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Wilby AJ, Cabral S, Zoghi N, Howell SJ, Farnie G, Harrison H. A novel preclinical model of the normal human breast. J Mammary Gland Biol Neoplasia 2024; 29:9. [PMID: 38695983 PMCID: PMC11065935 DOI: 10.1007/s10911-024-09562-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Accepted: 04/01/2024] [Indexed: 05/05/2024] Open
Abstract
Improved screening and treatment have decreased breast cancer mortality, although incidence continues to rise. Women at increased risk of breast cancer can be offered risk reducing treatments, such as tamoxifen, but this has not been shown to reduce breast cancer mortality. New, more efficacious, risk-reducing agents are needed. The identification of novel candidates for prevention is hampered by a lack of good preclinical models. Current patient derived in vitro and in vivo models cannot fully recapitulate the complexities of the human tissue, lacking human extracellular matrix, stroma, and immune cells, all of which are known to influence therapy response. Here we describe a normal breast explant model utilising a tuneable hydrogel which maintains epithelial proliferation, hormone receptor expression, and residency of T cells and macrophages over 7 days. Unlike other organotypic tissue cultures which are often limited by hyper-proliferation, loss of hormone signalling, and short treatment windows (< 48h), our model shows that tissue remains viable over 7 days with none of these early changes. This offers a powerful and unique opportunity to model the normal breast and study changes in response to various risk factors, such as breast density and hormone exposure. Further validation of the model, using samples from patients undergoing preventive therapies, will hopefully confirm this to be a valuable tool, allowing us to test novel agents for breast cancer risk reduction preclinically.
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Affiliation(s)
- Anthony J Wilby
- Division of Cancer Sciences, Manchester Cancer Research Centre, University of Manchester, Oglesby Cancer Research Building, Wilmslow Road, Manchester, M20 4GJ, United Kingdom
- Manchester Breast Centre, University of Manchester, Wilmslow Road, Manchester, M20 4GJ, United Kingdom
| | - Sara Cabral
- Division of Cancer Sciences, Manchester Cancer Research Centre, University of Manchester, Oglesby Cancer Research Building, Wilmslow Road, Manchester, M20 4GJ, United Kingdom
- Manchester Breast Centre, University of Manchester, Wilmslow Road, Manchester, M20 4GJ, United Kingdom
- Henry Royce Institute, University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
| | - Nastaran Zoghi
- Department of Materials & Institute of Biotechnology, University of Manchester, Manchester, M1 7DN, United Kingdom
| | - Sacha J Howell
- Division of Cancer Sciences, Manchester Cancer Research Centre, University of Manchester, Oglesby Cancer Research Building, Wilmslow Road, Manchester, M20 4GJ, United Kingdom
- Manchester Breast Centre, University of Manchester, Wilmslow Road, Manchester, M20 4GJ, United Kingdom
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, 29 Grafton St, Manchester, M13 9WU, United Kingdom
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, United Kingdom
| | - Gillian Farnie
- Cancer Research Horizons, The Francis Crick Institute, 1 Midland Road, Manchester, NW1 1AT, United Kingdom
| | - Hannah Harrison
- Division of Cancer Sciences, Manchester Cancer Research Centre, University of Manchester, Oglesby Cancer Research Building, Wilmslow Road, Manchester, M20 4GJ, United Kingdom.
- Manchester Breast Centre, University of Manchester, Wilmslow Road, Manchester, M20 4GJ, United Kingdom.
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2
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Zaluzec EK, Sempere LF. Systemic and Local Strategies for Primary Prevention of Breast Cancer. Cancers (Basel) 2024; 16:248. [PMID: 38254741 PMCID: PMC10814018 DOI: 10.3390/cancers16020248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 12/29/2023] [Accepted: 12/31/2023] [Indexed: 01/24/2024] Open
Abstract
One in eight women will develop breast cancer in the US. For women with moderate (15-20%) to average (12.5%) risk of breast cancer, there are few options available for risk reduction. For high-risk (>20%) women, such as BRCA mutation carriers, primary prevention strategies are limited to evidence-based surgical removal of breasts and/or ovaries and anti-estrogen treatment. Despite their effectiveness in risk reduction, not many high-risk individuals opt for surgical or hormonal interventions due to severe side effects and potentially life-changing outcomes as key deterrents. Thus, better communication about the benefits of existing strategies and the development of new strategies with minimal side effects are needed to offer women adequate risk-reducing interventions. We extensively review and discuss innovative investigational strategies for primary prevention. Most of these investigational strategies are at the pre-clinical stage, but some are already being evaluated in clinical trials and others are expected to lead to first-in-human clinical trials within 5 years. Likely, these strategies would be initially tested in high-risk individuals but may be applicable to lower-risk women, if shown to decrease risk at a similar rate to existing strategies, but with minimal side effects.
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Affiliation(s)
- Erin K. Zaluzec
- Precision Health Program, Michigan State University, East Lansing, MI 48824, USA;
- Department of Pharmacology & Toxicology, College of Veterinary Medicine, Michigan State University, East Lansing, MI 48824, USA
| | - Lorenzo F. Sempere
- Precision Health Program, Michigan State University, East Lansing, MI 48824, USA;
- Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI 48824, USA
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3
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Gareth Evans D, McWilliams L, Astley S, Brentnall AR, Cuzick J, Dobrashian R, Duffy SW, Gorman LS, Harkness EF, Harrison F, Harvie M, Jerrison A, Machin M, Maxwell AJ, Howell SJ, Wright SJ, Payne K, Qureshi N, Ruane H, Southworth J, Fox L, Bowers S, Hutchinson G, Thorpe E, Ulph F, Woof V, Howell A, French DP. Quantifying the effects of risk-stratified breast cancer screening when delivered in real time as routine practice versus usual screening: the BC-Predict non-randomised controlled study (NCT04359420). Br J Cancer 2023; 128:2063-2071. [PMID: 37005486 PMCID: PMC10066938 DOI: 10.1038/s41416-023-02250-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 02/28/2023] [Accepted: 03/20/2023] [Indexed: 04/04/2023] Open
Abstract
BACKGROUND Risk stratification as a routine part of the NHS Breast Screening Programme (NHSBSP) could provide a better balance of benefits and harms. We developed BC-Predict, to offer women when invited to the NHSBSP, which collects standard risk factor information; mammographic density; and in a sub-sample, a Polygenic Risk Score (PRS). METHODS Risk prediction was estimated primarily from self-reported questionnaires and mammographic density using the Tyrer-Cuzick risk model. Women eligible for NHSBSP were recruited. BC-Predict produced risk feedback letters, inviting women at high risk (≥8% 10-year) or moderate risk (≥5-<8% 10-year) to have appointments to discuss prevention and additional screening. RESULTS Overall uptake of BC-Predict in screening attendees was 16.9% with 2472 consenting to the study; 76.8% of those received risk feedback within the 8-week timeframe. Recruitment was 63.2% with an onsite recruiter and paper questionnaire compared to <10% with BC-Predict only (P < 0.0001). Risk appointment attendance was highest for those at high risk (40.6%); 77.5% of those opted for preventive medication. DISCUSSION We have shown that a real-time offer of breast cancer risk information (including both mammographic density and PRS) is feasible and can be delivered in reasonable time, although uptake requires personal contact. Preventive medication uptake in women newly identified at high risk is high and could improve the cost-effectiveness of risk stratification. TRIAL REGISTRATION Retrospectively registered with clinicaltrials.gov (NCT04359420).
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Affiliation(s)
- D Gareth Evans
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England.
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England.
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, 555 Wilmslow Road, Manchester, M20 4GJ, England.
- Genomic Medicine, Division of Evolution and Genomic Sciences, The University of Manchester, St Mary's Hospital, Manchester University NHS Foundation Trust, Oxford Road, Manchester, M13 9WL, England.
| | - Lorna McWilliams
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- Manchester Centre of Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, University of Manchester, Coupland Street, Manchester, M13 9PL, England
| | - Susan Astley
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Manchester, England
| | - Adam R Brentnall
- Centre for Prevention, Detection and Diagnosis, Wolfson Institute of Population Health, Queen Mary University of London, London, England
| | - Jack Cuzick
- Centre for Prevention, Detection and Diagnosis, Wolfson Institute of Population Health, Queen Mary University of London, London, England
| | - Richard Dobrashian
- East Lancashire Hospitals NHS Trust, Royal Blackburn Hospital, Haslingden Road, Lancashire, BB2 3HH, Manchester, England
| | - Stephen W Duffy
- Centre for Prevention, Detection and Diagnosis, Wolfson Institute of Population Health, Queen Mary University of London, London, England
| | - Louise S Gorman
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
- Manchester Centre of Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, University of Manchester, Coupland Street, Manchester, M13 9PL, England
- NIHR Greater Manchester Patient Safety Translational Research Centre, University of Manchester, Manchester, M13 9PL, England
| | - Elaine F Harkness
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, 555 Wilmslow Road, Manchester, M20 4GJ, England
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Manchester, England
| | | | - Michelle Harvie
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, 555 Wilmslow Road, Manchester, M20 4GJ, England
| | - Andrew Jerrison
- Research IT, IT Services, University of Manchester, Manchester, M13 9PL, England
| | - Matthew Machin
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Manchester, England
| | - Anthony J Maxwell
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, 555 Wilmslow Road, Manchester, M20 4GJ, England
| | - Sacha J Howell
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, 555 Wilmslow Road, Manchester, M20 4GJ, England
- Department of Medical Oncology, The Christie NHS Foundation Trust, Wilmslow Road, Manchester, M20 4BX, England
| | - Stuart J Wright
- Manchester Centre for Health Economics, Division of Population Health, Health Services Research & Primary Care, School of Health Sciences, University of Manchester, Manchester, M13 9PL, England
| | - Katherine Payne
- Manchester Centre for Health Economics, Division of Population Health, Health Services Research & Primary Care, School of Health Sciences, University of Manchester, Manchester, M13 9PL, England
| | - Nadeem Qureshi
- Primary Care Stratified Medicine research group, Centre for Academic Primary Care, University of Nottingham, University Park, Nottingham, NG7 2RD, England
| | - Helen Ruane
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
| | - Jake Southworth
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
| | - Lynne Fox
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
| | - Sarah Bowers
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
| | - Gillian Hutchinson
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
| | - Emma Thorpe
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
| | - Fiona Ulph
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- Manchester Centre of Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, University of Manchester, Coupland Street, Manchester, M13 9PL, England
| | - Victoria Woof
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- Manchester Centre of Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, University of Manchester, Coupland Street, Manchester, M13 9PL, England
| | - Anthony Howell
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, 555 Wilmslow Road, Manchester, M20 4GJ, England
- Department of Medical Oncology, The Christie NHS Foundation Trust, Wilmslow Road, Manchester, M20 4BX, England
| | - David P French
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- Manchester Centre of Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, University of Manchester, Coupland Street, Manchester, M13 9PL, England
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Lloyd R, Walter J, Pirikahu S, Cadby G, Hickey M, Sampson DD, Karnowski K, Hackmann MJ, Saunders C, Lilge L, Stone J. Assessment of repeated reference measurements to inform the validity of optical breast spectroscopy. THE REVIEW OF SCIENTIFIC INSTRUMENTS 2022; 93:044101. [PMID: 35489887 DOI: 10.1063/5.0072223] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Accepted: 03/07/2022] [Indexed: 06/14/2023]
Abstract
Mammographic breast density is a strong breast cancer risk factor, and its routine clinical measurement could potentially be used to identify women at higher risk of breast cancer and/or monitor primary prevention strategies. Previous reports of optical breast spectroscopy (OBS), a novel approach to measuring breast density, demonstrated that it is safe (no ionizing radiation), portable, low-cost, and does not require image interpretation but have been limited to small, single-center studies. Reference measurements taken on a phantom breast prior to and after each woman's OBS assessment are required for the calibration of the system transfer function as a part of processing participant data. To inform the validity of participant data, a detailed description of the reference measurements and a repeatability analysis of these measurements taken before and after participant assessment is presented. Reference measurements for OBS from 539 women aged 18-40 years were obtained as a part of a high-throughput epidemiological pilot study. Of these, measurements from 20 women with no useable data due to device failure (3.7%) were excluded and from another 12 women due to user error. The intra-class correlation (ICC) within complete pairs of reference data (taken before and after assessment) was high (all ICC > 0.84). The analysis presented here confirms the OBS participant data as valid for use in ongoing epidemiological research, providing further supporting evidence of OBS as a measure of breast density. A novel method of measuring breast density is needed to bridge large gaps in the knowledge of breast density in younger women and its relation to later-life breast cancer risk.
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Affiliation(s)
- Rachel Lloyd
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Crawley, Western Australia 6009, Australia
| | - Jane Walter
- University Health Network, Toronto, Ontario M5G 2M9, Canada
| | - Sarah Pirikahu
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Crawley, Western Australia 6009, Australia
| | - Gemma Cadby
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Crawley, Western Australia 6009, Australia
| | - Martha Hickey
- Department of Obstetrics and Gynaecology, University of Melbourne and the Royal Women's Hospital, Melbourne, Victoria 3052, Australia
| | - David D Sampson
- Surry Biophotonics, Advanced Technology Institute and School of Biosciences and Medicine, The University of Surrey, Guildford, Surrey GU2 7XH, United Kingdom
| | - Karol Karnowski
- Optical and Biomedical Engineering Laboratory School of Electrical, Electronic and Computer Engineering, The University of Western Australia, Crawley, Western Australia 6009, Australia
| | - Michael J Hackmann
- Optical and Biomedical Engineering Laboratory School of Electrical, Electronic and Computer Engineering, The University of Western Australia, Crawley, Western Australia 6009, Australia
| | - Christobel Saunders
- Medical School, The University of Western Australia, Crawley, Western Australia 6009, Australia
| | - Lothar Lilge
- University Health Network, Toronto, Ontario M5G 2M9, Canada
| | - Jennifer Stone
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Crawley, Western Australia 6009, Australia
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Clift AK, Dodwell D, Lord S, Petrou S, Brady SM, Collins GS, Hippisley-Cox J. The current status of risk-stratified breast screening. Br J Cancer 2022; 126:533-550. [PMID: 34703006 PMCID: PMC8854575 DOI: 10.1038/s41416-021-01550-3] [Citation(s) in RCA: 61] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 08/25/2021] [Accepted: 09/14/2021] [Indexed: 12/23/2022] Open
Abstract
Apart from high-risk scenarios such as the presence of highly penetrant genetic mutations, breast screening typically comprises mammography or tomosynthesis strategies defined by age. However, age-based screening ignores the range of breast cancer risks that individual women may possess and is antithetical to the ambitions of personalised early detection. Whilst screening mammography reduces breast cancer mortality, this is at the risk of potentially significant harms including overdiagnosis with overtreatment, and psychological morbidity associated with false positives. In risk-stratified screening, individualised risk assessment may inform screening intensity/interval, starting age, imaging modality used, or even decisions not to screen. However, clear evidence for its benefits and harms needs to be established. In this scoping review, the authors summarise the established and emerging evidence regarding several critical dependencies for successful risk-stratified breast screening: risk prediction model performance, epidemiological studies, retrospective clinical evaluations, health economic evaluations and qualitative research on feasibility and acceptability. Family history, breast density or reproductive factors are not on their own suitable for precisely estimating risk and risk prediction models increasingly incorporate combinations of demographic, clinical, genetic and imaging-related parameters. Clinical evaluations of risk-stratified screening are currently limited. Epidemiological evidence is sparse, and randomised trials only began in recent years.
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Affiliation(s)
- Ash Kieran Clift
- Cancer Research UK Oxford Centre, Department of Oncology, University of Oxford, Oxford, UK.
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
| | - David Dodwell
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Simon Lord
- Department of Oncology, University of Oxford, Oxford, UK
| | - Stavros Petrou
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | | | - Gary S Collins
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology & Musculoskeletal Sciences, University of Oxford, Oxford, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford, UK
| | - Julia Hippisley-Cox
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
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Bao Z, Zhao Y, Chen S, Chen X, Xu X, Wei L, Chen L. Evidence and assessment of parenchymal patterns of ultrasonography for breast cancer detection among Chinese women: a cross-sectional study. BMC Med Imaging 2021; 21:152. [PMID: 34666701 PMCID: PMC8527662 DOI: 10.1186/s12880-021-00687-0] [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: 06/05/2021] [Accepted: 09/23/2021] [Indexed: 11/17/2022] Open
Abstract
Background Screening of breast cancer in asymptomatic women is important to evaluate for early diagnosis. In China ultrasound is a more frequently used method than mammography for the detection of breast cancer. The objectives of the study were to provide evidence and assessment of parenchymal patterns of ultrasonography for breast cancer detection among Chinese women. Methods Breast ultrasound examinations including the parenchymatous pattern of cytopathological confirmed breast cancer (n = 541) and age-matched cytopathological not confirmed breast cancer (n = 849) women were retrospectively reviewed by seven sonographer physicians. According to compositions of ducts, the thickness of the breast, diameter of ducts, fat lobules, and fibro glandular tissues, the breast parenchymatous pattern was categorized into heterogeneous (high percentage of fatty tissues), ductal (the inner diameters of ducts > 50% of the thick mass of the breast), mixed (the inner diameters of ducts was 50% of the thick mass of the breast), and fibrous categories (a dense classification of the breast). Results Heterogeneous (p < 0.0001, OR = 3.972) and fibrous categories (p < 0.0001, OR = 2.702) were higher among women who have cytopathological confirmed breast cancer than those who have not cytopathological confirmed breast cancer. The heterogeneous category was high-risk ultrasonographic examination category followed by the fibrous category. Agreements between sonographer physicians for categories of ultrasonic examinations were fair to good (Cohen’s k = 0.591). Conclusions Breast cancer risk in Chinese asymptomatic women differ according to the ultrasonographic breast parenchymal pattern. Level of Evidence: III. Technical efficacy stage: 2.
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Affiliation(s)
- Zhongtao Bao
- Department of Ultrasound, First Affiliated Hospital of Fujian Medical University, No 20 Cha zhong Road, Taijiang District, Fuzhou, 350000, Fujian, China.
| | - Yanchun Zhao
- Department of Ultrasound, Provincial Clinical Academy of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, 350001, Fujian, China
| | - Shuqiang Chen
- Department of Ultrasound, First Affiliated Hospital of Fujian Medical University, No 20 Cha zhong Road, Taijiang District, Fuzhou, 350000, Fujian, China
| | - Xiaoyu Chen
- Department of Ultrasound, First Affiliated Hospital of Fujian Medical University, No 20 Cha zhong Road, Taijiang District, Fuzhou, 350000, Fujian, China
| | - Xiang Xu
- Department of Ultrasound, First Affiliated Hospital of Fujian Medical University, No 20 Cha zhong Road, Taijiang District, Fuzhou, 350000, Fujian, China
| | - Linglin Wei
- Department of Ultrasound, First Affiliated Hospital of Fujian Medical University, No 20 Cha zhong Road, Taijiang District, Fuzhou, 350000, Fujian, China
| | - Ling Chen
- Department of Ultrasound, First Affiliated Hospital of Fujian Medical University, No 20 Cha zhong Road, Taijiang District, Fuzhou, 350000, Fujian, China
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7
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Burnside ES, Warren LM, Myles J, Wilkinson LS, Wallis MG, Patel M, Smith RA, Young KC, Massat NJ, Duffy SW. Quantitative breast density analysis to predict interval and node-positive cancers in pursuit of improved screening protocols: a case-control study. Br J Cancer 2021; 125:884-892. [PMID: 34168297 PMCID: PMC8438060 DOI: 10.1038/s41416-021-01466-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Revised: 05/18/2021] [Accepted: 06/10/2021] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND This study investigates whether quantitative breast density (BD) serves as an imaging biomarker for more intensive breast cancer screening by predicting interval, and node-positive cancers. METHODS This case-control study of 1204 women aged 47-73 includes 599 cancer cases (302 screen-detected, 297 interval; 239 node-positive, 360 node-negative) and 605 controls. Automated BD software calculated fibroglandular volume (FGV), volumetric breast density (VBD) and density grade (DG). A radiologist assessed BD using a visual analogue scale (VAS) from 0 to 100. Logistic regression and area under the receiver operating characteristic curves (AUC) determined whether BD could predict mode of detection (screen-detected or interval); node-negative cancers; node-positive cancers, and all cancers vs. controls. RESULTS FGV, VBD, VAS, and DG all discriminated interval cancers (all p < 0.01) from controls. Only FGV-quartile discriminated screen-detected cancers (p < 0.01). Based on AUC, FGV discriminated all cancer types better than VBD or VAS. FGV showed a significantly greater discrimination of interval cancers, AUC = 0.65, than of screen-detected cancers, AUC = 0.61 (p < 0.01) as did VBD (0.63 and 0.53, respectively, p < 0.001). CONCLUSION FGV, VBD, VAS and DG discriminate interval cancers from controls, reflecting some masking risk. Only FGV discriminates screen-detected cancers perhaps adding a unique component of breast cancer risk.
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Affiliation(s)
- Elizabeth S Burnside
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, E3/311 Clinical Science Center, Madison, WI, USA.
| | - Lucy M Warren
- National Co-ordinating Centre for the Physics of Mammography (NCCPM), Medical Physics Department, Royal Surrey County Hospital, Guildford, UK
| | - Jonathan Myles
- Centre for Cancer Prevention, Queen Mary University of London, Wolfson Institute of Preventive Medicine, London, UK
| | | | - Matthew G Wallis
- Cambridge Breast Unit and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Trust, Cambridge, UK
| | - Mishal Patel
- Scientific Computing, Medical Physics Department, Royal Surrey County Hospital, Guildford, UK
| | | | - Kenneth C Young
- National Co-ordinating Centre for the Physics of Mammography (NCCPM), Medical Physics Department, Royal Surrey County Hospital, Guildford, UK
| | - Nathalie J Massat
- Centre for Cancer Prevention, Queen Mary University of London, Wolfson Institute of Preventive Medicine, London, UK
| | - Stephen W Duffy
- Centre for Cancer Prevention, Queen Mary University of London, Wolfson Institute of Preventive Medicine, London, UK
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8
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Toward a Population-Based Breast Cancer Risk Stratification Approach? The Needs and Concerns of Healthcare Providers. J Pers Med 2021; 11:jpm11060540. [PMID: 34200634 PMCID: PMC8228184 DOI: 10.3390/jpm11060540] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 06/03/2021] [Accepted: 06/05/2021] [Indexed: 12/15/2022] Open
Abstract
Given the expanding knowledge base in cancer genomics, risk-based screening is among the promising avenues to improve breast cancer (BC) prevention and early detection at the population level. Semi-structured interviews were conducted to explore the perceptions of healthcare professionals (HPs) regarding the implementation of such an approach and identify tools that can support HPs. After undertaking an in-depth thematic content analysis of the responses, 11 themes were identified. These were embedded into a logical model to distinguish the potential eligible participants (who?), the main clinical activities (how?) and associated tools (what?), the key factors of acceptability (which?), and the expected effects of the strategy (why?). Overall, it was found that the respondents positively welcomed the implementation of this strategy and agreed on some of the benefits that could accrue to women from tailored risk-based screening. Some important elements, however, deserve clarification. The results also highlight three main conditions that should be met to foster the acceptability of BC risk stratification: respecting the principle of equity, paying special attention to knowledge management, and rethinking human resources to capitalize on the strengths of the current workforce. Because the functioning of BC risk-based screening is not yet well defined, important planning work is required before advancing this organizational innovation, and outstanding issues must be resolved to get HPs on board.
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9
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Sartor H, Brandt J, Grassmann F, Eriksson M, Czene K, Melander O, Zackrisson S. The association of single nucleotide polymorphisms (SNPs) with breast density and breast cancer survival: the Malmö Diet and Cancer Study. Acta Radiol 2020; 61:1326-1334. [PMID: 32036684 PMCID: PMC7564305 DOI: 10.1177/0284185119900436] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Background Genetic factors are important in determining breast density, and heritable factors account for 60% of the variation. Certain single nucleotide polymorphisms (SNPs) are associated with density and risk of breast cancer but the association with prognosis is not clear. Purpose To investigate associations between selected SNPs and breast cancer survival in the Malmö Diet and Cancer Study (MDCS). Material and Methods A total of 724 unrelated women with breast cancer and registered radiological and pathological data were identified in MDCS 1991–2007, with genotyping available for 672 women. Associations among 15 SNPs, density, and breast cancer-specific survival were analyzed using logistic/Cox regression, adjusted for factors affecting density and survival. Variants significantly associated with either density or survival were validated in a large independent breast cancer cohort (LIBRO-1). Results Minor homozygotes of SNPs rs9383589, CCDC170 and rs6557161, ESR1 were associated with high breast density (adjusted odds ratio [AOR] 8.97, 95% confidence interval [CI] 1.35–59.57; AOR 2.08, 95% CI 1.19–3.65, respectively) and poorer breast cancer survival (adjusted hazard ratio [HRadj] 6.46, 95% CI 1.95–21.39; HRadj 2.30, 95% CI 1.33–3.96, respectively) compared to major homozygotes. For SNP rs3757318, ESR1, minor homozygotes (HRadj 7.46, 95% CI 2.28–24.45) were associated with poorer survival. We confirmed that rs6557161, ESR1 was significantly associated with both density and survival in the LIBRO-1 study. Conclusion These findings support a shared genetic basis for density and breast cancer survival. The SNP significantly associated with both density and survival in both cohorts may be of interest in future research investigating polygenic risk scores for breast cancer risk and screening stratification purposes.
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Affiliation(s)
- Hanna Sartor
- Diagnostic Radiology, Department of Translational Medicine, Skåne University Hospital, Lund University, Lund, Sweden
| | - Jasmine Brandt
- Department of Surgery, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Felix Grassmann
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Olle Melander
- Hypertension and Cardiovascular Disease, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Sophia Zackrisson
- Diagnostic Radiology, Department of Translational Medicine, Skåne University Hospital, Lund University, Lund, Sweden
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Saya S, Emery JD, Dowty JG, McIntosh JG, Winship IM, Jenkins MA. The Impact of a Comprehensive Risk Prediction Model for Colorectal Cancer on a Population Screening Program. JNCI Cancer Spectr 2020; 4:pkaa062. [PMID: 33134836 PMCID: PMC7583148 DOI: 10.1093/jncics/pkaa062] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 06/17/2020] [Accepted: 07/01/2020] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND In many countries, population colorectal cancer (CRC) screening is based on age and family history, though more precise risk prediction could better target screening. We examined the impact of a CRC risk prediction model (incorporating age, sex, lifestyle, genomic, and family history factors) to target screening under several feasible screening scenarios. METHODS We estimated the model's predicted CRC risk distribution in the Australian population. Predicted CRC risks were categorized into screening recommendations under 3 proposed scenarios to compare with current recommendations: 1) highly tailored, 2) 3 risk categories, and 3) 4 sex-specific risk categories. Under each scenario, for 35- to 74-year-olds, we calculated the number of CRC screens by immunochemical fecal occult blood testing (iFOBT) and colonoscopy and the proportion of predicted CRCs over 10 years in each screening group. RESULTS Currently, 1.1% of 35- to 74-year-olds are recommended screening colonoscopy and 56.2% iFOBT, and 5.7% and 83.2% of CRCs over 10 years were predicted to occur in these groups, respectively. For the scenarios, 1) colonoscopy was recommended to 8.1% and iFOBT to 37.5%, with 36.1% and 50.1% of CRCs in each group; 2) colonoscopy was recommended to 2.4% and iFOBT to 56.0%, with 13.2% and 76.9% of cancers in each group; and 3) colonoscopy was recommended to 5.0% and iFOBT to 54.2%, with 24.5% and 66.5% of cancers in each group. CONCLUSIONS A highly tailored CRC screening scenario results in many fewer screens but more cancers in those unscreened. Category-based scenarios may provide a good balance between number of screens and cancers detected and are simpler to implement.
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Affiliation(s)
- Sibel Saya
- Department of General Practice and Centre for Cancer Research, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia
| | - Jon D Emery
- Department of General Practice and Centre for Cancer Research, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia
| | - James G Dowty
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia
| | - Jennifer G McIntosh
- Department of General Practice and Centre for Cancer Research, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia
| | - Ingrid M Winship
- Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Melbourne, Australia
- Department of Medicine, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia
| | - Mark A Jenkins
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia
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11
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French DP, Astley S, Brentnall AR, Cuzick J, Dobrashian R, Duffy SW, Gorman LS, Harkness EF, Harrison F, Harvie M, Howell A, Jerrison A, Machin M, Maxwell AJ, McWilliams L, Payne K, Qureshi N, Ruane H, Sampson S, Stavrinos P, Thorpe E, Ulph F, van Staa T, Woof V, Evans DG. What are the benefits and harms of risk stratified screening as part of the NHS breast screening Programme? Study protocol for a multi-site non-randomised comparison of BC-predict versus usual screening (NCT04359420). BMC Cancer 2020; 20:570. [PMID: 32552763 PMCID: PMC7302349 DOI: 10.1186/s12885-020-07054-2] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 06/09/2020] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND In principle, risk-stratification as a routine part of the NHS Breast Screening Programme (NHSBSP) should produce a better balance of benefits and harms. The main benefit is the offer of NICE-approved more frequent screening and/ or chemoprevention for women who are at increased risk, but are unaware of this. We have developed BC-Predict, to be offered to women when invited to NHSBSP which collects information on risk factors (self-reported information on family history and hormone-related factors via questionnaire; mammographic density; and in a sub-sample, Single Nucleotide Polymorphisms). BC-Predict produces risk feedback letters, inviting women at high risk (≥8% 10-year) or moderate risk (≥5 to < 8% 10-year) to have discussion of prevention and early detection options at Family History, Risk and Prevention Clinics. Despite the promise of systems such as BC-Predict, there are still too many uncertainties for a fully-powered definitive trial to be appropriate or ethical. The present research aims to identify these key uncertainties regarding the feasibility of integrating BC-Predict into the NHSBSP. Key objectives of the present research are to quantify important potential benefits and harms, and identify key drivers of the relative cost-effectiveness of embedding BC-Predict into NHSBSP. METHODS A non-randomised fully counterbalanced study design will be used, to include approximately equal numbers of women offered NHSBSP (n = 18,700) and BC-Predict (n = 18,700) from selected screening sites (n = 7). In the initial 8-month time period, women eligible for NHSBSP will be offered BC-Predict in four screening sites. Three screening sites will offer women usual NHSBSP. In the following 8-months the study sites offering usual NHSBSP switch to BC-Predict and vice versa. Key potential benefits including uptake of risk consultations, chemoprevention and additional screening will be obtained for both groups. Key potential harms such as increased anxiety will be obtained via self-report questionnaires, with embedded qualitative process analysis. A decision-analytic model-based cost-effectiveness analysis will identify the key uncertainties underpinning the relative cost-effectiveness of embedding BC-Predict into NHSBSP. DISCUSSION We will assess the feasibility of integrating BC-Predict into the NHSBSP, and identify the main uncertainties for a definitive evaluation of the clinical and cost-effectiveness of BC-Predict. TRIAL REGISTRATION Retrospectively registered with clinicaltrials.gov (NCT04359420).
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Affiliation(s)
- David P French
- Manchester Centre of Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, University of Manchester, Coupland Street, Manchester, M13 9PL, England.
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England.
| | - Susan Astley
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Manchester, England
| | - Adam R Brentnall
- Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, England
| | - Jack Cuzick
- Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, England
| | - Richard Dobrashian
- East Lancashire Hospitals NHS Trust, Royal Blackburn Hospital, Haslingden Road, Lancashire, BB2 3HH, England
| | - Stephen W Duffy
- Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, England
| | - Louise S Gorman
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
- NIHR Greater Manchester Patient Safety Translational Research Centre, University of Manchester, Manchester, M13 9PL, England
| | - Elaine F Harkness
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Manchester, England
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
| | | | - Michelle Harvie
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, 555 Wilmslow Rd, Manchester, M20 4GJ, England
| | - Anthony Howell
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, 555 Wilmslow Rd, Manchester, M20 4GJ, England
- Department of Medical Oncology, The Christie NHS Foundation Trust, Wilmslow Rd, Manchester, M20 4BX, England
| | - Andrew Jerrison
- Research IT, IT Services, University of Manchester, Manchester, M13 9PL, England
| | - Matthew Machin
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Manchester, England
| | - Anthony J Maxwell
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Manchester, England
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
| | - Lorna McWilliams
- Manchester Centre of Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, University of Manchester, Coupland Street, Manchester, M13 9PL, England
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
| | - Katherine Payne
- Division of Population Health, Health Services Research & Primary Care, School of Health Sciences, University of Manchester, Manchester, M13 9PL, England
| | - Nadeem Qureshi
- School of Medicine, University of Nottingham, University Park, Nottingham, NG7 2RD, England
| | - Helen Ruane
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
| | - Sarah Sampson
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
| | - Paula Stavrinos
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
| | - Emma Thorpe
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
| | - Fiona Ulph
- Manchester Centre of Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, University of Manchester, Coupland Street, Manchester, M13 9PL, England
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
| | - Tjeerd van Staa
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Manchester, England
| | - Victoria Woof
- Manchester Centre of Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, University of Manchester, Coupland Street, Manchester, M13 9PL, England
| | - D Gareth Evans
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, 555 Wilmslow Rd, Manchester, M20 4GJ, England
- Genomic Medicine, Division of Evolution and Genomic Sciences, The University of Manchester, St Mary's Hospital, Manchester University NHS Foundation Trust, Oxford Road, Manchester, M13 9WL, England
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12
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Renehan AG, Pegington M, Harvie MN, Sperrin M, Astley SM, Brentnall AR, Howell A, Cuzick J, Gareth Evans D. Young adulthood body mass index, adult weight gain and breast cancer risk: the PROCAS Study (United Kingdom). Br J Cancer 2020; 122:1552-1561. [PMID: 32203222 PMCID: PMC7217761 DOI: 10.1038/s41416-020-0807-9] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Revised: 01/15/2020] [Accepted: 03/03/2020] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND We tested the hypothesis that body mass index (BMI) aged 20 years modifies the association of adult weight gain and breast cancer risk. METHODS We recruited women (aged 47-73 years) into the PROCAS (Predicting Risk Of Cancer At Screening; Manchester, UK: 2009-2013) Study. In 47,042 women, we determined BMI at baseline and (by recall) at age 20 years, and derived weight changes. We estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for new breast cancer using Cox models and explored relationships between BMI aged 20 years, subsequent weight changes and breast cancer risk. RESULTS With median follow-up of 5.6 years, 1142 breast cancers (post-menopausal at entry: 829) occurred. Among post-menopausal women at entry, BMI aged 20 years was inversely associated [HR per SD: 0.87 (95% CI: 0.79-0.95)], while absolute weight gain was associated with breast cancer [HR per SD:1.23 (95% CI: 1.14-1.32)]. For post-menopausal women who had a recall BMI aged 20 years <23.4 kg/m2 (75th percentile), absolute weight gain was associated with breast cancer [HR per SD: 1.31 (95% CIs: 1.21-1.42)], but there were no associations for women with a recall BMI aged 20 years of >23.4 kg/m2 (Pinteraction values <0.05). CONCLUSIONS Adult weight gain increased post-menopausal breast cancer risk only among women who were <23.4 kg/m2 aged 20 years.
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Affiliation(s)
- Andrew G Renehan
- Manchester Cancer Research Centre and NIHR Manchester Biomedical Research Centre, Manchester, UK.
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.
| | - Mary Pegington
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Prevent Breast Cancer, Nightingale Breast Screening Centre, University Hospital of South Manchester, Manchester, UK
| | - Michelle N Harvie
- Prevent Breast Cancer, Nightingale Breast Screening Centre, University Hospital of South Manchester, Manchester, UK
| | - Matthew Sperrin
- MRC Health eResearch Centre (HeRC), Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Susan M Astley
- Centre for Imaging Science, Division of Informatics, Imaging and Data Science, Faculty of Biology, Medicine and Health, University of Manchester, Oxford Road, Manchester, UK
- The University of Manchester, Manchester Academic Health Science Centre, University Hospital of South Manchester, Manchester, UK
| | - Adam R Brentnall
- Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, UK
| | - Anthony Howell
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Prevent Breast Cancer, Nightingale Breast Screening Centre, University Hospital of South Manchester, Manchester, UK
| | - Jack Cuzick
- Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, UK
| | - D Gareth Evans
- Manchester Cancer Research Centre and NIHR Manchester Biomedical Research Centre, Manchester, UK
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Prevent Breast Cancer, Nightingale Breast Screening Centre, University Hospital of South Manchester, Manchester, UK
- Genomic Medicine, Manchester Academic Health Sciences Centre, University of Manchester and Central Manchester Foundation Trust, Manchester, UK
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Changes in breast density over serial mammograms: A case-control study. Eur J Radiol 2020; 127:108980. [PMID: 32320912 DOI: 10.1016/j.ejrad.2020.108980] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Revised: 02/28/2020] [Accepted: 03/26/2020] [Indexed: 11/23/2022]
Abstract
PURPOSE In addition to a breast density category, temporal changes in breast density have gained attention as a dynamic breast cancer risk marker. This case-control study aimed to investigate a potential change in breast density preceding tumor development and the relationship of this potential change to prognostic pathological tumor variables. METHOD A total of 51 consecutive, eligible-for-analyses, biopsy-proven breast cancers were diagnosed between 1 st of August and 31 st of December 2014 at Skåne University Hospital, Sweden. Mammogram data and patient- and tumor characteristics were retrieved retrospectively from medical charts. Breast density was quantitatively estimated using LIBRA (a free open source software package). The cases were matched for year of birth, number of screening rounds, and date for first and last mammograms with controls from the Malmö Breast Tomosynthesis Screening Trial in a 1:2 ratio, resulting in median time between mammograms of 4.5 (1.3-11.9) years for cases and 4.7 (1.4-11.1) years for controls, averaging approximately three screening rounds (1-6 rounds). RESULTS We detected a statistically significant difference in breast density change over time, with cases showing an increase in breast density (1.7 %) as compared to controls (-0.3 %) (p = 0.045). We found that in women with breast cancer, older women (≥ 55 years) experienced a higher breast density increase compared to younger women (5.1 % vs. 0.3 %, p = 0.002). CONCLUSIONS There was a statistically significant difference in density change, where women with breast cancer showed an increased density over time, which was particularly evident in women > 55 years of age.
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Fowler EE, Smallwood A, Khan N, Miltich C, Drukteinis J, Sellers TA, Heine J. Calibrated Breast Density Measurements. Acad Radiol 2019; 26:1181-1190. [PMID: 30545682 PMCID: PMC6557684 DOI: 10.1016/j.acra.2018.10.009] [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: 06/07/2018] [Revised: 09/28/2018] [Accepted: 10/04/2018] [Indexed: 11/20/2022]
Abstract
RATIONALE AND OBJECTIVES Mammographic density is an important risk factor for breast cancer, but translation to the clinic requires assurance that prior work based on mammography is applicable to current technologies. The purpose of this work is to evaluate whether a calibration methodology developed previously produces breast density metrics predictive of breast cancer risk when applied to a case-control study. MATERIALS AND METHODS A matched case control study (n = 319 pairs) was used to evaluate two calibrated measures of breast density. Two-dimensional mammograms were acquired from six Hologic mammography units: three conventional Selenia two-dimensional full-field digital mammography systems and three Dimensions digital breast tomosynthesis systems. We evaluated the capability of two calibrated breast density measures to quantify breast cancer risk: the mean (PGm) and standard deviation (PGsd) of the calibrated pixels. Matching variables included age, hormone replacement therapy usage/duration, screening history, and mammography unit. Calibrated measures were compared to the percentage of breast density (PD) determined with the operator-assisted Cumulus method. Conditional logistic regression was used to generate odds ratios (ORs) from continuous and quartile (Q) models with 95% confidence intervals. The area under the receiver operating characteristic curve (Az) was also used as a comparison metric. Both univariate models and models adjusted for body mass index and ethnicity were evaluated. RESULTS In adjusted models, both PGsd and PD were statistically significantly associated with breast cancer with similar Az of 0.61-0.62. The corresponding ORs and confidence intervals were also similar. For PGsd, the OR was 1.34 (1.09, 1.66) for the continuous measure and 1.83 (1.11, 3.02), 2.19 (1.28, 3.73), and 2.20 (1.26, 3.85) for Q2-Q4. For PD, the OR was 1.43 (1.16, 1.76) for the continuous measure and 0.84 (0.52, 1.38), 1.96 (1.19, 3.23), and 2.27 (1.29, 4.00) for Q2-Q4. The results for PGm were slightly attenuated and not statistically significant. The OR was 1.22 (0.99, 1.51) with Az = 0.60 for the continuous measure and 1.24 (0.78, 1.97), 0.98 (0.60, 1.61), and 1.26, (0.77, 2.07) for Q2-Q4 with Az = 0.60. CONCLUSION The calibrated PGsd measure provided significant associations with breast cancer comparable to those given by PD. The calibrated PGm performed slightly worse. These findings indicate that the calibration approach developed previously replicates under more general conditions.
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Affiliation(s)
| | | | | | | | - Jennifer Drukteinis
- Moffitt Cancer Center & Research Institute, 12901 Bruce B. Downs Blvd, Tampa FL, 33612 (MCC)
| | | | - John Heine
- Corresponding Author information: John Heine, PhD, Moffitt Cancer Center & Research Institute, 12901 Bruce B, Downs Blvd, Mail Stop: Can/Cont, Tampa, FL 33612, Phone: 813-745-6719
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15
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Darcey E, Ambati R, Lund H, Redfern A, Saunders C, Thompson S, Wylie E, Stone J. Measuring height and weight as part of routine mammographic screening for breast cancer. J Med Screen 2019; 26:204-211. [PMID: 31288600 DOI: 10.1177/0969141319860873] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Objectives Body mass index is a strong predictor of post-menopausal breast cancer risk and (negatively) confounds the association between mammographic breast density and breast cancer risk; however, height and weight are not typically measured as part of routine mammographic screening. This study piloted voluntary height and weight measurement within the BreastScreen Western Australia (WA) programme, and assessed trial participation. Methods From February 2016 to January 2018, 204,429 women attending BreastScreen WA were invited to have their height and weight measured and recorded as part of their routine screening mammogram. Descriptive data analysis was used to assess pilot participation rates by available screening data. Results Of the 204,429 patients who attended BreastScreen WA during the pilot, 76.35% (156,072) agreed to have their height and weight measured. Pilot participation rates were significantly lower in those patients with disabilities (RR: 0.626; 95% CI: 0.600, 0.653), those who spoke a language other than English at home (RR: 0.876; 95% CI: 0.867, 0.885), and those who identified as Aboriginal and Torres Strait Islander (RR: 0.829; 95% CI: 0.807, 0.852). Pilot participation decreased over time from 88.9% in the first three months to 55.5% in the last month, due to lessening of support from BreastScreen staff. Conclusion Measuring height and weight at the time of routine mammographic screening is feasible, although logistical issues, particularly the added time/effort required of support staff, should be considered. BreastScreen WA has since decided to collect voluntary self-reported height and weight data as routine screening policy.
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Affiliation(s)
- Ellie Darcey
- Centre for Genetic Origins of Health and Disease, School of Biomedical Science, Curtin University and The University of Western Australia, Perth, Australia
| | | | - Helen Lund
- BreastScreen Western Australia, Women and Newborn Health Service, Perth, Australia
| | - Andrew Redfern
- Medical School, The University of Western Australia, Perth, Australia.,Fiona Stanley Hospital, Murdoch, Australia
| | - Christobel Saunders
- Medical School, The University of Western Australia, Perth, Australia.,Fiona Stanley Hospital, Murdoch, Australia
| | - Sandra Thompson
- Western Australian Centre for Rural Health, School of Population and Global Health, The University of Western Australia, Geraldton, Australia
| | - Elizabeth Wylie
- BreastScreen Western Australia, Women and Newborn Health Service, Perth, Australia.,Medical School, The University of Western Australia, Perth, Australia
| | - Jennifer Stone
- Centre for Genetic Origins of Health and Disease, School of Biomedical Science, Curtin University and The University of Western Australia, Perth, Australia
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Sinclair J, McCann M, Sheldon E, Gordon I, Brierley-Jones L, Copson E. The acceptability of addressing alcohol consumption as a modifiable risk factor for breast cancer: a mixed method study within breast screening services and symptomatic breast clinics. BMJ Open 2019; 9:e027371. [PMID: 31209091 PMCID: PMC6609127 DOI: 10.1136/bmjopen-2018-027371] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
OBJECTIVES Potentially modifiable risk factors account for approximately 23% of breast cancers, with obesity and alcohol being the two greatest. Breast screening and symptomatic clinical attendances provide opportunities ('teachable moments') to link health promotion and breast cancer-prevention advice within established clinical pathways. This study explored knowledge and attitudes towards alcohol as a risk factor for breast cancer, and potential challenges inherent in incorporating advice about alcohol health risks into breast clinics and screening appointments. DESIGN A mixed-method study including a survey on risk factors for breast cancer and understanding of alcohol content. Survey results were explored in a series of five focus groups with women and eight semi-structured interviews with health professionals. SETTING Women attending NHS Breast Screening Programme (NHSBSP) mammograms, symptomatic breast clinics and healthcare professionals in those settings. PARTICIPANTS 205 women were recruited (102 NHSBSP attenders and 103 symptomatic breast clinic attenders) and 33 NHS Staff. RESULTS Alcohol was identified as a breast cancer risk factor by 40/205 (19.5%) of attenders and 16/33 (48.5%) of staff. Overall 66.5% of attenders drank alcohol, and 56.6% could not estimate correctly the alcohol content of any of four commonly consumed alcoholic drinks. All women agreed that including a prevention-focussed intervention would not reduce the likelihood of their attendance at screening mammograms or breast clinics. Qualitative data highlighted concerns in both women and staff of how to talk about alcohol and risk factors for breast cancer in a non-stigmatising way, as well as ambivalence from specialist staff as to their role in health promotion. CONCLUSIONS Levels of alcohol health literacy and numeracy were low. Adding prevention interventions to screening and/or symptomatic clinics appears acceptable to attendees, highlighting the potential for using these opportunities as 'teachable moments'. However, there are substantial cultural and systemic challenges to overcome if this is to be implemented successfully.
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Affiliation(s)
- Julia Sinclair
- Clinical and Experimental Sciences Academic Unit, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Mark McCann
- MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK
| | - Ellena Sheldon
- Core Trainee in Psychiatry, Peninsula Postgraduate Medical Education, Plymouth, UK
| | - Isabel Gordon
- Department of Pharmacy Health and Well-being, University of Sunderland, Sunderland, UK
| | - Lyn Brierley-Jones
- Department of Sociology, University of York, Wentworth College, York, UK
| | - Ellen Copson
- Cancer Sciences Academic Unit, Faculty of Medicine, University of Southampton, Southampton, UK
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17
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Chambers SE, Copson ER, Dutey-Magni PF, Priest C, Anderson AS, Sinclair JMA. Alcohol use and breast cancer risk: A qualitative study of women's perspectives to inform the development of a preventative intervention in breast clinics. Eur J Cancer Care (Engl) 2019; 28:e13075. [PMID: 31038252 PMCID: PMC6767031 DOI: 10.1111/ecc.13075] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2018] [Revised: 02/18/2019] [Accepted: 03/25/2019] [Indexed: 12/29/2022]
Abstract
Objective This study aimed to explore women's views about breast cancer risk and alcohol use, to inform the design of a prototype for an intervention in breast clinics about alcohol as a modifiable risk factor for breast cancer. Methods Women recruited in NHS breast screening and symptomatic clinics in Southampton, UK, were invited to take part in semi‐structured telephone interviews or a focus group to discuss their perspectives of breast cancer risk, alcohol consumption and their information needs about these topics. Data were analysed thematically. Twenty‐eight women took part in telephone interviews, and 16 attended one of three focus groups. Results While most women reported a personal responsibility for their health and were interested in advice about modifiable risk factors, few without (or prior to) experience of breast symptoms independently sought information. Many considered alcohol advice irrelevant as the association with breast cancer was largely unknown, and participants did not consider their drinking to be problematic. Women reported trusting information from health organisations like the NHS, but advice needs to be sensitive and non‐blaming. Conclusion NHS breast screening and symptomatic clinics offer a “teachable moment” to engage women with context‐specific advice about alcohol and cancer risk that, if targeted correctly, may assist them in making informed lifestyle choices.
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Affiliation(s)
- Sophia E Chambers
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Ellen R Copson
- Cancer Sciences, Faculty of Medicine, University of Southampton and University Hospital Southampton, Southampton, UK
| | - Peter F Dutey-Magni
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK.,Institute of Health Informatics, University College London, London, UK
| | - Caspian Priest
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Annie S Anderson
- Centre for Research into Cancer Prevention and Screening, Ninewells Hospital & Medical School, University of Dundee, Dundee, UK
| | - Julia M A Sinclair
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
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18
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Lippey J, Keogh LA, Mann GB, Campbell IG, Forrest LE. "A Natural Progression": Australian Women's Attitudes About an Individualized Breast Screening Model. Cancer Prev Res (Phila) 2019; 12:383-390. [PMID: 31003994 DOI: 10.1158/1940-6207.capr-18-0443] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2018] [Revised: 03/01/2019] [Accepted: 04/09/2019] [Indexed: 11/16/2022]
Abstract
Individualized screening is our logical next step to improve population breast cancer screening in Australia. To explore breast screening participants' views of the current program in Victoria, Australia, examine their openness to change, and attitudes toward an individualized screening model, this qualitative work was performed from a population-based breast screening cohort. This work was designed to inform the development of a decision aid to facilitate women's decisions about participating in individualized screening, and to elicit Australian consumer perspectives on the international movement toward individualized breast screening. A total of 52 women participated in one of four focus groups, and were experienced with screening with 90% of participants having had more than three mammograms. Focus group discussion was facilitated following three main themes: (i) experience of breast screening; (ii) breast cancer risk perception, and (iii) views on individualized screening. Participants had strong, positive, emotional ties to breast screening in its current structure but were supportive, with some reservations, of the idea of individualized screening. There was good understanding about the factors contributing to personalized risk and a wide range of opinions about the inclusion of genetic testing with genetic testing being considered a foreign and evolving domain. Individualized breast screening that takes account of risk factors such as mammographic density, lifestyle, and genetic factors would be acceptable to a population of women who are invested in the current system. The communication and implementation of a new program would be critical to its acceptance and potential success. Reservations may be had in regards to uptake of genetic testing, motivations behind the change, and management of the women allocated to a lower risk category.
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Affiliation(s)
- Jocelyn Lippey
- Department of Surgery, University of Melbourne, Melbourne, Australia. .,St. Vincent's Hospital, Victoria, Australia
| | - Louise A Keogh
- Melbourne School of Population and Global Health, University of Melbourne, Carlton, Australia
| | - G Bruce Mann
- Department of Surgery, University of Melbourne, Melbourne, Australia.,Royal Melbourne Hospital, Victoria, Australia
| | - Ian G Campbell
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Australia.,Cancer Genetics Laboratory, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Laura E Forrest
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Australia.,Parkville Familial Cancer Centre, Peter MacCallum Cancer Centre, Melbourne, Australia
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19
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Fung SM, Wong XY, Lee SX, Miao H, Hartman M, Wee HL. Performance of Single-Nucleotide Polymorphisms in Breast Cancer Risk Prediction Models: A Systematic Review and Meta-analysis. Cancer Epidemiol Biomarkers Prev 2018; 28:506-521. [DOI: 10.1158/1055-9965.epi-18-0810] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Revised: 10/30/2018] [Accepted: 12/03/2018] [Indexed: 11/16/2022] Open
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20
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Stone J. Should breast cancer screening programs routinely measure mammographic density? J Med Imaging Radiat Oncol 2018; 62:151-158. [DOI: 10.1111/1754-9485.12652] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Accepted: 08/05/2017] [Indexed: 11/29/2022]
Affiliation(s)
- Jennifer Stone
- Centre for Genetic Origins of Health and Disease; Curtin University and The University of Western Australia; Perth Western Australia Australia
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21
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Blouin-Bougie J, Amara N, Bouchard K, Simard J, Dorval M. Disentangling the determinants of interest and willingness-to-pay for breast cancer susceptibility testing in the general population: a cross-sectional Web-based survey among women of Québec (Canada). BMJ Open 2018; 8:e016662. [PMID: 29487071 PMCID: PMC5855474 DOI: 10.1136/bmjopen-2017-016662] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
OBJECTIVES To identify common and specific individual factors that favour or impede women's interest in and willingness-to-pay (WTP) for breast cancer susceptibility testing (BCST) and to identify the most impactful factors on both outcome measures. DESIGN AND METHODS This study used a self-administered cross-sectional Web-based questionnaire that included hypothetical scenarios about the availability of a new genetic test for breast cancer. PARTICIPANTS French-speaking women of the general population of Québec (Canada), aged between 35 and 69 years, were identified from a Web-based panel (2410 met the selection criteria, 1160 were reached and 1031 completed the survey). MEASURES The outcomes are the level of interest in and the range of WTP for BCST. Three categories of individual factors identified in the literature were used as potential explanatory factors, that is, demographic, clinical and psychosocial. RESULTS Descriptive statistics indicated that the vast majority of sampled women are interested in BCST (90%). Among those, more than half of them are willing-to-pay for such a test (57%). The regression models pointed out several factors associated with both outcomes (eg, age, income, family history, locus of control-powerful others) and marginal effects were used to highlight the most impactful factors for each outcome. CONCLUSION The results of this study provide a proxy of the readiness of women of the general population to use and to pay for BCST. They also offer insights for developing inclusive and specific strategies to foster informed decision-making and guide the services offered by health organisations corresponding to women's preferences and needs.
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Affiliation(s)
| | - Nabil Amara
- Department of Management, Université Laval, Québec, QC, Canada
| | - Karine Bouchard
- Centre des maladies du sein Deschênes-Fabia, Centre de recherche du CHU de Québec-Université Laval, Hôpital du Saint-Sacrement, Québec, QC, Canada
| | - Jacques Simard
- Faculty of Medicine, Centre de recherche du CHU de Québec-Université Laval, Québec, QC, Canada
| | - Michel Dorval
- Faculty of Pharmacy, Centre de recherche du CHU de Québec-Université Laval, Hôpital du Saint-Sacrement, Québec, QC, Canada
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22
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McLean KE, Stone J. Role of breast density measurement in screening for breast cancer. Climacteric 2018; 21:214-220. [DOI: 10.1080/13697137.2018.1424816] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Affiliation(s)
- K. E. McLean
- Centre for Genetic Origins of Health and Disease, Curtin University and The University of Western Australia, Perth, WA, Australia
| | - J. Stone
- Centre for Genetic Origins of Health and Disease, Curtin University and The University of Western Australia, Perth, WA, Australia
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23
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Noonan S, Pasa A, Fontana V, Caviglia S, Bonanni B, Costa A, Smith SG, Peccatori F, DeCensi A. A Survey among Breast Cancer Specialists on the Low Uptake of Therapeutic Prevention with Tamoxifen or Raloxifene. Cancer Prev Res (Phila) 2018; 11:38-43. [PMID: 29061559 DOI: 10.1158/1940-6207.capr-17-0162] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2017] [Revised: 08/03/2017] [Accepted: 10/12/2017] [Indexed: 11/16/2022]
Abstract
With this survey, we aimed to address the reasons why physicians are reluctant to prescribe breast cancer-preventive therapy with the selective estrogen receptor modulators (SERM) tamoxifen or raloxifene despite a strong evidence of efficacy. A self-administered 5-point Likert questionnaire was given during breast cancer meetings in Europe or sent via email to rank the importance of 10 predefined reasons for low uptake of SERMs for breast cancer therapeutic prevention. Analyses tested the associations between the stated reasons and physician characteristics such as gender, age, country of work, and specialty. Of 246 delivered questionnaires, 27 were incomplete and were excluded from analysis. Overall, there was a small variability in response scores, with a tendency for physicians to give moderate importance (score = 3) to all 10 statements. However, the top five reasons were: the expected greater preventive effectiveness of aromatase inhibitors (70.3% with score >3), difficulty applying current risk models in clinical practice (69.9%), the lack of clarity on the most appropriate physician for prevention advice (68.4%), the lack of reliable short-term biomarkers of effectiveness (67.5%), and the lack of commercial interest in therapeutic prevention (66.0%). The lack of reliable short-term biomarkers showed a tendency to discriminate between medical oncologists and other breast specialists (OR = 2.42; 95% CI, 0.93-6.25). This survey highlights the complexity of prescribing decisions among physicians in this context. Coupled with the known barriers among eligible women, these data may help to identify strategies to increase uptake of breast cancer therapeutic prevention. Cancer Prev Res; 11(1); 38-43. ©2017 AACR.
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Affiliation(s)
- Silvia Noonan
- Medical Oncology, E.O. Ospedali Galliera, Genoa, Italy
| | - Ambra Pasa
- Medical Oncology, E.O. Ospedali Galliera, Genoa, Italy
| | - Vincenzo Fontana
- Clinical Epidemiology Unit, IRCCS AOU San Martino IST, Genoa, Italy
| | | | - Bernardo Bonanni
- Division of Cancer Prevention and Genetics, European Institute of Oncology, Milan, Italy
| | | | - Samuel G Smith
- Leeds Institute of Health Sciences, University of Leeds, United Kingdom
| | - Fedro Peccatori
- European School of Oncology Milan, Italy
- Gynecologic Oncology Division, European Institute of Oncology, Milan, Italy
| | - Andrea DeCensi
- Medical Oncology, E.O. Ospedali Galliera, Genoa, Italy.
- Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, United Kingdom
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24
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RUIZ JESSICA, NOUIZI FAROUK, CHO JAEDU, ZHENG JIE, LI YIFAN, CHEN JEONHOR, SU MINYING, GULSEN GULTEKIN. Breast density quantification using structured-light-based diffuse optical tomography simulations. APPLIED OPTICS 2017; 56:7146-7157. [PMID: 29047975 PMCID: PMC6691974 DOI: 10.1364/ao.56.007146] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Accepted: 07/26/2017] [Indexed: 05/08/2023]
Abstract
We present the feasibility of structured-light-based diffuse optical tomography (DOT) to quantify the breast density with an extensive simulation study. This study is performed on multiple numerical breast phantoms built from magnetic resonance imaging (MRI) images. These phantoms represent realistic tissue morphologies and are given typical breast optical properties. First, synthetic data are simulated at five wavelengths using our structured-light-based DOT forward problem. Afterwards, the inverse problem is solved to obtain the absorption images and subsequently the chromophore concentration maps. Parameters, such as segmented volumes and mean concentrations, are extracted from these maps and used in a regression model to estimate the percent breast densities. These estimations are correlated with the true values from MRI, r=0.97, showing that our new technique is promising in measuring breast density.
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Affiliation(s)
- JESSICA RUIZ
- Tu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, California 92697, USA
| | - FAROUK NOUIZI
- Tu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, California 92697, USA
| | - JAEDU CHO
- Tu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, California 92697, USA
| | - JIE ZHENG
- Tu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, California 92697, USA
| | - YIFAN LI
- Tu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, California 92697, USA
| | - JEON-HOR CHEN
- Tu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, California 92697, USA
- E-Da Hospital and I-Shou University, Kaohsiung, Taiwan
| | - MIN-YING SU
- Tu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, California 92697, USA
| | - GULTEKIN GULSEN
- Tu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, California 92697, USA
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25
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Paquet L, Simmonds L, Yang C, Verma S. An exploratory study of patients' views about being at high-risk for breast cancer and risk management beliefs and intentions, before and after risk counselling: Preliminary evidence of the influence of beliefs on post-counselling prevention intentions. PATIENT EDUCATION AND COUNSELING 2017; 100:575-582. [PMID: 27756584 DOI: 10.1016/j.pec.2016.10.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2016] [Revised: 09/24/2016] [Accepted: 10/08/2016] [Indexed: 06/06/2023]
Abstract
OBJECTIVES 1) To describe how women at high-risk for breast cancer (BC) perceive their at-risk status and the options available to manage this risk, before and after risk counselling; 2) to explore the contributions of pre-counselling demographic, clinical, cognitive and emotional factors to post-counselling risk management intentions. METHODS 58 of 173 eligible patients (34%) enrolled and were asked to fill surveys including measures of 1) subjective risk, 2) illness (being at high-risk for BC) and 3) treatment (surveillance, lifestyle modifications, and chemoprevention) cognitions, 4) BC fear and 5) future risk management intentions, prior to and 3 months after risk consultation. RESULTS 48 of 58 participants (83%) completed both surveys. Beliefs and emotions about their condition and its management were stable over time. Surveillance and lifestyle were associated with stronger intentions, higher perceived need, and lower concerns than chemoprevention (all ps <0.001). The strongest predictors of intentions strengths were the women's beliefs about the risk reduction methods, especially for lifestyle and chemoprevention (all ps <0.01). CONCLUSIONS The findings emphasize the importance of patients' beliefs in risk management decisions. PRACTICAL IMPLICATIONS Patients' treatment beliefs appear to influence their choice of BC risk reduction strategies and should be discussed during risk reduction consultations.
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Affiliation(s)
- Lise Paquet
- Department of Psychology, Carleton University, Ottawa K1S 5B6, Canada.
| | - Lisa Simmonds
- Medical Oncology, The Ottawa Hospital Cancer Centre, Ottawa, Canada
| | - Charles Yang
- Medical Oncology, The Ottawa Hospital Cancer Centre, Ottawa, Canada
| | - Shailendra Verma
- Medical Oncology, The Ottawa Hospital Cancer Centre, Ottawa, Canada
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26
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Hou XY, Niu HY, Huang XL, Gao Y. Correlation of Breast Ultrasound Classifications with Breast Cancer in Chinese Women. ULTRASOUND IN MEDICINE & BIOLOGY 2016; 42:2616-2621. [PMID: 27554070 DOI: 10.1016/j.ultrasmedbio.2016.07.012] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2015] [Revised: 06/17/2016] [Accepted: 07/09/2016] [Indexed: 06/06/2023]
Abstract
The aim of this study was to identify potential links between ultrasonographic breast parenchymal patterns and the risk of breast cancer in Chinese women. The population of Chinese women at high risk for breast cancer was explored using the ultrasonographic classification. Ultrasonographic parenchymal patterns were classified into four types: heterogeneous type, ductal type, mixed type and fibrous type. A total of 5879 Chinese women underwent breast ultrasound examination from May 2010 to April 2014. Of the 5879 women, 256 women had pathology-confirmed breast cancer. Among the remaining 5623 women, 512 randomly selected, age-matched women were recruited into the present study. The correlation between ultrasonographic type and breast cancer revealed that the odds ratio (OR) was highest for the heterogeneous type (odds ratio = 4.11, 95% confidence interval: 2.01-8.41, p < 0.001), followed by the fibrous type (odds ratio = 2.05, 95% confidence interval: 1.51-2.78, p < 0.001). The odds ratios of the ductal and mixed types were both less than 1 (p < 0.05). This study indicates that the heterogeneous and fibrous types in the ultrasonographic classification are associated with an increased risk of breast cancer and, therefore, can be used as a marker of breast cancer risk in the female population of China.
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Affiliation(s)
- Xin-Yan Hou
- Department of Ultrasound, PLA Beijing Military General Hospital, Beijing, China.
| | - Hai-Yan Niu
- Department of Ultrasound, PLA Beijing Military General Hospital, Beijing, China
| | - Xiao-Ling Huang
- Department of Ultrasound, PLA Beijing Military General Hospital, Beijing, China
| | - Yu Gao
- Department of Ultrasound, PLA Beijing Military General Hospital, Beijing, China
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27
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Abdolell M, Tsuruda KM, Lightfoot CB, Payne JI, Caines JS, Iles SE. Utility of relative and absolute measures of mammographic density vs clinical risk factors in evaluating breast cancer risk at time of screening mammography. Br J Radiol 2015; 89:20150522. [PMID: 26689094 DOI: 10.1259/bjr.20150522] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVE Various clinical risk factors, including high breast density, have been shown to be associated with breast cancer. The utility of using relative and absolute area-based breast density-related measures was evaluated as an alternative to clinical risk factors in cancer risk assessment at the time of screening mammography. METHODS Contralateral mediolateral oblique digital mammography images from 392 females with unilateral breast cancer and 817 age-matched controls were analysed. Information on clinical risk factors was obtained from the provincial breast-imaging information system. Breast density-related measures were assessed using a fully automated breast density measurement software. Multivariable logistic regression was conducted, and area under the receiver-operating characteristic (AUROC) curve was used to evaluate the performance of three cancer risk models: the first using only clinical risk factors, the second using only density-related measures and the third using both clinical risk factors and density-related measures. RESULTS The risk factor-based model generated an AUROC of 0.535, while the model including only breast density-related measures generated a significantly higher AUROC of 0.622 (p < 0.001). The third combined model generated an AUROC of 0.632 and performed significantly better than the risk factor model (p < 0.001) but not the density-related measures model (p = 0.097). CONCLUSION Density-related measures from screening mammograms at the time of screen may be superior predictors of cancer compared with clinical risk factors. ADVANCES IN KNOWLEDGE Breast cancer risk models based on density-related measures alone can outperform risk models based on clinical factors. Such models may support the development of personalized breast-screening protocols.
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Affiliation(s)
- Mohamed Abdolell
- 1 Department of Diagnostic Radiology, Dalhousie University, Halifax, NS, Canada.,2 Department of Diagnostic Imaging, Nova Scotia Health Authority, Halifax, NS, Canada
| | - Kaitlyn M Tsuruda
- 2 Department of Diagnostic Imaging, Nova Scotia Health Authority, Halifax, NS, Canada
| | - Christopher B Lightfoot
- 1 Department of Diagnostic Radiology, Dalhousie University, Halifax, NS, Canada.,2 Department of Diagnostic Imaging, Nova Scotia Health Authority, Halifax, NS, Canada
| | - Jennifer I Payne
- 1 Department of Diagnostic Radiology, Dalhousie University, Halifax, NS, Canada.,3 Nova Scotia Breast Screening Program, Halifax, NS, Canada.,4 Department of Community Health and Epidemiology, Dalhousie University, Halifax, NS, Canada
| | - Judy S Caines
- 1 Department of Diagnostic Radiology, Dalhousie University, Halifax, NS, Canada.,2 Department of Diagnostic Imaging, Nova Scotia Health Authority, Halifax, NS, Canada.,3 Nova Scotia Breast Screening Program, Halifax, NS, Canada
| | - Sian E Iles
- 1 Department of Diagnostic Radiology, Dalhousie University, Halifax, NS, Canada.,2 Department of Diagnostic Imaging, Nova Scotia Health Authority, Halifax, NS, Canada
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28
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Evans DG, Wisely J, Clancy T, Lalloo F, Wilson M, Johnson R, Duncan J, Barr L, Gandhi A, Howell A. Longer term effects of the Angelina Jolie effect: increased risk-reducing mastectomy rates in BRCA carriers and other high-risk women. Breast Cancer Res 2015; 17:143. [PMID: 26603733 PMCID: PMC4659163 DOI: 10.1186/s13058-015-0650-8] [Citation(s) in RCA: 69] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Affiliation(s)
- D Gareth Evans
- Genesis Breast Cancer Prevention Centre, University Hospital of South Manchester NHS Trust, Wythenshawe, Manchester, M23 9LT, UK. .,Genomic Medicine, St. Mary's Hospital, Manchester Academic Health Science Centre, Institute of Human Development, Central Manchester Foundation Trust, Oxford Road, Manchester, M13 9WL, UK.
| | - Julie Wisely
- Department of Psychology, University Hospital of South Manchester NHS Trust, Wythenshawe, Manchester, M23 9LT, UK.
| | - Tara Clancy
- Genomic Medicine, St. Mary's Hospital, Manchester Academic Health Science Centre, Institute of Human Development, Central Manchester Foundation Trust, Oxford Road, Manchester, M13 9WL, UK.
| | - Fiona Lalloo
- Genomic Medicine, St. Mary's Hospital, Manchester Academic Health Science Centre, Institute of Human Development, Central Manchester Foundation Trust, Oxford Road, Manchester, M13 9WL, UK.
| | - Mary Wilson
- Nightingale Breast Screening Centre, University Hospital of South Manchester NHS Trust, Wythenshawe, Manchester, M23 9LT, UK.
| | - Richard Johnson
- Department of Breast Surgery, University Hospital of South Manchester NHS Trust, Wythenshawe, Manchester, M23 9LT, UK.
| | - Jonathon Duncan
- Department of Plastic Surgery, University Hospital of South Manchester NHS Trust, Wythenshawe, Manchester, M23 9LT, UK.
| | - Lester Barr
- Department of Breast Surgery, University Hospital of South Manchester NHS Trust, Wythenshawe, Manchester, M23 9LT, UK.
| | - Ashu Gandhi
- Department of Breast Surgery, University Hospital of South Manchester NHS Trust, Wythenshawe, Manchester, M23 9LT, UK.
| | - Anthony Howell
- Genesis Breast Cancer Prevention Centre, University Hospital of South Manchester NHS Trust, Wythenshawe, Manchester, M23 9LT, UK.
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29
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Allman R, Dite GS, Hopper JL, Gordon O, Starlard-Davenport A, Chlebowski R, Kooperberg C. SNPs and breast cancer risk prediction for African American and Hispanic women. Breast Cancer Res Treat 2015; 154:583-9. [PMID: 26589314 PMCID: PMC4661211 DOI: 10.1007/s10549-015-3641-7] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2015] [Accepted: 11/13/2015] [Indexed: 12/24/2022]
Abstract
For African American or Hispanic women, the extent to which clinical breast cancer risk prediction models are improved by including information on susceptibility single nucleotide polymorphisms (SNPs) is unknown, even though these women comprise increasing proportions of the US population and represent a large proportion of the world’s population. We studied 7539 African American and 3363 Hispanic women from the Women’s Health Initiative. The age-adjusted 5-year risks from the BCRAT and IBIS risk prediction models were measured and combined with a risk score based on >70 independent susceptibility SNPs. Logistic regression, adjusting for age group, was used to estimate risk associations with log-transformed age-adjusted 5-year risks. Discrimination was measured by the odds ratio (OR) per standard deviation (SD) and the area under the receiver operator curve (AUC). When considered alone, the ORs for African American women were 1.28 for BCRAT, and 1.04 for IBIS. When combined with the SNP risk score (OR 1.23), the corresponding ORs were 1.39 and 1.22. For Hispanic women the corresponding ORs were 1.25 for BCRAT, and 1.15 for IBIS. When combined with the SNP risk score (OR 1.39), the corresponding ORs were 1.48 and 1.42. There was no evidence that any of the combined models were not well calibrated. Including information on known breast cancer susceptibility loci provides approximately 10 and 19 % improvement in risk prediction using BCRAT for African Americans and Hispanics, respectively. The corresponding figures for IBIS are approximately 18 and 26 %, respectively.
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Affiliation(s)
- Richard Allman
- Genetic Technologies Ltd., 60-66 Hanover Street, Fitzroy, VIC, 3065, Australia.
| | - Gillian S Dite
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne, Australia
| | - Ora Gordon
- Providence St. Joseph Medical Center/UCLA School of Medicine, Los Angeles, CA, USA
| | - Athena Starlard-Davenport
- Department of Medical Genetics, The University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Rowan Chlebowski
- Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
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