Hertel O, Tjønneland A, Lynge E, Vejborg I, Andersen ZJ. Long-term exposure to air pollution and mammographic density in the Danish Diet, Cancer and Health cohort. Environ Health 2015; 14:31. [PMID: 25879829 PMCID: PMC4392475 DOI: 10.1186/s12940-015-0017-8] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2014] [Accepted: 03/19/2015] [Indexed: 05/30/2023]
Abstract
BACKGROUND Growing evidence suggests that air pollution may be a risk factor for breast cancer, but the biological mechanism remains unknown. High mammographic density (MD) is one of the strongest predictors and biomarkers of breast cancer risk, but it has yet to be linked to air pollution. We investigated the association between long-term exposure to traffic-related air pollution and MD in a prospective cohort of women 50 years and older. METHODS For the 4,769 women (3,930 postmenopausal) participants in the Danish Diet, Cancer and Health cohort (1993-1997) who attended mammographic screening in Copenhagen (1993-2001), we used MD assessed at the first screening after cohort entry. MD was defined as mixed/dense or fatty. Traffic-related air pollution at residence was assessed by modeled levels of nitrogen oxides (NOx) and nitrogen dioxide (NO2). The association between mean NOx and NO2 levels since 1971 until cohort baseline (1993-97) and MD was analyzed using logistic regression, adjusting for confounders, and separately by menopause, smoking status, and obesity. RESULTS We found inverse, statistically borderline significant associations between long-term exposure to air pollution and having mixed/dense MD in our fully adjusted model (OR; 95% CI: 0.96; 0.93-1.01 per 20 μg/m(3) of NOx and 0.89; 0.80- 0.98 per 10 μg/m(3) of NO2). There was no interaction with menopause, smoking, or obesity. CONCLUSION Traffic-related air pollution exposure does not increase MD, indicating that if air pollution increases breast cancer risk, it is not via MD.
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Affiliation(s)
- Stephanie Huynh
- Center for Epidemiology and Screening, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.
- Department of Neuroscience, Smith College, Northampton, Massachusetts, USA.
| | - My von Euler-Chelpin
- Center for Epidemiology and Screening, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.
| | | | - Ole Hertel
- Department of Environmental Science, Aarhus University, Roskilde, Denmark.
| | - Anne Tjønneland
- Danish Center for Cancer Research, Danish Cancer Society, Copenhagen, Denmark.
| | - Elsebeth Lynge
- Center for Epidemiology and Screening, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.
| | - Ilse Vejborg
- Diagnostic Imaging Centre, Copenhagen University Hospital, Copenhagen, Denmark.
| | - Zorana J Andersen
- Center for Epidemiology and Screening, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.
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23
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Abstract
Tobacco smoke has both carcinogenic effects and anti-estrogenic properties and its inconsistent association with breast cancer risk in observational studies may be because of these competing effects across the lifecourse. We conducted a prospective study of prenatal smoke exposure, childhood household smoke exposure, and adult active smoke exposure and mammographic density, a strong intermediate marker of breast cancer risk, in an adult follow-up of existing US birth cohorts. Specifically, we followed up women who were born between 1959 and 1967 and whose mothers participated in either the Collaborative Perinatal Project (Boston and Providence sites) or the Childhood Health and Development Study in California. Of the 1134 women interviewed in adulthood (ranging in age from 39 to 49 years at interview), 79% had a screening mammogram. Cigarette smoking was reported by mothers at the time of their pregnancy; 40% of mothers smoked while pregnant. Women whose mothers smoked during pregnancy had a 3.1% (95% confidence interval (CI) = -6.0%, -0.2%) lower mammographic density than women whose mothers did not smoke during pregnancy. When we further accounted for adult body mass index and adult smoking status, the association remained (β = -2.7, 95% CI = -5.0, -0.3). When we examined patterns of smoking, prenatal smoke exposure without adult smoke exposure was associated with a 5.6% decrease in mammographic density (β = -5.6, 95% CI = -9.6, -1.6). Given the strength of mammographic density as an intermediate marker for breast cancer, the inverse associations between mammographic density and smoking patterns across the lifecourse may help explain the complex association between cigarette smoking and breast cancer risk.
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24
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Gierach GL, Geller BM, Shepherd JA, Patel DA, Vacek PM, Weaver DL, Chicoine RE, Pfeiffer RM, Fan B, Mahmoudzadeh AP, Wang J, Johnson JM, Herschorn SD, Brinton LA, Sherman ME. Comparison of mammographic density assessed as volumes and areas among women undergoing diagnostic image-guided breast biopsy. Cancer Epidemiol Biomarkers Prev 2014; 23:2338-48. [PMID: 25139935 DOI: 10.1158/1055-9965.epi-14-0257] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Mammographic density (MD), the area of non-fatty-appearing tissue divided by total breast area, is a strong breast cancer risk factor. Most MD analyses have used visual categorizations or computer-assisted quantification, which ignore breast thickness. We explored MD volume and area, using a volumetric approach previously validated as predictive of breast cancer risk, in relation to risk factors among women undergoing breast biopsy. METHODS Among 413 primarily white women, ages 40 to 65 years, undergoing diagnostic breast biopsies between 2007 and 2010 at an academic facility in Vermont, MD volume (cm(3)) was quantified in craniocaudal views of the breast contralateral to the biopsy target using a density phantom, whereas MD area (cm(2)) was measured on the same digital mammograms using thresholding software. Risk factor associations with continuous MD measurements were evaluated using linear regression. RESULTS Percent MD volume and area were correlated (r = 0.81) and strongly and inversely associated with age, body mass index (BMI), and menopause. Both measures were inversely associated with smoking and positively associated with breast biopsy history. Absolute MD measures were correlated (r = 0.46) and inversely related to age and menopause. Whereas absolute dense area was inversely associated with BMI, absolute dense volume was positively associated. CONCLUSIONS Volume and area MD measures exhibit some overlap in risk factor associations, but divergence as well, particularly for BMI. IMPACT Findings suggest that volume and area density measures differ in subsets of women; notably, among obese women, absolute density was higher with volumetric methods, suggesting that breast cancer risk assessments may vary for these techniques.
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Affiliation(s)
- Gretchen L Gierach
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, Maryland.
| | | | - John A Shepherd
- University of California, San Francisco, San Francisco, California
| | - Deesha A Patel
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, Maryland
| | | | | | | | - Ruth M Pfeiffer
- Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, Maryland
| | - Bo Fan
- University of California, San Francisco, San Francisco, California
| | | | - Jeff Wang
- University of California, San Francisco, San Francisco, California
| | | | | | - Louise A Brinton
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, Maryland
| | - Mark E Sherman
- Breast and Gynecologic Cancer Research Group, Division of Cancer Prevention, National Cancer Institute, NIH, Bethesda, Maryland
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25
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Association of mammographic breast density with dairy product consumption, sun exposure, and daily activity. ISRN ONCOLOGY 2014; 2014:159049. [PMID: 24729894 PMCID: PMC3960730 DOI: 10.1155/2014/159049] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 12/12/2013] [Accepted: 01/22/2014] [Indexed: 11/18/2022]
Abstract
Background. Mammographic density is a risk factor, for breast cancer and its association with various factors is under investigation; we carried out a study to assess its relationship with daily dairy intake, sun exposure, and physical activities. Patients and Methods. Women ≥40 years of age were interviewed about habits of dairy product consumption, daily sun exposure and physical activity. Exclusion criteria consisted of history of breast cancer, consumption of calcium and vitamin D supplements, hormone replacement therapy, or renal disease. Mammographic densities were classified according to the classification system of the American College of Radiologists into 4 classes. Results. Overall 703 cases were entered in the study. The mean age was 48.2 ± 6.2 years. The most common and least frequent classes of mammographic density were classes 2 and 4, respectively. There was no significant association between mammographic density and rate of dairy consumption, amount of sunlight exposure, and daily physical activity. Conclusion. Relation of sunlight exposure and intake of milk products with mammographic density need further study, while the subject of physical activity can be evaluated by a systematic review and meta-analysis of the existing literature.
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26
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Dai H, Yan Y, Wang P, Liu P, Cao Y, Xiong L, Luo Y, Pan T, Ma X, Wang J, Yang Z, Liu X, Chen C, Huang Y, Li Y, Wang Y, Hao X, Ye Z, Chen K. Distribution of mammographic density and its influential factors among Chinese women. Int J Epidemiol 2014; 43:1240-51. [PMID: 24639441 DOI: 10.1093/ije/dyu042] [Citation(s) in RCA: 68] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Mammographic density (MD) has not been systematically investigated among Chinese women. Breast cancer screening programmes provided detailed information on MD in a large number of asymptomatic women. METHODS In the Multi-modality Independent Screening Trial (MIST), we estimated the association between MD and its influential factors using logistic regression, adjusting for age, body mass index (BMI) and study area. Differences between Chinese and other ethnic groups with respect to MD were also explored with adjustment for age and BMI. RESULTS A total of 28 388 women aged 45 to 65 years, who had been screened by mammography, were enrolled in the study. Of these, 49.2% were categorized as having dense breasts (BI-RADS density 3 and 4) and 50.8% as fatty breasts (BI-RADS density 1 and 2). Postmenopausal status [odds ratio (OR) = 0.66; 95% confidence interval (CI): 0.62-0.70] and higher number of live births (OR = 0.56; 95% CI: 0.46-0.68) were inversely associated with MD, whereas prior benign breast disease (OR = 1.48; 95% CI: 1.40-1.56) and later age at first birth (OR = 1.17; 95% CI: 1.08-1.27) were positively associated with MD. In comparison with the data from the Breast Cancer Surveillance Consortium, we found that women in MIST were more likely to have fatty breasts than Americans (from the Breast Cancer Surveillance Consortium) in the older age group (≥50 years) but more likely to have dense breasts in the younger age group (<50 years). CONCLUSIONS This study suggests that several risk factors for breast cancer were associated with breast density in Chinese women. Information on the determinants of mammographic density may provide valuable insights into breast cancer aetiology.
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Affiliation(s)
- Hongji Dai
- Department of Epidemiology and Biostatistics and Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Prevention and Cure Center of Breast Disease, Third Hospital of Nanchang, Nanchang, China, Department of Medical Image and Department of Cancer Prevention and Control, Liaoning Cancer Institute and Hospital, Shenyang, China, Center for Breast Disease, Haidian Maternal and Child Health Hospital, Beijing, China, Department of Radiology, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China and Chinese Anti-Cancer Association, Tianjin, China
| | - Ye Yan
- Department of Epidemiology and Biostatistics and Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Prevention and Cure Center of Breast Disease, Third Hospital of Nanchang, Nanchang, China, Department of Medical Image and Department of Cancer Prevention and Control, Liaoning Cancer Institute and Hospital, Shenyang, China, Center for Breast Disease, Haidian Maternal and Child Health Hospital, Beijing, China, Department of Radiology, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China and Chinese Anti-Cancer Association, Tianjin, China
| | - Peishan Wang
- Department of Epidemiology and Biostatistics and Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Prevention and Cure Center of Breast Disease, Third Hospital of Nanchang, Nanchang, China, Department of Medical Image and Department of Cancer Prevention and Control, Liaoning Cancer Institute and Hospital, Shenyang, China, Center for Breast Disease, Haidian Maternal and Child Health Hospital, Beijing, China, Department of Radiology, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China and Chinese Anti-Cancer Association, Tianjin, China
| | - Peifang Liu
- Department of Epidemiology and Biostatistics and Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Prevention and Cure Center of Breast Disease, Third Hospital of Nanchang, Nanchang, China, Department of Medical Image and Department of Cancer Prevention and Control, Liaoning Cancer Institute and Hospital, Shenyang, China, Center for Breast Disease, Haidian Maternal and Child Health Hospital, Beijing, China, Department of Radiology, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China and Chinese Anti-Cancer Association, Tianjin, China
| | - Yali Cao
- Department of Epidemiology and Biostatistics and Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Prevention and Cure Center of Breast Disease, Third Hospital of Nanchang, Nanchang, China, Department of Medical Image and Department of Cancer Prevention and Control, Liaoning Cancer Institute and Hospital, Shenyang, China, Center for Breast Disease, Haidian Maternal and Child Health Hospital, Beijing, China, Department of Radiology, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China and Chinese Anti-Cancer Association, Tianjin, China
| | - Li Xiong
- Department of Epidemiology and Biostatistics and Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Prevention and Cure Center of Breast Disease, Third Hospital of Nanchang, Nanchang, China, Department of Medical Image and Department of Cancer Prevention and Control, Liaoning Cancer Institute and Hospital, Shenyang, China, Center for Breast Disease, Haidian Maternal and Child Health Hospital, Beijing, China, Department of Radiology, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China and Chinese Anti-Cancer Association, Tianjin, China
| | - Yahong Luo
- Department of Epidemiology and Biostatistics and Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Prevention and Cure Center of Breast Disease, Third Hospital of Nanchang, Nanchang, China, Department of Medical Image and Department of Cancer Prevention and Control, Liaoning Cancer Institute and Hospital, Shenyang, China, Center for Breast Disease, Haidian Maternal and Child Health Hospital, Beijing, China, Department of Radiology, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China and Chinese Anti-Cancer Association, Tianjin, China
| | - Tie Pan
- Department of Epidemiology and Biostatistics and Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Prevention and Cure Center of Breast Disease, Third Hospital of Nanchang, Nanchang, China, Department of Medical Image and Department of Cancer Prevention and Control, Liaoning Cancer Institute and Hospital, Shenyang, China, Center for Breast Disease, Haidian Maternal and Child Health Hospital, Beijing, China, Department of Radiology, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China and Chinese Anti-Cancer Association, Tianjin, China
| | - Xiangjun Ma
- Department of Epidemiology and Biostatistics and Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Prevention and Cure Center of Breast Disease, Third Hospital of Nanchang, Nanchang, China, Department of Medical Image and Department of Cancer Prevention and Control, Liaoning Cancer Institute and Hospital, Shenyang, China, Center for Breast Disease, Haidian Maternal and Child Health Hospital, Beijing, China, Department of Radiology, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China and Chinese Anti-Cancer Association, Tianjin, China
| | - Jie Wang
- Department of Epidemiology and Biostatistics and Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Prevention and Cure Center of Breast Disease, Third Hospital of Nanchang, Nanchang, China, Department of Medical Image and Department of Cancer Prevention and Control, Liaoning Cancer Institute and Hospital, Shenyang, China, Center for Breast Disease, Haidian Maternal and Child Health Hospital, Beijing, China, Department of Radiology, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China and Chinese Anti-Cancer Association, Tianjin, China
| | - Zhenhua Yang
- Department of Epidemiology and Biostatistics and Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Prevention and Cure Center of Breast Disease, Third Hospital of Nanchang, Nanchang, China, Department of Medical Image and Department of Cancer Prevention and Control, Liaoning Cancer Institute and Hospital, Shenyang, China, Center for Breast Disease, Haidian Maternal and Child Health Hospital, Beijing, China, Department of Radiology, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China and Chinese Anti-Cancer Association, Tianjin, China
| | - Xueou Liu
- Department of Epidemiology and Biostatistics and Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Prevention and Cure Center of Breast Disease, Third Hospital of Nanchang, Nanchang, China, Department of Medical Image and Department of Cancer Prevention and Control, Liaoning Cancer Institute and Hospital, Shenyang, China, Center for Breast Disease, Haidian Maternal and Child Health Hospital, Beijing, China, Department of Radiology, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China and Chinese Anti-Cancer Association, Tianjin, China
| | - Chuan Chen
- Department of Epidemiology and Biostatistics and Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Prevention and Cure Center of Breast Disease, Third Hospital of Nanchang, Nanchang, China, Department of Medical Image and Department of Cancer Prevention and Control, Liaoning Cancer Institute and Hospital, Shenyang, China, Center for Breast Disease, Haidian Maternal and Child Health Hospital, Beijing, China, Department of Radiology, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China and Chinese Anti-Cancer Association, Tianjin, China
| | - Yubei Huang
- Department of Epidemiology and Biostatistics and Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Prevention and Cure Center of Breast Disease, Third Hospital of Nanchang, Nanchang, China, Department of Medical Image and Department of Cancer Prevention and Control, Liaoning Cancer Institute and Hospital, Shenyang, China, Center for Breast Disease, Haidian Maternal and Child Health Hospital, Beijing, China, Department of Radiology, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China and Chinese Anti-Cancer Association, Tianjin, China
| | - Yi Li
- Department of Epidemiology and Biostatistics and Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Prevention and Cure Center of Breast Disease, Third Hospital of Nanchang, Nanchang, China, Department of Medical Image and Department of Cancer Prevention and Control, Liaoning Cancer Institute and Hospital, Shenyang, China, Center for Breast Disease, Haidian Maternal and Child Health Hospital, Beijing, China, Department of Radiology, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China and Chinese Anti-Cancer Association, Tianjin, China
| | - Yaogang Wang
- Department of Epidemiology and Biostatistics and Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Prevention and Cure Center of Breast Disease, Third Hospital of Nanchang, Nanchang, China, Department of Medical Image and Department of Cancer Prevention and Control, Liaoning Cancer Institute and Hospital, Shenyang, China, Center for Breast Disease, Haidian Maternal and Child Health Hospital, Beijing, China, Department of Radiology, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China and Chinese Anti-Cancer Association, Tianjin, China
| | - Xishan Hao
- Department of Epidemiology and Biostatistics and Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Prevention and Cure Center of Breast Disease, Third Hospital of Nanchang, Nanchang, China, Department of Medical Image and Department of Cancer Prevention and Control, Liaoning Cancer Institute and Hospital, Shenyang, China, Center for Breast Disease, Haidian Maternal and Child Health Hospital, Beijing, China, Department of Radiology, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China and Chinese Anti-Cancer Association, Tianjin, ChinaDepartment of Epidemiology and Biostatistics and Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Prevention and Cure Center of Breast Disease, Third Hospital of Nanchang, Nanchang, China, Department of Medical Image and Department of Cancer Prevention and Control, Liaoning Cancer Institute and Hospital, Shenyang, China, Center for Breast Disease, Haidian Maternal and Child Health Hospital, Beijing, China, Department of Radiology, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tian
| | - Zhaoxiang Ye
- Department of Epidemiology and Biostatistics and Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Prevention and Cure Center of Breast Disease, Third Hospital of Nanchang, Nanchang, China, Department of Medical Image and Department of Cancer Prevention and Control, Liaoning Cancer Institute and Hospital, Shenyang, China, Center for Breast Disease, Haidian Maternal and Child Health Hospital, Beijing, China, Department of Radiology, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China and Chinese Anti-Cancer Association, Tianjin, China
| | - Kexin Chen
- Department of Epidemiology and Biostatistics and Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Prevention and Cure Center of Breast Disease, Third Hospital of Nanchang, Nanchang, China, Department of Medical Image and Department of Cancer Prevention and Control, Liaoning Cancer Institute and Hospital, Shenyang, China, Center for Breast Disease, Haidian Maternal and Child Health Hospital, Beijing, China, Department of Radiology, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China, Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China and Chinese Anti-Cancer Association, Tianjin, China
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27
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Behrendt CE, Tumyan L, Gonser L, Shaw SL, Vora L, Paz IB, Ellenhorn JDI, Yim JH. Evaluation of expert criteria for preoperative magnetic resonance imaging of newly diagnosed breast cancer. Breast 2014; 23:341-5. [PMID: 24530008 DOI: 10.1016/j.breast.2014.01.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2013] [Revised: 12/11/2013] [Accepted: 01/09/2014] [Indexed: 01/15/2023] Open
Abstract
Despite 2 randomized trials reporting no reduction in operations or local recurrence at 1 year, preoperative magnetic resonance imaging (MRI) is increasingly used in diagnostic workup of breast cancer. We evaluated 5 utilization criteria recently proposed by experts. Of women (n = 340) newly diagnosed with unilateral breast cancer who underwent bilateral MRI, most (69.4%) met at least 1 criterion before MRI: mammographic density (44.4%), under consideration for partial breast irradiation (PBI) (19.7%), genetic-familial risk (12.9%), invasive lobular carcinoma (11.8%), and multifocal/multicentric disease (10.6%). MRI detected occult malignant lesion or extension of index lesion in 21.2% of index, 3.3% of contralateral, breasts. No expert criterion was associated with MRI-detected malignant lesion, which associated instead with pre-MRI plan of lumpectomy without PBI (48.2% of subjects): Odds Ratio 3.05, 95% CI 1.57-5.91 (p adjusted for multiple hypothesis testing = 0.007, adjusted for index-vs-contralateral breast and covariates). The expert guidelines were not confirmed by clinical evidence.
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MESH Headings
- Adult
- Aged
- Breast/pathology
- Breast/surgery
- Breast Density
- Breast Neoplasms/diagnosis
- Breast Neoplasms/genetics
- Breast Neoplasms/surgery
- Carcinoma, Ductal, Breast/diagnosis
- Carcinoma, Ductal, Breast/genetics
- Carcinoma, Ductal, Breast/surgery
- Carcinoma, Lobular/diagnosis
- Carcinoma, Lobular/genetics
- Carcinoma, Lobular/surgery
- Cohort Studies
- Female
- Genetic Predisposition to Disease
- Humans
- Magnetic Resonance Imaging/methods
- Mammary Glands, Human/abnormalities
- Mastectomy
- Mastectomy, Segmental
- Middle Aged
- Neoplasms, Multiple Primary/diagnosis
- Neoplasms, Multiple Primary/genetics
- Neoplasms, Multiple Primary/surgery
- Patient Selection
- Practice Guidelines as Topic/standards
- Radiotherapy, Adjuvant
- Retrospective Studies
- Risk Assessment
- Young Adult
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Affiliation(s)
- Carolyn E Behrendt
- Biostatistics, City of Hope National Medical Center, 1500 E. Duarte Road, Duarte, CA 91010, USA.
| | - Lusine Tumyan
- Diagnostic Radiology, City of Hope National Medical Center, 1500 E. Duarte Road, Duarte, CA 91010, USA
| | - Laura Gonser
- General Surgery, University of California San Francisco, Fresno Campus/Community Regional Medical Center, 2823 Fresno St., Fresno, CA 93721, USA
| | - Sara L Shaw
- Diagnostic Radiology, City of Hope National Medical Center, 1500 E. Duarte Road, Duarte, CA 91010, USA
| | - Lalit Vora
- Diagnostic Radiology, City of Hope National Medical Center, 1500 E. Duarte Road, Duarte, CA 91010, USA
| | - I Benjamin Paz
- Surgical Oncology, City of Hope National Medical Center, 1500 E. Duarte Road, Duarte, CA 91010, USA
| | - Joshua D I Ellenhorn
- Surgical Oncology, City of Hope National Medical Center, 1500 E. Duarte Road, Duarte, CA 91010, USA
| | - John H Yim
- Surgical Oncology, City of Hope National Medical Center, 1500 E. Duarte Road, Duarte, CA 91010, USA.
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28
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Brand JS, Czene K, Eriksson L, Trinh T, Bhoo-Pathy N, Hall P, Celebioglu F. Influence of lifestyle factors on mammographic density in postmenopausal women. PLoS One 2013; 8:e81876. [PMID: 24349146 PMCID: PMC3857226 DOI: 10.1371/journal.pone.0081876] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2013] [Accepted: 10/21/2013] [Indexed: 11/19/2022] Open
Abstract
Background Mammographic density is a strong risk factor for breast cancer. Apart from hormone replacement therapy (HRT), little is known about lifestyle factors that influence breast density. Methods We examined the effect of smoking, alcohol and physical activity on mammographic density in a population-based sample of postmenopausal women without breast cancer. Lifestyle factors were assessed by a questionnaire and percentage and area measures of mammographic density were measured using computer-assisted software. General linear models were used to assess the association between lifestyle factors and mammographic density and effect modification by body mass index (BMI) and HRT was studied. Results Overall, alcohol intake was positively associated with percent mammographic density (P trend = 0.07). This association was modified by HRT use (P interaction = 0.06): increasing alcohol intake was associated with increasing percent density in current HRT users (P trend = 0.01) but not in non-current users (P trend = 0.82). A similar interaction between alcohol and HRT was found for the absolute dense area, with a positive association being present in current HRT users only (P interaction = 0.04). No differences in mammographic density were observed across categories of smoking and physical activity, neither overall nor in stratified analyses by BMI and HRT use. Conclusions Increasing alcohol intake is associated with an increase in mammography density, whereas smoking and physical activity do not seem to influence density. The observed interaction between alcohol and HRT may pose an opportunity for HRT users to lower their mammographic density and breast cancer risk.
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Affiliation(s)
- Judith S. Brand
- Institution of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, Stockholm, Sweden
- * E-mail:
| | - Kamila Czene
- Institution of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, Stockholm, Sweden
| | - Louise Eriksson
- Institution of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, Stockholm, Sweden
| | - Thang Trinh
- Institution of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, Stockholm, Sweden
| | - Nirmala Bhoo-Pathy
- National Clinical Research Centre, Level 3, Dermatology Block, Hospital Kuala Lumpur, Jalan Pahang, Kuala Lumpur, Malaysia
- Julius Centre University of Malaya, Faculty of Medicine, University of Malaya, Lembah Pantai, Kuala Lumpur, Malaysia
| | - Per Hall
- Institution of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, Stockholm, Sweden
| | - Fuat Celebioglu
- Department of Clinical Science and Education, Södersjukhuset (KI SÖS), S1. Sjukhusbacken 10, Stockholm, Sweden
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29
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Gaudet MM, Gapstur SM, Sun J, Diver WR, Hannan LM, Thun MJ. Active Smoking and Breast Cancer Risk: Original Cohort Data and Meta-Analysis. ACTA ACUST UNITED AC 2013; 105:515-25. [PMID: 23449445 DOI: 10.1093/jnci/djt023] [Citation(s) in RCA: 198] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Mia M Gaudet
- Epidemiology Research Program, American Cancer Society, Atlanta, GA 30303, USA.
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30
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Diet across the Lifespan and the Association with Breast Density in Adulthood. Int J Breast Cancer 2013; 2013:808317. [PMID: 23431461 PMCID: PMC3574651 DOI: 10.1155/2013/808317] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2012] [Accepted: 11/30/2012] [Indexed: 02/01/2023] Open
Abstract
Studies have shown inconsistent results regarding the association between dietary factors across the lifespan and breast density and breast cancer in women. Breast density is a strong risk factor for breast cancer, and the mechanism through which it influences cancer risk remains unclear. Breast density has been shown to be modifiable, potentially through dietary modifications. The goal of this paper is to summarize the current studies on diet and diet-related factors across all ages, determine which dietary factors show the strongest association with breast density, the most critical age of exposure, and identify future directions. We identified 28 studies, many of which are cross-sectional, and found that the strongest associations are among vitamin D, calcium, dietary fat, and alcohol in premenopausal women. Longitudinal studies with repeated dietary measures as well as the examination of overall diet over time are needed to confirm these findings.
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31
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Kricker A, Disipio T, Stone J, Goumas C, Armes JE, Gertig DM, Armstrong BK. Bodyweight and other correlates of symptom-detected breast cancers in a population offered screening. Cancer Causes Control 2011; 23:89-102. [PMID: 22020871 DOI: 10.1007/s10552-011-9858-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2011] [Accepted: 10/12/2011] [Indexed: 11/30/2022]
Abstract
OBJECTIVE To determine the factors associated with symptom-detected breast cancers in a population offered screening. METHODS We interviewed 1,459 Australian women aged 40-69, 946 with symptom-detected and 513 with mammogram-detected invasive breast cancers ≥ 1.1 cm in diameter about their personal, mammogram, and breast histories before diagnosis and reviewed medical records for tumor characteristics and mammogram dates, calculating ORs and 95% confidence intervals (CIs) for symptom- versus mammogram-detected cancers in logistic regression models. RESULTS Lack of regular mammograms (<2 mammograms in the 4.5 years before diagnosis) was the strongest correlate of symptom-detected breast cancer (OR = 3.04 for irregular or no mammograms). In women who had regular mammograms (≥ 2 mammograms in the 4.5 years before diagnosis), the independent correlates of symptom-detected cancers were low BMI (OR < 25 kg/m(2) vs. ≥ 30 kg/m(2) = 2.18, 95% CI 1.23-3.84; p = 0.008), increased breast density (available in 498 women) (OR highest quarter vs. lowest = 3.50, 95% CI 1.76-6.97; p (trend) = 0.004), high-grade cancer, and a larger cancer (each p < 0.01). In women who did not have regular mammograms, the independent correlates were age <50 years, a first cancer, and a ≥ 2-cm cancer. Smoking appeared to modify the association of symptom-detected cancer with low BMI (higher ORs for low BMI in current smokers) and estrogen receptor (ER) status (higher ORs for low BMI in ER cancers). CONCLUSION Women with low BMI may benefit from a tailored approach to breast cancer detection, particularly if they smoke.
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Affiliation(s)
- Anne Kricker
- Sydney School of Public Health, University of Sydney, QEII Building D02, Sydney, NSW 2006, Australia.
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32
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Alcohol, tobacco, and mammographic density: a population-based study. Breast Cancer Res Treat 2011; 129:135-47. [PMID: 21373874 DOI: 10.1007/s10549-011-1414-5] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2011] [Accepted: 02/13/2011] [Indexed: 10/18/2022]
Abstract
Mammographic density (MD), or the proportion of the breast with respect to its overall area that is composed of dense tissue, is a strong risk factor for breast cancer. Studies support a positive association of mammographic density and alcohol drinking. This was a cross-sectional multicenter study based on 3584 women, aged 45-68 years, recruited from seven screening centers within the Spanish breast cancer screening program network. The association between MD, alcohol consumption and tobacco use was evaluated by using ordinal logistic models with random center-specific intercepts. We found a weak positive association between current alcohol intake and higher MD, with current alcohol consumption increasing the odds of high MD by 13% (OR = 1.13; 95% CI 0.99-1.28) and high daily grams of alcohol being positively associated with increased MD (P for trend = 0.045). There were no statistically significant differences in MD between smokers and non-smokers. Nevertheless, increased number of daily cigarettes and increased number of accumulated lifetime cigarettes were negatively associated with high MD (P for trend 0.017 and 0.021). The effect of alcohol on MD was modified by menopausal status and tobacco smoking: whereas, alcohol consumption and daily grams of alcohol were positively associated with higher MD in postmenopausal women and in women who were not currently smoking, alcohol consumption had no effect on MD in premenopausal women and current smokers. Our results support an association between recent alcohol consumption and high MD, characterized by a modest increase in risk at low levels of current consumption and a decrease in risk among heavier drinkers. Our study also shows how the effects of alcohol in the breast can be modified by other factors, such as smoking.
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33
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Adams SV, Newcomb PA, Shafer MM, Atkinson C, Bowles EJA, Newton KM, Lampe JW. Urinary cadmium and mammographic density in premenopausal women. Breast Cancer Res Treat 2011; 128:837-44. [PMID: 21327468 DOI: 10.1007/s10549-011-1383-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2010] [Accepted: 02/01/2011] [Indexed: 12/17/2022]
Abstract
Mammographic density (MD), a strong marker of breast cancer risk, is influenced by genetic, environmental, and hormonal factors. Cadmium, a persistent and widespread environmental pollutant, has been associated with risk of breast cancer, and laboratory evidence suggests cadmium is a carcinogen in the breast. We investigated the hypothesis that cadmium exposure is associated with higher MD. In a cross-sectional study of MD and urinary cadmium concentration, percentage MD (MD%) and Breast Imaging-Reporting and Data Systems (BI-RADS®) density category were determined from screening mammograms of 190 premenopausal women ages 40-45 years. Women completed a health questionnaire, and the cadmium content of spot urine samples was measured with inductively coupled plasma mass spectrometry and corrected for urine creatinine. Urinary cadmium concentrations are thought to reflect exposure to cadmium during a period of 20-30 years. Multivariable linear regression and logistic regression were used to estimate the strength of association between urinary cadmium and mammographic breast density. Adjusted mean MD% among women in the upper tertile of creatinine-corrected urinary cadmium was 4.6% higher (95% CI: -2.3 to 11.6%) than in women in the lowest cadmium tertile. Each twofold increase in urinary cadmium was associated with higher odds of MD% in the upper tertile (OR: 1.29, 95% CI: 0.82-2.02) or a BI-RADS category rating of "extremely dense" (OR: 1.75, 95% CI: 1.14-2.70). Stronger associations were observed among nulliparous women, and current or former smokers. Exposure to cadmium may be associated with increased breast density in premenopausal women.
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Affiliation(s)
- Scott V Adams
- Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
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