1
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Bhatt R, van den Hout A, Antoniou AC, Shah M, Ficorella L, Steggall E, Easton DF, Pharoah PDP, Pashayan N. Estimation of age of onset and progression of breast cancer by absolute risk dependent on polygenic risk score and other risk factors. Cancer 2024; 130:1590-1599. [PMID: 38174903 PMCID: PMC7615824 DOI: 10.1002/cncr.35183] [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: 06/14/2023] [Revised: 11/08/2023] [Accepted: 12/05/2023] [Indexed: 01/05/2024]
Abstract
BACKGROUND Genetic, lifestyle, reproductive, and anthropometric factors are associated with the risk of developing breast cancer. However, it is not yet known whether polygenic risk score (PRS) and absolute risk based on a combination of risk factors are associated with the risk of progression of breast cancer. This study aims to estimate the distribution of sojourn time (pre-clinical screen-detectable period) and mammographic sensitivity by absolute breast cancer risk derived from polygenic profile and the other risk factors. METHODS The authors used data from a population-based case-control study. Six categories of 10-year absolute risk based on different combinations of risk factors were derived using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm. Women were classified into low, medium, and high-risk groups. The authors constructed a continuous-time multistate model. To calculate the sojourn time, they simulated the trajectories of subjects through the disease states. RESULTS There was little difference in sojourn time with a large overlap in the 95% confidence interval (CI) between the risk groups across the six risk categories and PRS studied. However, the age of entry into the screen-detectable state varied by risk category, with the mean age of entry of 53.4 years (95% CI, 52.2-54.1) and 57.0 years (95% CI, 55.1-57.7) in the high-risk and low-risk women, respectively. CONCLUSION In risk-stratified breast screening, the age at the start of screening, but not necessarily the frequency of screening, should be tailored to a woman's risk level. The optimal risk-stratified screening strategy that would improve the benefit-to-harm balance and the cost-effectiveness of the screening programs needs to be studied.
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Affiliation(s)
- Rikesh Bhatt
- Department of Applied Health Research, University College London, London, UK
| | - Ardo van den Hout
- Department of Statistical Science, University College London, London, UK
| | - Antonis C. Antoniou
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Mitul Shah
- Department of Oncology, University of Cambridge, Cambridge, UK
| | - Lorenzo Ficorella
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | | | - Douglas F. Easton
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Paul D. P. Pharoah
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Department of Computational Biomedicine, Cedars Sinai Medical Center, Los Angeles, California, USA
| | - Nora Pashayan
- Department of Applied Health Research, University College London, London, UK
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2
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Laza C, Niño de Guzmán E, Gea M, Plazas M, Posso M, Rué M, Castells X, Román M. "For and against" factors influencing participation in personalized breast cancer screening programs: a qualitative systematic review until March 2022. Arch Public Health 2024; 82:23. [PMID: 38389068 PMCID: PMC10882761 DOI: 10.1186/s13690-024-01248-x] [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: 11/09/2023] [Accepted: 02/05/2024] [Indexed: 02/24/2024] Open
Abstract
BACKGROUND Personalized breast cancer screening is a novel strategy that estimates individual risk based on age, breast density, family history of breast cancer, personal history of benign breast lesions, and polygenic risk. Its goal is to propose personalized early detection recommendations for women in the target population based on their individual risk. Our aim was to synthesize the factors that influence women's decision to participate in personalized breast cancer screening, from the perspective of women and health care professionals. METHODS Systematic review of qualitative evidence on factors influencing participation in personalized Breast Cancer Screening. We searched in Medline, Web of science, Scopus, EMBASE, CINAHL and PsycINFO for qualitative and mixed methods studies published up to March 2022. Two reviewers conducted study selection and extracted main findings. We applied the best-fit framework synthesis and adopted the Multilevel influences on the cancer care continuum model for analysis. After organizing initial codes into the seven levels of the selected model, we followed thematic analysis and developed descriptive and analytical themes. We assessed the methodological quality with the Critical Appraisal Skills Program tool. RESULTS We identified 18 studies published between 2017 and 2022, conducted in developed countries. Nine studies were focused on women (n = 478) and in four studies women had participated in a personalized screening program. Nine studies focused in health care professionals (n = 162) and were conducted in primary care and breast cancer screening program settings. Factors influencing women's decision to participate relate to the women themselves, the type of program (personalized breast cancer screening) and perspective of health care professionals. Factors that determined women participation included persistent beliefs and insufficient knowledge about breast cancer and personalized screening, variable psychological reactions, and negative attitudes towards breast cancer risk estimates. Other factors against participation were insufficient health care professionals knowledge on genetics related to breast cancer and personalized screening process. The factors that were favourable included the women's perceived benefits for themselves and the positive impact on health systems. CONCLUSION We identified the main factors influencing women's decisions to participate in personalized breast cancer screening. Factors related to women, were the most relevant negative factors. A future implementation requires improving health literacy for women and health care professionals, as well as raising awareness of the strategy in society.
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Affiliation(s)
- Celmira Laza
- Department of Nursing and Physiotherapy, University of Lleida, Lleida, Spain
- Biomedical Research Institute of Lleida Fundació Dr. Pifarré (IRBLleida), Lleida, Spain
| | - Ena Niño de Guzmán
- Cancer Prevention and Control Program, Institut Català d' Oncologia, Barcelona, Spain
| | - Montserrat Gea
- Department of Nursing and Physiotherapy, University of Lleida, Lleida, Spain
- Biomedical Research Institute of Lleida Fundació Dr. Pifarré (IRBLleida), Lleida, Spain
| | - Merideidy Plazas
- Cochrane Associated Center- University Foundation of Health Sciences, Bogotá, Colombia
| | - Margarita Posso
- Department of Epidemiology and Evaluation, Hospital del Mar Research Institute, Barcelona, Spain
| | - Montserrat Rué
- Biomedical Research Institute of Lleida Fundació Dr. Pifarré (IRBLleida), Lleida, Spain
- Basic Medical Sciences, University of Lleida, Lleida, Spain
| | - Xavier Castells
- Department of Epidemiology and Evaluation, Hospital del Mar Research Institute, Barcelona, Spain
| | - Marta Román
- Department of Epidemiology and Evaluation, Hospital del Mar Research Institute, Barcelona, Spain.
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3
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LA Dunlop K, Smit AK, Keogh LA, Newson AJ, Rankin NM, Cust AE. Acceptability of risk-tailored cancer screening among Australian GPs: a qualitative study. Br J Gen Pract 2024; 74:BJGP.2023.0117. [PMID: 38373853 PMCID: PMC10904141 DOI: 10.3399/bjgp.2023.0117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Accepted: 05/22/2023] [Indexed: 02/21/2024] Open
Abstract
BACKGROUND Cancer screening that is tailored to individual risk has the potential to improve health outcomes and reduce screening-related harms, if implemented well. However, successful implementation depends on acceptability, particularly as this approach will require GPs to change their practice. AIM To explore Australian GPs' views about the acceptability of risk-tailored screening across cancer types and to identify barriers to and facilitators of implementation. DESIGN AND SETTING A qualitative study using semi-structured interviews with Australian GPs. METHOD Interviews were carried out with GPs and audio-recorded and transcribed. Data were first analysed inductively then deductively using an implementation framework. RESULTS Participants (n = 20) found risk-tailored screening to be acceptable in principle, recognising potential benefits in offering enhanced screening to those at highest risk. However, they had significant concerns that changes in screening advice could potentially cause confusion. They also reported that a reduced screening frequency or exclusion from a screening programme for those deemed low risk may not initially be acceptable, especially for common cancers with minimally invasive screening. Other reservations about implementing risk-tailored screening in general practice included a lack of high-quality evidence of benefit, fear of missing the signs or symptoms of a patient's cancer, and inadequate time with patients. While no single preferred approach to professional education was identified, education around communicating screening results and risk stratification was considered important. CONCLUSION GPs may not currently be convinced of the net benefits of risk-tailored screening. Development of accessible evidence-based guidelines, professional education, risk calculators, and targeted public messages will increase its feasibility in general practice.
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Affiliation(s)
- Kate LA Dunlop
- The Daffodil Centre, a joint venture with Cancer Council NSW and Melanoma Institute Australia, University of Sydney, Sydney
| | - Amelia K Smit
- The Daffodil Centre, a joint venture with Cancer Council NSW and Melanoma Institute Australia, University of Sydney, Sydney
| | - Louise A Keogh
- Centre for Health Equity, Melbourne School of Population and Global Health, University of Melbourne, Melbourne
| | - Ainsley J Newson
- Faculty of Medicine and Health, Sydney School of Public Health, Sydney Health Ethics, University of Sydney, Sydney
| | - Nicole M Rankin
- Evaluation and Implementation Science Unit, Melbourne School of Population and Global Health, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne
| | - Anne E Cust
- The Daffodil Centre, a joint venture with Cancer Council NSW and Melanoma Institute Australia, University of Sydney, Sydney
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4
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Dunlop KLA, Keogh LA, Smith AL, Aranda S, Aitken J, Watts CG, Smit AK, Janda M, Mann GJ, Cust AE, Rankin NM. Acceptability and appropriateness of a risk-tailored organised melanoma screening program: Qualitative interviews with key informants. PLoS One 2023; 18:e0287591. [PMID: 38091281 PMCID: PMC10718433 DOI: 10.1371/journal.pone.0287591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 06/08/2023] [Indexed: 12/18/2023] Open
Abstract
INTRODUCTION In Australia, opportunistic screening (occurring as skin checks) for the early detection of melanoma is common, and overdiagnosis is a recognised concern. Risk-tailored cancer screening is an approach to cancer control that aims to provide personalised screening tailored to individual risk. This study aimed to explore the views of key informants in Australia on the acceptability and appropriateness of risk-tailored organised screening for melanoma, and to identify barriers, facilitators and strategies to inform potential future implementation. Acceptability and appropriateness are crucial, as successful implementation will require a change of practice for clinicians and consumers. METHODS This was a qualitative study using semi-structured interviews. Key informants were purposively selected to ensure expertise in melanoma early detection and screening, prioritising senior or executive perspectives. Consumers were expert representatives. Data were analysed deductively using the Tailored Implementation for Chronic Diseases (TICD) checklist. RESULTS Thirty-six participants were interviewed (10 policy makers; 9 consumers; 10 health professionals; 7 researchers). Key informants perceived risk-tailored screening for melanoma to be acceptable and appropriate in principle. Barriers to implementation included lack of trial data, reluctance for low-risk groups to not screen, variable skill level in general practice, differing views on who to conduct screening tests, confusing public health messaging, and competing health costs. Key facilitators included the perceived opportunity to improve health equity and the potential cost-effectiveness of a risk-tailored screening approach. A range of implementation strategies were identified including strengthening the evidence for cost-effectiveness, engaging stakeholders, developing pathways for people at low risk, evaluating different risk assessment criteria and screening delivery models and targeted public messaging. CONCLUSION Key informants were supportive in principle of risk-tailored melanoma screening, highlighting important next steps. Considerations around risk assessment, policy and modelling the costs of current verses future approaches will help inform possible future implementation of risk-tailored population screening for melanoma.
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Affiliation(s)
- Kate L. A. Dunlop
- The Daffodil Centre, The University of Sydney, A Joint Venture with Cancer Council NSW, Sydney, NSW, Australia
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia
| | - Louise A. Keogh
- Centre for Health Equity, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Andrea L. Smith
- The Daffodil Centre, The University of Sydney, A Joint Venture with Cancer Council NSW, Sydney, NSW, Australia
| | - Sanchia Aranda
- School of Health Sciences, University of Melbourne, Melbourne, Australia
| | - Joanne Aitken
- Viertel Cancer Research Centre, Cancer Council Queensland, Brisbane, Queensland, Australia
| | - Caroline G. Watts
- The Daffodil Centre, The University of Sydney, A Joint Venture with Cancer Council NSW, Sydney, NSW, Australia
- Surveillance, Evaluation & Research Program, Kirby Institute, UNSW Sydney, Sydney, New South Wales, Australia
| | - Amelia K. Smit
- The Daffodil Centre, The University of Sydney, A Joint Venture with Cancer Council NSW, Sydney, NSW, Australia
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia
| | - Monika Janda
- Centre for Health Services Research, The University of Queensland, St Lucia, Queensland, Australia
| | - Graham J. Mann
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia
- John Curtin School of Medical Research, Australian National University, Acton, Australian Capital Territory, Australia
- Centre for Cancer Research, Westmead Institute for Medical Research, The University of Sydney, Westmead, Sydney, New South Wales, Australia
| | - Anne E. Cust
- The Daffodil Centre, The University of Sydney, A Joint Venture with Cancer Council NSW, Sydney, NSW, Australia
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia
| | - Nicole M. Rankin
- Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
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5
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Levi H, Carmi S, Rosset S, Yerushalmi R, Zick A, Yablonski-Peretz T, Wang Q, Bolla MK, Dennis J, Michailidou K, Lush M, Ahearn T, Andrulis IL, Anton-Culver H, Antoniou AC, Arndt V, Augustinsson A, Auvinen P, Beane Freeman L, Beckmann M, Behrens S, Bermisheva M, Bodelon C, Bogdanova NV, Bojesen SE, Brenner H, Byers H, Camp N, Castelao J, Chang-Claude J, Chirlaque MD, Chung W, Clarke C, Collee MJ, Colonna S, Couch F, Cox A, Cross SS, Czene K, Daly M, Devilee P, Dork T, Dossus L, Eccles DM, Eliassen AH, Eriksson M, Evans G, Fasching P, Fletcher O, Flyger H, Fritschi L, Gabrielson M, Gago-Dominguez M, García-Closas M, Garcia-Saenz JA, Genkinger J, Giles GG, Goldberg M, Guénel P, Hall P, Hamann U, He W, Hillemanns P, Hollestelle A, Hoppe R, Hopper J, Jakovchevska S, Jakubowska A, Jernström H, John E, Johnson N, Jones M, Vijai J, Kaaks R, Khusnutdinova E, Kitahara C, Koutros S, Kristensen V, Kurian AW, Lacey J, Lambrechts D, Le Marchand L, Lejbkowicz F, Lindblom A, Loibl S, Lori A, Lubinski J, Mannermaa A, Manoochehri M, Mavroudis D, Menon U, Mulligan A, Murphy R, Nevelsteen I, Newman WG, Obi N, O'Brien K, Offit K, Olshan A, Plaseska-Karanfilska D, Olson J, Panico S, Park-Simon TW, Patel A, Peterlongo P, Rack B, Radice P, Rennert G, Rhenius V, Romero A, Saloustros E, Sandler D, Schmidt MK, Schwentner L, Shah M, Sharma P, Simard J, Southey M, Stone J, Tapper WJ, Taylor J, Teras L, Toland AE, Troester M, Truong T, van der Kolk LE, Weinberg C, Wendt C, Yang XR, Zheng W, Ziogas A, Dunning AM, Pharoah P, Easton DF, Ben-Sachar S, Elefant N, Shamir R, Elkon R. Evaluation of European-based polygenic risk score for breast cancer in Ashkenazi Jewish women in Israel. J Med Genet 2023; 60:1186-1197. [PMID: 37451831 PMCID: PMC10715538 DOI: 10.1136/jmg-2023-109185] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 05/28/2023] [Indexed: 07/18/2023]
Abstract
BACKGROUND Polygenic risk score (PRS), calculated based on genome-wide association studies (GWASs), can improve breast cancer (BC) risk assessment. To date, most BC GWASs have been performed in individuals of European (EUR) ancestry, and the generalisation of EUR-based PRS to other populations is a major challenge. In this study, we examined the performance of EUR-based BC PRS models in Ashkenazi Jewish (AJ) women. METHODS We generated PRSs based on data on EUR women from the Breast Cancer Association Consortium (BCAC). We tested the performance of the PRSs in a cohort of 2161 AJ women from Israel (1437 cases and 724 controls) from BCAC (BCAC cohort from Israel (BCAC-IL)). In addition, we tested the performance of these EUR-based BC PRSs, as well as the established 313-SNP EUR BC PRS, in an independent cohort of 181 AJ women from Hadassah Medical Center (HMC) in Israel. RESULTS In the BCAC-IL cohort, the highest OR per 1 SD was 1.56 (±0.09). The OR for AJ women at the top 10% of the PRS distribution compared with the middle quintile was 2.10 (±0.24). In the HMC cohort, the OR per 1 SD of the EUR-based PRS that performed best in the BCAC-IL cohort was 1.58±0.27. The OR per 1 SD of the commonly used 313-SNP BC PRS was 1.64 (±0.28). CONCLUSIONS Extant EUR GWAS data can be used for generating PRSs that identify AJ women with markedly elevated risk of BC and therefore hold promise for improving BC risk assessment in AJ women.
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Grants
- R01 CA176785 NCI NIH HHS
- NU58DP006344 NCCDPHP CDC HHS
- R37 CA070867 NCI NIH HHS
- HHSN261201800015I NCI NIH HHS
- R01 CA064277 NCI NIH HHS
- P50 CA116201 NCI NIH HHS
- G1000143 Medical Research Council
- P30 CA062203 NCI NIH HHS
- HHSN261201800015C NCI NIH HHS
- R01 CA047305 NCI NIH HHS
- HHSN261201800009I NCI NIH HHS
- R01 CA163353 NCI NIH HHS
- UM1 CA164917 NCI NIH HHS
- U01 CA199277 NCI NIH HHS
- U01 CA179715 NCI NIH HHS
- HHSN261201800032C NCI NIH HHS
- U54 CA156733 NCI NIH HHS
- HHSN261201800009C NCI NIH HHS
- Z01 CP010119 Intramural NIH HHS
- UM1 CA164973 NCI NIH HHS
- P01 CA087969 NCI NIH HHS
- UM1 CA164920 NCI NIH HHS
- NU58DP006320 CDC HHS
- UM1 CA176726 NCI NIH HHS
- R01 CA092447 NCI NIH HHS
- Z01 ES049030 Intramural NIH HHS
- R01 CA058860 NCI NIH HHS
- K07 CA092044 NCI NIH HHS
- HHSN261201800016C NCI NIH HHS
- P50 CA058223 NCI NIH HHS
- R01 CA100374 NCI NIH HHS
- P30 CA008748 NCI NIH HHS
- R01 CA128978 NCI NIH HHS
- R01 CA047147 NCI NIH HHS
- U19 CA148537 NCI NIH HHS
- R01 CA116167 NCI NIH HHS
- R01 CA148667 NCI NIH HHS
- R01 CA063464 NCI NIH HHS
- HHSN261201800016I NCI NIH HHS
- UM1 CA186107 NCI NIH HHS
- P30 CA023100 NCI NIH HHS
- U01 CA063464 NCI NIH HHS
- R01 CA077398 NCI NIH HHS
- R01 CA054281 NCI NIH HHS
- R01 CA132839 NCI NIH HHS
- P30 CA068485 NCI NIH HHS
- U01 CA058860 NCI NIH HHS
- U01 CA164920 NCI NIH HHS
- R35 CA253187 NCI NIH HHS
- 14136 Cancer Research UK
- U19 CA148112 NCI NIH HHS
- HHSN261201800032I NCI NIH HHS
- U01 CA098758 NCI NIH HHS
- Z01 ES044005 Intramural NIH HHS
- U19 CA148065 NCI NIH HHS
- P30 CA033572 NCI NIH HHS
- R01 CA069664 NCI NIH HHS
- Wellcome Trust
- 001 World Health Organization
- Z01 ES049033 Intramural NIH HHS
- R01 CA192393 NCI NIH HHS
- U01 CA164973 NCI NIH HHS
- R37 CA054281 NCI NIH HHS
- Consellería de Industria Programa Sectorial de Investigación Aplicada
- Statistics Netherlands
- South Eastern Norway Health Authority
- Lower Saxonian Cancer Society
- Lise Boserup Fund
- Heidelberger Zentrum für Personalisierte Onkologie Deutsches Krebsforschungszentrum In Der Helmholtz-Gemeinschaft
- Lon V. Smith Foundation
- Scottish Funding Council
- Komen Foundation
- Claudia von Schilling Foundation for Breast Cancer Research
- Russian Foundation for Basic Research
- Ligue Contre le Cancer
- Sigrid Juselius Foundation
- Kuopion Yliopistollinen Sairaala
- Sheffield Experimental Cancer Medicine Centre
- Stockholm läns landsting
- Department of Health and Human Services (USA)
- Department of Defence (USA)
- Stichting Tegen Kanker
- David F. and Margaret T. Grohne Family Foundation
- Sundhed og Sygdom, Det Frie Forskningsråd
- Stavros Niarchos Foundation
- Post-Cancer GWAS initiative
- Institute of the Ruhr University Bochum
- Instituto de Salud Carlos III
- Institute of Cancer Research
- Public Health Institute
- Fondation du cancer du sein du Québec
- Institut National de la Santé et de la Recherche Médicale
- Pink Ribbon
- Institute for Prevention and Occupational Medicine
- K.G. Jebsen Centre for Breast Cancer Research
- Research Centre for Genetic Engineering and Biotechnology
- Center of Excellence (Finland)
- Robert and Kate Niehaus Clinical Cancer Genetics Initiative
- Rudolf Bartling Foundation
- Center for Disease Control and Prevention (USA)
- Karolinska Institutet
- Norges Forskningsråd
- Robert Bosch Stiftung
- Intramural Research Funds of the National Cancer Institute (USA)
- Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, ISCIII RETIC
- Intramural Research Program of the Division of Cancer Epidemiology and Genetics
- Centre International de Recherche sur le Cancer
- Queensland Cancer Fund
- Red Temática de Investigación Cooperativa en Cáncer
- Intramural Research Program of the National Institutes of Health
- National Health Service (UK)
- Ministerie van Volksgezondheid, Welzijn en Sport
- National cancer institute (USA)
- KWF Kankerbestrijding
- Märit and Hans Rausings Initiative Against Breast Cancer
- Associazione Italiana per la Ricerca sul Cancro
- Fundación Científica Asociación Española Contra el Cáncer
- ERC advanced grant
- Australian National Health and Medical Research Council
- Agence Nationale de la Recherche
- Dutch Prevention Funds,
- Agence Nationale de Sécurité Sanitaire de l'Alimentation, de l'Environnement et du Travail
- American Cancer Society
- Dutch Zorg Onderzoek
- Alexander von Humboldt-Stiftung
- Ministerio de Economia y Competitividad (Spain)
- Ministère du Développement Économique, de l’Innovation et de l’Exportation
- Susan G. Komen for the Cure
- Minister of Science and Higher Education
- Medical Research Council UK
- Ministry of Science and Higher Education of the Russian Federation
- Ministry of Science and Higher Education (Sweden)
- Against Breast Cancer
- Mutuelle Générale de l’Education Nationale
- Academy of Finland
- Deutsche Krebshilfe e.V.
- Dietmar-Hopp Foundation,
- Division of Cancer Prevention, National Cancer Institute
- Deutsche Krebshilfe
- World Cancer Research Fund
- Genome Québec
- National Cancer Institute’s Surveillance, Epidemiology and End Results Program
- Breast Cancer Campaign
- National Cancer Research Network
- Berta Kamprad Foundation FBKS
- Bert von Kantzows foundation
- Biomedical Research Centre at Guy’s and St Thomas
- Genome Canada
- Freistaat Sachsen
- Biobanking and Biomolecular Resources Research Infrastructure
- Friends of Hannover Medical School
- Breast Cancer Research Foundation
- California Department of Public Health
- Government of Russian Federation
- Deutsche Forschungsgemeinschaft
- National Institute for Health and Care Research
- National Health and Medical Research Council (Australia)
- German Federal Ministry of Research and Education
- National Institute of Environmental Health Sciences
- Breast Cancer Now
- Seventh Framework Programme
- Transcan
- Centrum för idrottsforskning
- UK National Institute for Health Research Biomedical Research Centre
- University of Crete
- National Breast Cancer Foundation (Finland)
- European Regional Development Fund
- National Breast Cancer Foundation (Australia)
- United States Army Medical Research and Materiel Command
- EU Horizon 2020 Research and Innovation Programme
- Directorate-General XII, Science, Research, and Development
- Baden Württemberg Ministry of Science, Research and Arts
- VicHealth
- Fondo de Investigación Sanitario
- Victorian Breast Cancer Research Consortium.
- Finnish Cancer Foundation
- University of Southern California San Francisco
- Fomento de la Investigación Clínica Independiente
- the Cancer Biology Research Center (CBRC), Djerassi Oncology Center
- Bundesministerium für Bildung und Forschung
- Cancerfonden
- Tel Aviv University Center for AI and Data Science
- University of Oulu
- National Breast Cancer Foundation (JS)
- Safra Center for Bioinformatics
- Fondation de France, Institut National du Cancer
- Israeli Science Foundation
- University of Utah
- National Cancer Center Research and Development Fund (Japan)
- Chief Scientist Office, Scottish Government Health and Social Care Directorate
- Oak Foundation
- Health Research Fund (FIS)
- Ontario Familial Breast Cancer Registry
- New South Wales Cancer Council
- North Carolina University Cancer Research Fund
- Kreftforeningen
- Northern California Breast Cancer Family Registry
- Institut Gustave Roussy
- Huntsman Cancer Institute, University of Utah
- Ovarian Cancer Research Fund
- NIHR Oxford Biomedical Research Centre
- Hellenic Health Foundation
- Oulun Yliopistollinen Sairaala
- Helmholtz Society
- Herlev and Gentofte Hospital
- PSRSIIRI-701
- Helsinki University Hospital Research Fund
- Cancer Council Victoria
- National Research Council (Italy)
- Cancer Council Tasmania
- Cancer Council Western Australia
- Hamburger Krebsgesellschaft
- Gustav V Jubilee foundation
- National Program of Cancer Registries
- Canadian Cancer Society
- Cancer Council South Australia
- Canadian Institutes of Health Research
- Cancer Council NSW
- Guy's & St. Thomas' NHS Foundation Trust
- Netherlands Organisation of Scientific Research
- Cancer Institute NSW
- National Institutes of Health (USA)
- National Research Foundation of Korea
- Syöpäsäätiö
- Cancer Foundation of Western Australia
- Netherlands Cancer Registry (NKR),
- Cancer Fund of North Savo
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Affiliation(s)
- Hagai Levi
- The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
- Department of Human Molecular Genetics and Biochemistry, Tel Aviv University, Tel Aviv, Israel
| | - Shai Carmi
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Saharon Rosset
- Department of Statistics and Operations Research, Tel Aviv University, Tel Aviv, Israel
| | - Rinat Yerushalmi
- Institute of Oncology, Davidoff Cancer Center, Rabin Medical Center, Beilinson Hospital, Petah Tikva, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Aviad Zick
- Department of oncology, Hadassah Medical Center, Jerusalem, Israel
- Hebrew University of Jerusalem, Jerusalem, Israel
| | - Tamar Yablonski-Peretz
- Department of oncology, Hadassah Medical Center, Jerusalem, Israel
- Hebrew University of Jerusalem, Jerusalem, Israel
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Manjeet K Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Kyriaki Michailidou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Biostatistics Unit, The Cyprus Institute of Neurology & Genetics, Nicosia, Cyprus
| | - Michael Lush
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Thomas Ahearn
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Irene L Andrulis
- Fred A. Litwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Hoda Anton-Culver
- Department of Medicine, Genetic Epidemiology Research Institute, University of California Irvine, Irvine, CA, USA
| | - Antonis C Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Volker Arndt
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Annelie Augustinsson
- Oncology, Department of Clinical Sciences in Lund, Lund University, Lund, Sweden
| | - Päivi Auvinen
- Translational Cancer Research Area, University of Eastern Finland, Kuopio, Finland
- Institute of Clinical Medicine, Oncology, University of Eastern Finland, Kuopio, Finland
- Department of Oncology, Cancer Center, Kuopio University Hospital, Kuopio, Finland
| | - Laura Beane Freeman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Matthias Beckmann
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Sabine Behrens
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Marina Bermisheva
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre of the Russian Academy of Sciences, Ufa, Russia
| | - Clara Bodelon
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Natalia V Bogdanova
- Department of Radiation Oncology, Hannover Medical School, Hannover, Germany
- Gynaecology Research Unit, Hannover Medical School, Hamburg, Germany
- N.N. Alexandrov Research Institute of Oncology and Medical Radiology, Minsk, Belarus
| | - Stig E Bojesen
- Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Faculty of Health and Medical Sciences, Copenhagen, Denmark
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
| | - Helen Byers
- North West Genomics Laboratory Hub, Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Nicola Camp
- Department of Internal Medicine and Huntsman Cancer Institute, University of Utah, Salt lake city, UT, USA
| | - Jose Castelao
- Oncology and Genetics Unit, Instituto de Investigación Sanitaria Galicia Sur (IISGS), Xerencia de Xestion Integrada de Vigo-SERGAS, Vigo, Spain
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Cancer Epidemiology Group, University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | | | - Wendy Chung
- Departments of Pediatrics and Medicine, Columbia University, New York, NY, USA
| | - Christine Clarke
- Westmead Institute for Medical Research, University of Sydney, Sydney, New South Wales, Australia
| | - Margriet J Collee
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, Netherlands
| | - Sarah Colonna
- Department of Internal Medicine and Huntsman Cancer Institute, University of Utah, Salt lake city, UT, USA
| | - Fergus Couch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Angela Cox
- Department of Oncology and Metabolism, Sheffield Institute for Nucleic Acids (SInFoNiA), University of Sheffield, Sheffield, UK
| | - Simon S Cross
- Academic Unit of Pathology, Department of Neuroscience, University of Sheffield, Sheffield, UK
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Mary Daly
- Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, PA, USA
| | - Peter Devilee
- Department of Pathology, Leiden University Medical Center, Leiden, Netherlands
- Department of Human Genetics, Leiden University Medical, Leiden, Netherlands
| | - Thilo Dork
- Gynaecology Research Unit, Hannover Medical School, Hamburg, Germany
| | - Laure Dossus
- Nutrition and Metabolism Section, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Diana M Eccles
- Cancer Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - A Heather Eliassen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Gareth Evans
- North West Genomics Laboratory Hub, Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Peter Fasching
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Olivia Fletcher
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - Henrik Flyger
- Department of Breast Surgery, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Lin Fritschi
- School of Population Health, Curtin University, Perth, Western Australia, Australia
| | - Marike Gabrielson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Manuela Gago-Dominguez
- Genomic Medicine Group, International Cancer Genetics and Epidemiology Group, Fundación Pública Galega de Medicina Xenómica, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago, SERGAS, Santiago de Compostela, Spain
| | - Montserrat García-Closas
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | | | - Jeanine Genkinger
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
- Herbert Irving Comprehensive Cancer Center, New York, New York, USA
| | - Graham G Giles
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Mark Goldberg
- Department of Medicine, McGill University, Montreal, Quebec, Canada
- Division of Clinical Epidemiology, Royal Victoria Hospital, McGill University, Montreal, QU, Canada
| | - Pascal Guénel
- Team 'Exposome and Heredity', CESP, Gustave Roussy, INSERM, University Paris-Saclay, UVSQ, Villejuif, France
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Oncology, Södersjukhuset, Stockholm, Sweden
| | - Ute Hamann
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Wei He
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Peter Hillemanns
- Gynaecology Research Unit, Hannover Medical School, Hamburg, Germany
| | | | - Reiner Hoppe
- Dr Margarete Fischer Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tubingen, Germany
| | - John Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Simona Jakovchevska
- Research Centre for Genetic Engineering and Biotechnology 'Georgi D. Efremov', Skopje, North Macedonia
| | - Anna Jakubowska
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
- Independent Laboratory of Molecular Biology and Genetic Diagnostics, Pomeranian Medical University, Szczecin, Poland
| | - Helena Jernström
- Oncology, Department of Clinical Sciences in Lund, Lund University, Lund, Sweden
| | - Esther John
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medicine, Division of Oncology, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Nichola Johnson
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - Michael Jones
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, UK
| | - Joseph Vijai
- Clinical Genetics Research Lab, Department of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Clinical Genetics Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Elza Khusnutdinova
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre of the Russian Academy of Sciences, Ufa, Russia
- Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa, Russia
| | - Cari Kitahara
- Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Stella Koutros
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Vessela Kristensen
- Institute of Clinical Medicine, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Allison W Kurian
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medicine, Division of Oncology, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - James Lacey
- Department of Computational and Quantitative Medicine, City of Hope, Duarte, CA, USA
- City of Hope Comprehensive Cancer Center, City of Hope, Duarte, CA, USA
| | - Diether Lambrechts
- Laboratory for Translational Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium
- VIB Center for Cancer Biology, VIB, Leuven, Belgium
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Flavio Lejbkowicz
- Clalit National Cancer Control Center, Carmel Medical Center and Technion Faculty of Medicine, Haifa, Israel
| | - Annika Lindblom
- Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | | | - Adriana Lori
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Jan Lubinski
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Arto Mannermaa
- Translational Cancer Research Area, University of Eastern Finland, Kuopio, Finland
- Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland
- Biobank of Eastern Finland, Kuopio University Hospital, Kuopio, Finland
| | - Mehdi Manoochehri
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Dimitrios Mavroudis
- Department of Medical Oncology, University Hospital of Heraklion, Heraklion, Greece
| | - Usha Menon
- MRC Clinical Trials Unit, Institute of Clinical Trials and Methodology, University College, London, UK
| | - AnnaMarie Mulligan
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
- Laboratory Medicine Program, University Health Network, Toronto, Ontario, Canada
| | - Rachel Murphy
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
- Cancer Control Research, BC Cancer Agency, Vancouver, BC, Canada
| | - Ines Nevelsteen
- Leuven Multidisciplinary Breast Center, Department of Oncology, Leuven Cancer Institute, University Hospitals Leuven, Leuven, Belgium
| | - William G Newman
- North West Genomics Laboratory Hub, Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Nadia Obi
- Institute for Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Katie O'Brien
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Ken Offit
- Clinical Genetics Research Lab, Department of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Clinical Genetics Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Andrew Olshan
- Department of Epidemiology, Gillings School of Global Public Health and UNC Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | | - Janet Olson
- Department of Quantitative Health Sciences, Division of Epidemiology, Mayo Clinic, Rochester, MN, USA
| | - Salvatore Panico
- Dipertimento Di Medicina Clinca e Chirurgia, Federico II University, Naples, Italy
| | | | - Alpa Patel
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Paolo Peterlongo
- Genome Diagnostics Program, IFOM ETS - the AIRC Institute of Molecular Oncology, Milan, Italy
| | - Brigitte Rack
- Department of Gynaecology and Obstetrics, University Hospital Ulm, Ulm, Germany
| | - Paolo Radice
- Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori (INT), Milan, Italy
| | - Gad Rennert
- Clalit National Cancer Control Center, Carmel Medical Center and Technion Faculty of Medicine, Haifa, Israel
| | - Valerie Rhenius
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Atocha Romero
- Laboratorio de Oncología Molecular, Hospital Clínico San Carlos, Madrid, Spain
| | | | - Dale Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Marjanka K Schmidt
- Division of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, Netherlands
- Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek hospital, Amsterdam, Netherlands
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, Netherlands
| | - Lukas Schwentner
- Department of Gynaecology and Obstetrics, University Hospital Ulm, Ulm, Germany
| | - Mitul Shah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Priyanka Sharma
- Department of Internal Medicine, Division of Medical Oncology, University of Kansas Medical Center, Westwood, KS, USA
| | - Jacques Simard
- Genomics Center, Molecular Medicine, Université Laval, Quebec, Quebec, Canada
| | - Melissa Southey
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Department of Clinical Pathology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Jennifer Stone
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Genetic Epidemiology Group, School of Population and Global Health, University of Western Australia, Perth, Western Australia, Australia
| | - William J Tapper
- Cancer Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Jack Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
- Epigenetic and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Lauren Teras
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Amanda E Toland
- Department of Cancer Biology and Genetics, The Ohio State University, Columbus, OH, USA
| | - Melissa Troester
- Department of Epidemiology, Gillings School of Global Public Health and UNC Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Thérèse Truong
- Team 'Exposome and Heredity', CESP, Gustave Roussy, INSERM, University Paris-Saclay, UVSQ, Villejuif, France
| | | | - Clarice Weinberg
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Camilla Wendt
- Department of Clinical Science and Education, Karolinska Institutet, Stockholm, Sweden
| | - Xiaohong Rose Yang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Argyrios Ziogas
- Department of Medicine, Genetic Epidemiology Research Institute, University of California Irvine, Irvine, CA, USA
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Paul Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, West Hollywood, CA, USA
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Shay Ben-Sachar
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
- Clalit Research Institute, Clalit Health Services, Ramat Gan, Israel
| | - Naama Elefant
- Clalit Research Institute, Clalit Health Services, Ramat Gan, Israel
- Department of Genetics, Hadassah Medical Center, Jerusalem, Israel
| | - Ron Shamir
- The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
| | - Ran Elkon
- Department of Human Molecular Genetics and Biochemistry, Tel Aviv University, Tel Aviv, Israel
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6
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Saya S, Boyd L, Chondros P, McNamara M, King M, Milton S, Lourenco RDA, Clark M, Fishman G, Marker J, Ostroff C, Allman R, Walter FM, Buchanan D, Winship I, McIntosh J, Macrae F, Jenkins M, Emery J. The SCRIPT trial: study protocol for a randomised controlled trial of a polygenic risk score to tailor colorectal cancer screening in primary care. Trials 2022; 23:810. [PMID: 36163034 PMCID: PMC9513012 DOI: 10.1186/s13063-022-06734-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 09/12/2022] [Indexed: 11/10/2022] Open
Abstract
Background Polygenic risk scores (PRSs) can predict the risk of colorectal cancer (CRC) and target screening more precisely than current guidelines using age and family history alone. Primary care, as a far-reaching point of healthcare and routine provider of cancer screening and risk information, may be an ideal location for their widespread implementation. Methods This trial aims to determine whether the SCRIPT intervention results in more risk-appropriate CRC screening after 12 months in individuals attending general practice, compared with standard cancer risk reduction information. The SCRIPT intervention consists of a CRC PRS, tailored risk-specific screening recommendations and a risk report for participants and their GP, delivered in general practice. Patients aged between 45 and 70 inclusive, attending their GP, will be approached for participation. For those over 50, only those overdue for CRC screening will be eligible to participate. Two hundred and seventy-four participants will be randomised to the intervention or control arms, stratified by general practice, using a computer-generated allocation sequence. The primary outcome is risk-appropriate CRC screening after 12 months. For those in the intervention arm, risk-appropriate screening is defined using PRS-derived risk; for those in the control arm, it is defined using family history and national screening guidelines. Timing, type and results of the previous screening are considered in both arms. Objective health service data will capture screening behaviour. Secondary outcomes include cancer-specific worry, risk perception, predictors of CRC screening behaviour, screening intentions and health service use at 1, 6 and 12 months post-intervention delivery. Discussion This trial aims to determine whether a PRS-derived personalised CRC risk estimate delivered in primary care increases risk-appropriate CRC screening. A future population risk-stratified CRC screening programme could incorporate risk assessment within primary care while encouraging adherence to targeted screening recommendations. Trial registration Australian and New Zealand Clinical Trial Registry ACTRN12621000092897p. Registered on 1 February 2021. Supplementary Information The online version contains supplementary material available at 10.1186/s13063-022-06734-7.
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Affiliation(s)
- Sibel Saya
- Primary Care Cancer Research Group, Department of General Practice, Centre for Cancer Research, The University of Melbourne, Victorian Comprehensive Cancer Centre, Level 10, 305 Grattan Street, Melbourne, Victoria, 3000, Australia. .,Centre for Cancer Research, University of Melbourne, Melbourne, Australia.
| | - Lucy Boyd
- Primary Care Cancer Research Group, Department of General Practice, Centre for Cancer Research, The University of Melbourne, Victorian Comprehensive Cancer Centre, Level 10, 305 Grattan Street, Melbourne, Victoria, 3000, Australia.,Centre for Cancer Research, University of Melbourne, Melbourne, Australia
| | - Patty Chondros
- Primary Care Cancer Research Group, Department of General Practice, Centre for Cancer Research, The University of Melbourne, Victorian Comprehensive Cancer Centre, Level 10, 305 Grattan Street, Melbourne, Victoria, 3000, Australia
| | - Mairead McNamara
- Primary Care Cancer Research Group, Department of General Practice, Centre for Cancer Research, The University of Melbourne, Victorian Comprehensive Cancer Centre, Level 10, 305 Grattan Street, Melbourne, Victoria, 3000, Australia.,Centre for Cancer Research, University of Melbourne, Melbourne, Australia
| | - Michelle King
- Primary Care Cancer Research Group, Department of General Practice, Centre for Cancer Research, The University of Melbourne, Victorian Comprehensive Cancer Centre, Level 10, 305 Grattan Street, Melbourne, Victoria, 3000, Australia.,Centre for Cancer Research, University of Melbourne, Melbourne, Australia
| | - Shakira Milton
- Primary Care Cancer Research Group, Department of General Practice, Centre for Cancer Research, The University of Melbourne, Victorian Comprehensive Cancer Centre, Level 10, 305 Grattan Street, Melbourne, Victoria, 3000, Australia.,Centre for Cancer Research, University of Melbourne, Melbourne, Australia
| | - Richard De Abreu Lourenco
- Centre for Health Economics Research and Evaluation, University of Technology Sydney, Sydney, Australia
| | | | - George Fishman
- Consumer Advisory Group, Primary Care Collaborative Cancer Clinical Trials Group, Carlton, Australia
| | - Julie Marker
- Consumer Advisory Group, Primary Care Collaborative Cancer Clinical Trials Group, Carlton, Australia
| | - Cheri Ostroff
- Centre for Workplace Excellence, University of South Australia, Adelaide, Australia
| | - Richard Allman
- Genetic Technologies/Phenogen Sciences, Fitzroy, Australia.,Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne, Australia
| | - Fiona M Walter
- Primary Care Cancer Research Group, Department of General Practice, Centre for Cancer Research, The University of Melbourne, Victorian Comprehensive Cancer Centre, Level 10, 305 Grattan Street, Melbourne, Victoria, 3000, Australia.,Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Daniel Buchanan
- Centre for Cancer Research, University of Melbourne, Melbourne, Australia.,Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne, Australia.,Department of Clinical Pathology, University of Melbourne, Melbourne, Australia
| | - Ingrid Winship
- Department of Medicine, Melbourne Medical School, University of Melbourne, Melbourne, Australia.,Genetic Medicine, Royal Melbourne Hospital, Melbourne, Australia
| | - Jennifer McIntosh
- Primary Care Cancer Research Group, Department of General Practice, Centre for Cancer Research, The University of Melbourne, Victorian Comprehensive Cancer Centre, Level 10, 305 Grattan Street, Melbourne, Victoria, 3000, Australia.,HumaniSE Lab, Department of Software Systems and Cybersecurity, Monash University, Clayton, Australia
| | - Finlay Macrae
- Department of Medicine, Melbourne Medical School, University of Melbourne, Melbourne, Australia.,Colorectal Medicine and Genetics, The Royal Melbourne Hospital, Melbourne, Australia
| | - Mark Jenkins
- Centre for Cancer Research, University of Melbourne, Melbourne, Australia.,Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne, Australia
| | - Jon Emery
- Primary Care Cancer Research Group, Department of General Practice, Centre for Cancer Research, The University of Melbourne, Victorian Comprehensive Cancer Centre, Level 10, 305 Grattan Street, Melbourne, Victoria, 3000, Australia.,Centre for Cancer Research, University of Melbourne, Melbourne, Australia
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7
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Dennison RA, Boscott RA, Thomas R, Griffin SJ, Harrison H, John SD, Moorthie SA, Morris S, Rossi SH, Stewart GD, Thomas CV, Usher‐Smith JA. A community jury study exploring the public acceptability of using risk stratification to determine eligibility for cancer screening. Health Expect 2022; 25:1789-1806. [PMID: 35526275 PMCID: PMC9327868 DOI: 10.1111/hex.13522] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Revised: 04/26/2022] [Accepted: 04/27/2022] [Indexed: 01/18/2023] Open
Abstract
INTRODUCTION Using risk stratification to determine eligibility for cancer screening is likely to improve the efficiency of screening programmes by targeting resources towards those most likely to benefit. We aimed to explore the implications of this approach from a societal perspective by understanding public views on the most acceptable stratification strategies. METHODS We conducted three online community juries with 9 or 10 participants in each. Participants were purposefully sampled by age (40-79 years), sex, ethnicity, social grade and English region. On the first day, participants were informed of the potential benefits and harms of cancer screening and the implications of different ways of introducing stratification using scenarios based on phenotypic and genetic risk scores. On the second day, participants deliberated to reach a verdict on the research question, 'Which approach(es) to inviting people to screening are acceptable, and under what circumstances?' Deliberations and feedback were recorded and analysed using thematic analysis. RESULTS Across the juries, the principle of risk stratification was generally considered to be an acceptable approach for determining eligibility for screening. Disregarding increasing capacity, the participants considered it to enable efficient resource allocation to high-risk individuals and could see how it might help to save lives. However, there were concerns regarding fair implementation, particularly how the risk assessment would be performed at scale and how people at low risk would be managed. Some favoured using the most accurate risk prediction model whereas others thought that certain risk factors should be prioritized (particularly factors considered as non-modifiable and relatively stable, such as genetics and family history). Transparently justifying the programme and public education about cancer risk emerged as important contributors to acceptability. CONCLUSION Using risk stratification to determine eligibility for cancer screening was acceptable to informed members of the public, particularly if it included risk factors they considered fair and when communicated transparently. PATIENT OR PUBLIC CONTRIBUTION Two patient and public involvement representatives were involved throughout this study. They were not involved in synthesizing the results but contributed to producing study materials, co-facilitated the community juries and commented on the interpretation of the findings and final report.
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Affiliation(s)
- Rebecca A. Dennison
- Primary Care Unit, Department of Public Health and Primary CareUniversity of CambridgeCambridgeUK
| | | | - Rae Thomas
- Institute for Evidence‐Based HealthcareBond UniversityGold CoastQueenslandAustralia
| | - Simon J. Griffin
- Primary Care Unit, Department of Public Health and Primary CareUniversity of CambridgeCambridgeUK
| | - Hannah Harrison
- Primary Care Unit, Department of Public Health and Primary CareUniversity of CambridgeCambridgeUK
| | - Stephen D. John
- Department of History and Philosophy of ScienceUniversity of CambridgeCambridgeUK
| | | | - Stephen Morris
- Primary Care Unit, Department of Public Health and Primary CareUniversity of CambridgeCambridgeUK
| | | | | | - Chloe V. Thomas
- School of Health and Related ResearchUniversity of SheffieldSheffieldUK
| | - Juliet A. Usher‐Smith
- Primary Care Unit, Department of Public Health and Primary CareUniversity of CambridgeCambridgeUK
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8
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Roux A, Cholerton R, Sicsic J, Moumjid N, French DP, Giorgi Rossi P, Balleyguier C, Guindy M, Gilbert FJ, Burrion JB, Castells X, Ritchie D, Keatley D, Baron C, Delaloge S, de Montgolfier S. Study protocol comparing the ethical, psychological and socio-economic impact of personalised breast cancer screening to that of standard screening in the "My Personal Breast Screening" (MyPeBS) randomised clinical trial. BMC Cancer 2022; 22:507. [PMID: 35524202 PMCID: PMC9073478 DOI: 10.1186/s12885-022-09484-6] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 04/02/2022] [Indexed: 12/11/2022] Open
Abstract
Background The MyPeBS study is an ongoing randomised controlled trial testing whether a risk-stratified breast cancer screening strategy is non-inferior, or eventually superior, to standard age-based screening at reducing incidence of stage 2 or more cancers. This large European Commission-funded initiative aims to include 85,000 women aged 40 to 70 years, without prior breast cancer and not previously identified at high risk in six countries (Belgium, France, Italy, Israel, Spain, UK). A specific work package within MyPeBS examines psychological, socio-economic and ethical aspects of this new screening strategy. It compares women’s reported data and outcomes in both trial arms on the following issues: general anxiety, cancer-related worry, understanding of breast cancer screening strategy and information-seeking behaviour, socio-demographic and economic characteristics, quality of life, risk perception, intention to change health-related behaviours, satisfaction with the trial. Methods At inclusion, 3-months, 1-year and 4-years, each woman participating in MyPeBS is asked to fill online questionnaires. Descriptive statistics, bivariate analyses, subgroup comparisons and analysis of variations over time will be performed with appropriate tests to assess differences between arms. Multivariate regression models will allow modelling of different patient reported data and outcomes such as comprehension of the information provided, general anxiety or cancer worry, and information seeking behaviour. In addition, a qualitative study (48 semi-structured interviews conducted in France and in the UK with women randomised in the risk-stratified arm), will help further understand participants’ acceptability and comprehension of the trial, and their experience of risk assessment. Discussion Beyond the scientific and medical objectives of this clinical study, it is critical to acknowledge the consequences of such a paradigm shift for women. Indeed, introducing a risk-based screening relying on individual biological differences also implies addressing non-biological differences (e.g. social status or health literacy) from an ethical perspective, to ensure equal access to healthcare. The results of the present study will facilitate making recommendations on implementation at the end of the trial to accompany any potential change in screening strategy. Trial registration Study sponsor: UNICANCER. My personalised breast screening (MyPeBS). Clinicaltrials.gov (2018) available at: https://clinicaltrials.gov/ct2/show/NCT03672331 Contact: Cécile VISSAC SABATIER, PhD, + 33 (0)1 73 79 77 58 ext + 330,142,114,293, contact@mypebs.eu. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-022-09484-6.
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Affiliation(s)
- Alexandra Roux
- IRIS (UMR8156 CNRS & U997 INSERM), Paris 13 University, Aubervilliers, France
| | | | | | - Nora Moumjid
- Université Lyon 1, P2S EA 4129, Centre Léon Bérard, F-69373, Lyon, France
| | | | | | | | - Michal Guindy
- Assuta Medical Centers, Tel Aviv, Israel.,Ben Gurion University, Beersheba, Israel
| | | | | | - Xavier Castells
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | | | | | | | - Suzette Delaloge
- Institut Gustave Roussy, Villejuif, France.,Unicancer, Paris, France
| | - Sandrine de Montgolfier
- IRIS (UMR8156 CNRS & U997 INSERM), Paris 13 University, Aubervilliers, France. .,Paris Est Creteil University, Créteil, France.
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9
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El Hadi C, Ayoub G, Bachir Y, Haykal M, Jalkh N, Kourie HR. Polygenic and Network-Based Studies in Risk Identification and Demystification of cancer. Expert Rev Mol Diagn 2022; 22:427-438. [PMID: 35400274 DOI: 10.1080/14737159.2022.2065195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Diseases were initially thought to be the consequence of a single gene mutation. Advances in DNA sequencing tools and our understanding of gene behavior have revealed that complex diseases, such as cancer, are the product of genes cooperating with each other and with their environment in orchestrated communication networks. Seeing that the function of individual genes is still used to analyze cancer, the shift to using functionally interacting groups of genes as a new unit of study holds promise for demystifying cancer. AREAS COVERED The literature search focused on three types of cancer, namely breast, lung, and prostate, but arguments from other cancers were also included. The aim was to prove that multigene analyses can accurately predict and prognosticate cancer risk, subtype cancer for more personalized and effective treatments, and discover anti-cancer therapies. Computational intelligence is being harnessed to analyze this type of data and is proving indispensable to scientific progress. EXPERT OPINION In the future, comprehensive profiling of all kinds of patient data (e.g., serum molecules, environmental exposures) can be used to build universal networks that should help us elucidate the molecular mechanisms underlying diseases and provide appropriate preventive measures, ensuring lifelong health and longevity.
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Affiliation(s)
| | - George Ayoub
- Faculty of Medicine, Saint Joseph University, Beirut, Lebanon
| | - Yara Bachir
- Faculty of Medicine, Saint Joseph University, Beirut, Lebanon
| | - Michèle Haykal
- Faculty of Medicine, Saint Joseph University, Beirut, Lebanon
| | - Nadine Jalkh
- Medical Genetics Unit, Technology and Health division, Faculty of Medicine, Saint Joseph University, Beirut, Lebanon
| | - Hampig Raphael Kourie
- Department of Hematology-Oncology, Hotel Dieu de France University Hospital, Faculty of Medicine, Saint Joseph University, Beirut, Lebanon
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10
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Canzian F, Piredda C, Macauda A, Zawirska D, Andersen NF, Nagler A, Zaucha JM, Mazur G, Dumontet C, Wątek M, Jamroziak K, Sainz J, Várkonyi J, Butrym A, Beider K, Abildgaard N, Lesueur F, Dudziński M, Vangsted AJ, Pelosini M, Subocz E, Petrini M, Buda G, Raźny M, Gemignani F, Marques H, Orciuolo E, Kadar K, Jurczyszyn A, Druzd-Sitek A, Vogel U, Andersen V, Reis RM, Suska A, Avet-Loiseau H, Kruszewski M, Tomczak W, Rymko M, Minvielle S, Campa D. A polygenic risk score for multiple myeloma risk prediction. Eur J Hum Genet 2022; 30:474-479. [PMID: 34845334 PMCID: PMC8991223 DOI: 10.1038/s41431-021-00986-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Revised: 10/04/2021] [Accepted: 10/08/2021] [Indexed: 12/24/2022] Open
Abstract
There is overwhelming epidemiologic evidence that the risk of multiple myeloma (MM) has a solid genetic background. Genome-wide association studies (GWAS) have identified 23 risk loci that contribute to the genetic susceptibility of MM, but have low individual penetrance. Combining the SNPs in a polygenic risk score (PRS) is a possible approach to improve their usefulness. Using 2361 MM cases and 1415 controls from the International Multiple Myeloma rESEarch (IMMEnSE) consortium, we computed a weighted and an unweighted PRS. We observed associations with MM risk with OR = 3.44, 95% CI 2.53-4.69, p = 3.55 × 10-15 for the highest vs. lowest quintile of the weighted score, and OR = 3.18, 95% CI 2.1 = 34-4.33, p = 1.62 × 10-13 for the highest vs. lowest quintile of the unweighted score. We found a convincing association of a PRS generated with 23 SNPs and risk of MM. Our work provides additional validation of previously discovered MM risk variants and of their combination into a PRS, which is a first step towards the use of genetics for risk stratification in the general population.
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Affiliation(s)
- Federico Canzian
- Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Chiara Piredda
- Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Biology, University of Pisa, Pisa, Italy
| | - Angelica Macauda
- Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Biology, University of Pisa, Pisa, Italy
| | - Daria Zawirska
- Department of Hematology, University Hospital of Cracow, Cracow, Poland
| | | | - Arnon Nagler
- Hematology Division, Chaim Sheba Medical Center, Tel Hashomer, Israel
| | | | - Grzegorz Mazur
- Department of Internal and Occupational Diseases, Hypertension and Clinical Oncology, Medical University Wroclaw, Wroclaw, Poland
| | - Charles Dumontet
- Cancer Research Center of Lyon/Hospices Civils de Lyon, Lyon, France
| | - Marzena Wątek
- Hematology Clinic, Holycross Cancer Center, Kielce, Poland
| | - Krzysztof Jamroziak
- Department of Hematology, Institute of Hematology and Transfusion Medicine, Warsaw, Poland
| | - Juan Sainz
- Genomic Oncology Area, GENYO. Centre for Genomics and Oncological Research: Pfizer, University of Granada/Andalusian Regional Government, Granada, Spain
- Hematology department, Virgen de las Nieves University Hospital, Granada, Spain
| | - Judit Várkonyi
- Third Department of Internal Medicine, Semmelweis University, Budapest, Hungary
| | - Aleksandra Butrym
- Department of Internal and Occupational Diseases, Medical University Wroclaw, Wroclaw, Poland
| | - Katia Beider
- Hematology Division, Chaim Sheba Medical Center, Tel Hashomer, Israel
| | - Niels Abildgaard
- Department of Hematology, Odense University Hospital, Odense, Denmark
| | - Fabienne Lesueur
- Institut Curie, PSL Research University, Mines ParisTech Inserm, U900, Paris, France
| | - Marek Dudziński
- Hematology Department, Teaching Hospital No 1, Rzeszów, Poland
| | - Annette Juul Vangsted
- Department of Hematology, Rigshospitalet, Copenhagen University, Copenhagen, Denmark
| | - Matteo Pelosini
- Clinical and Experimental Medicine, Section of Hematology, University of Pisa, Pisa, Italy
| | - Edyta Subocz
- Department of Haematology, Military Institute of Medicine, Warsaw, Poland
| | - Mario Petrini
- Clinical and Experimental Medicine, Section of Hematology, University of Pisa, Pisa, Italy
| | - Gabriele Buda
- Clinical and Experimental Medicine, Section of Hematology, University of Pisa, Pisa, Italy
| | - Małgorzata Raźny
- Department of Hematology, Rydygier Specialistic Hospital, Cracow, Poland
| | | | - Herlander Marques
- Life and Health Sciences Research Institute (ICVS), School of Health Sciences/Molecular Oncology Research Center, University of Minho, Braga, Portugal
| | - Enrico Orciuolo
- Clinical and Experimental Medicine, Section of Hematology, University of Pisa, Pisa, Italy
| | - Katalin Kadar
- Third Department of Internal Medicine, Semmelweis University, Budapest, Hungary
| | - Artur Jurczyszyn
- Department of Hematology, Jagiellonian University Medical College, Cracow, Poland
| | | | - Ulla Vogel
- National Research Centre for the Working Environment, DK-2100, Copenhagen, Denmark
| | - Vibeke Andersen
- Institute of Molecular Medicine, University of Southern Denmark, Odense, Denmark
| | - Rui Manuel Reis
- Life and Health Sciences Research Institute (ICVS), School of Health Sciences/Molecular Oncology Research Center, University of Minho, Braga, Portugal
- ICVS/3B's - PT Government Associate Laboratory, Braga/Guimarães, Portugal
- Molecular Oncology Research Center, Barretos Cancer Hospital, S.Paulo, Brazil
| | - Anna Suska
- Department of Hematology, Jagiellonian University Medical College, Cracow, Poland
| | - Hervé Avet-Loiseau
- Unité de Génomique du Myélome, Institut Universitaire du Cancer Toulouse - Oncopole, Toulouse, France
| | - Marcin Kruszewski
- Department of Hematology, University Hospital Bydgoszcz, Bydgoszcz, Poland
| | | | - Marcin Rymko
- Department of Hematology, N. Copernicus Town Hospital, Torun, Poland
| | - Stephane Minvielle
- CRCINA, INSERM, CNRS, Université d'Angers, Université de Nantes, Nantes, France
| | - Daniele Campa
- Department of Biology, University of Pisa, Pisa, Italy
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11
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Schmutzler RK, Schmitz-Luhn B, Borisch B, Devilee P, Eccles D, Hall P, Balmaña J, Boccia S, Dabrock P, Emons G, Gaissmaier W, Gronwald J, Houwaart S, Huster S, Kast K, Katalinic A, Linn SC, Moorthie S, Pharoah P, Rhiem K, Spranger T, Stoppa-Lyonnet D, van Delden JJM, van den Bulcke M, Woopen C. Risk-Adjusted Cancer Screening and Prevention (RiskAP): Complementing Screening for Early Disease Detection by a Learning Screening Based on Risk Factors. Breast Care (Basel) 2022; 17:208-223. [PMID: 35702492 PMCID: PMC9149472 DOI: 10.1159/000517182] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 03/22/2021] [Indexed: 01/04/2024] Open
Abstract
BACKGROUND Risk-adjusted cancer screening and prevention is a promising and continuously emerging option for improving cancer prevention. It is driven by increasing knowledge of risk factors and the ability to determine them for individual risk prediction. However, there is a knowledge gap between evidence of increased risk and evidence of the effectiveness and efficiency of clinical preventive interventions based on increased risk. This gap is, in particular, aggravated by the extensive availability of genetic risk factor diagnostics, since the question of appropriate preventive measures immediately arises when an increased risk is identified. However, collecting proof of effective preventive measures, ideally by prospective randomized preventive studies, typically requires very long periods of time, while the knowledge about an increased risk immediately creates a high demand for action. SUMMARY Therefore, we propose a risk-adjusted prevention concept that is based on the best current evidence making needed and appropriate preventive measures available, and which is constantly evaluated through outcome evaluation, and continuously improved based on these results. We further discuss the structural and procedural requirements as well as legal and socioeconomical aspects relevant for the implementation of this concept.
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Affiliation(s)
- Rita K. Schmutzler
- Center Familial Breast and Ovarian Cancer and Center of Integrated Oncology (CIO), University Hospital Cologne, Cologne, Germany
| | - Björn Schmitz-Luhn
- Cologne Center for Ethics, Rights, Economics, and Social Sciences of Health (ceres), University of Cologne, and Research Unit Ethics, University Hospital of Cologne, Cologne, Germany
| | - Bettina Borisch
- Institute of Global Health, University of Geneva, Geneva, Switzerland
| | - Peter Devilee
- Leids Universitair Medisch Zentrum, Universiteit Leiden, Leiden, The Netherlands
| | - Diana Eccles
- Clinical Trials Unit, University of Southampton, Southampton, United Kingdom
| | - Per Hall
- Karolinska Institutet, Stockholm, Sweden
| | - Judith Balmaña
- Vall d'Hebron Instituto de Oncologia (VHIO), Barcelona, Spain
| | - Stefania Boccia
- Sezione di Igiene, Instituto di Sanità Pubblica, Università Cattolica del Sacro Cuore, Rome, Italy
- Department of Woman and Child Health and Public Health − Public Health Area, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | | | - Günter Emons
- Uniklinik Göttingen, Georg-August-Universität Göttingen, Göttingen, Germany
| | - Wolfgang Gaissmaier
- Max-Planck-Institut für Bildungsforschung, Universität Konstanz, Konstanz, Germany
| | - Jacek Gronwald
- International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | | | - Stefan Huster
- Lehrstuhl für Öffentliches Recht, Sozial- und Gesundheitsrecht und Rechtsphilosophie, Ruhr-Universität Bochum, Bochum, Germany
| | - Karin Kast
- Center Familial Breast and Ovarian Cancer and Center of Integrated Oncology (CIO), University Hospital Cologne, Cologne, Germany
| | | | - Sabine C. Linn
- Departments of Medical Oncology and Molecular Pathology − Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Sowmiya Moorthie
- PHG Foundation, University of Cambridge, Cambridge, United Kingdom
| | - Paul Pharoah
- Department of Oncology, University of Cambridge, Cambridge, United Kingdom
| | - Kerstin Rhiem
- Center Familial Breast and Ovarian Cancer and Center of Integrated Oncology (CIO), University Hospital Cologne, Cologne, Germany
| | - Tade Spranger
- Center for Life Science & Law, Universität Bonn, Bonn, Germany
| | | | | | | | - Christiane Woopen
- Cologne Center for Ethics, Rights, Economics, and Social Sciences of Health (ceres), University of Cologne, and Research Unit Ethics, University Hospital of Cologne, Cologne, Germany
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12
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Hipp LE, Hulswit BB, Milliron KJ. Clinical Tools and Counseling Considerations for Breast Cancer Risk Assessment and Evaluation for Hereditary Cancer Risk. Best Pract Res Clin Obstet Gynaecol 2022; 82:12-29. [DOI: 10.1016/j.bpobgyn.2022.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 02/01/2022] [Accepted: 02/02/2022] [Indexed: 11/28/2022]
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13
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Yu T, Ye DM. The epidemiologic factors associated with breast density: A review. JOURNAL OF RESEARCH IN MEDICAL SCIENCES 2022; 27:53. [PMID: 36092490 PMCID: PMC9450246 DOI: 10.4103/jrms.jrms_962_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 01/14/2022] [Accepted: 01/26/2022] [Indexed: 11/04/2022]
Abstract
In recent years, some studies have evaluated the epidemiologic factors associated with breast density. However, the variant and inconsistent results exist. In addition, breast density has been proved to be a significant risk factor associated with breast cancer. Our review summarized the published studies and emphasized the crucial factors including epidemiological factors associated with breast density. In addition, we also discussed the potential reasons for the discrepant results with risk factors. To decrease the incidence and mortality rates for breast cancer, in clinical practice, breast density should be included for clinical risk models in addition to epidemiological factors, and physicians should get more concentrate on those women with risk factors and provide risk-based breast cancer screening regimens.
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14
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Current advances in prognostic and diagnostic biomarkers for solid cancers: Detection techniques and future challenges. Biomed Pharmacother 2021; 146:112488. [PMID: 34894516 DOI: 10.1016/j.biopha.2021.112488] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 11/19/2021] [Accepted: 11/30/2021] [Indexed: 12/20/2022] Open
Abstract
Solid cancers are one of the leading causes of cancer related deaths, characterized by rapid growth of tumour, and local and distant metastases. Current advances on multimodality care have substantially improved local control and metastasis-free survival of patients by resection of primary tumour. The major concern in disease prognosis is the timely detection of resectable or metastatic tumour, thus reinforcing the need for identification of biomarkers for premalignant lesions of solid cancer. This ultimately improves the outcome for the patients. Therefore, the purpose of this review is to update the recent advancements on prognostic and diagnostic biomarkers to enhance early detection of common solid cancers including, breast, lung, colorectal, prostate and stomach cancer. We also provide an insight into Food and Drug Administration (FDA)-approved solid cancers biomarkers; various conventional techniques used for detection of prognostic and diagnostic biomarkers and discuss approaches to turn challenges in this field into opportunities.
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15
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Yiangou K, Kyriacou K, Kakouri E, Marcou Y, Panayiotidis MI, Loizidou MA, Hadjisavvas A, Michailidou K. Combination of a 15-SNP Polygenic Risk Score and Classical Risk Factors for the Prediction of Breast Cancer Risk in Cypriot Women. Cancers (Basel) 2021; 13:cancers13184568. [PMID: 34572793 PMCID: PMC8468424 DOI: 10.3390/cancers13184568] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 09/03/2021] [Accepted: 09/08/2021] [Indexed: 12/26/2022] Open
Abstract
Simple Summary Breast cancer is the most commonly diagnosed type of cancer in women worldwide. Stratification of women based on their individual breast cancer risk could guide targeted preventative strategies and population screening. Integrated models that combine the effects of a polygenic risk score (PRS) with classical breast cancer risk factors could provide an individualized breast-cancer risk estimation. Although various studies have extensively evaluated the performance of such integrated models in populations of European ancestry, no previous studies have included individuals of Greek-Cypriot origin. To this end, we have assessed the predictive performance of a 15-SNP PRS (PRS15), in combination with classical breast-cancer risk factors, in women of Greek-Cypriot origin. This proof-of-concept study suggests that models combining genetic data with classical risk factors may be used in the future for the prediction of breast-cancer risk and, therefore, supports their potential clinical utility for targeted preventative strategies in Cypriot women. Abstract The PRS combines multiplicatively the effects of common low-risk single nucleotide polymorphisms (SNPs) and has the potential to be used for the estimation of an individual’s risk for a trait or disease. PRS has been successfully implemented for the prediction of breast cancer risk. The combination of PRS with classical breast cancer risk factors provides a more comprehensive risk estimation and could, thus, improve risk stratification and personalized preventative strategies. In this study, we assessed the predictive performance of the combined effect of PRS15 with classical breast-cancer risk factors in Cypriot women using 1109 cases and 1177 controls from the MASTOS study. The PRS15 was significantly associated with an increased breast cancer risk in Cypriot women OR (95% CI) 1.66 (1.25–2.19). The integrated risk model obtained an AUC (95% CI) 0.70 (0.67–0.72) and had the ability to stratify women according to their disease status at the extreme deciles. These results provide evidence that the combination of PRS with classical risk factors may be used in the future for the stratification of Cypriot women based on their disease risk, and support its potential clinical utility for targeted preventative actions and population screening.
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Affiliation(s)
- Kristia Yiangou
- Department of Cancer Genetics, Therapeutics and Ultrastructural Pathology, The Cyprus Institute of Neurology and Genetics, Nicosia 2371, Cyprus; (K.Y.); (K.K.); (M.I.P.); (M.A.L.)
- The Cyprus School of Molecular Medicine, The Cyprus Institute of Neurology and Genetics, Nicosia 2371, Cyprus
| | - Kyriacos Kyriacou
- Department of Cancer Genetics, Therapeutics and Ultrastructural Pathology, The Cyprus Institute of Neurology and Genetics, Nicosia 2371, Cyprus; (K.Y.); (K.K.); (M.I.P.); (M.A.L.)
- The Cyprus School of Molecular Medicine, The Cyprus Institute of Neurology and Genetics, Nicosia 2371, Cyprus
| | - Eleni Kakouri
- Department of Medical Oncology, Bank of Cyprus Oncology Center, Nicosia 2012, Cyprus; (E.K.); (Y.M.)
| | - Yiola Marcou
- Department of Medical Oncology, Bank of Cyprus Oncology Center, Nicosia 2012, Cyprus; (E.K.); (Y.M.)
| | - Mihalis I. Panayiotidis
- Department of Cancer Genetics, Therapeutics and Ultrastructural Pathology, The Cyprus Institute of Neurology and Genetics, Nicosia 2371, Cyprus; (K.Y.); (K.K.); (M.I.P.); (M.A.L.)
- The Cyprus School of Molecular Medicine, The Cyprus Institute of Neurology and Genetics, Nicosia 2371, Cyprus
| | - Maria A. Loizidou
- Department of Cancer Genetics, Therapeutics and Ultrastructural Pathology, The Cyprus Institute of Neurology and Genetics, Nicosia 2371, Cyprus; (K.Y.); (K.K.); (M.I.P.); (M.A.L.)
- The Cyprus School of Molecular Medicine, The Cyprus Institute of Neurology and Genetics, Nicosia 2371, Cyprus
| | - Andreas Hadjisavvas
- Department of Cancer Genetics, Therapeutics and Ultrastructural Pathology, The Cyprus Institute of Neurology and Genetics, Nicosia 2371, Cyprus; (K.Y.); (K.K.); (M.I.P.); (M.A.L.)
- The Cyprus School of Molecular Medicine, The Cyprus Institute of Neurology and Genetics, Nicosia 2371, Cyprus
- Correspondence: (A.H.); (K.M.)
| | - Kyriaki Michailidou
- The Cyprus School of Molecular Medicine, The Cyprus Institute of Neurology and Genetics, Nicosia 2371, Cyprus
- Biostatistics Unit, The Cyprus Institute of Neurology and Genetics, Nicosia 2371, Cyprus
- Correspondence: (A.H.); (K.M.)
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16
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Gao C, Polley EC, Hart SN, Huang H, Hu C, Gnanaolivu R, Lilyquist J, Boddicker NJ, Na J, Ambrosone CB, Auer PL, Bernstein L, Burnside ES, Eliassen AH, Gaudet MM, Haiman C, Hunter DJ, Jacobs EJ, John EM, Lindström S, Ma H, Neuhausen SL, Newcomb PA, O'Brien KM, Olson JE, Ong IM, Patel AV, Palmer JR, Sandler DP, Tamimi R, Taylor JA, Teras LR, Trentham-Dietz A, Vachon CM, Weinberg CR, Yao S, Weitzel JN, Goldgar DE, Domchek SM, Nathanson KL, Couch FJ, Kraft P. Risk of Breast Cancer Among Carriers of Pathogenic Variants in Breast Cancer Predisposition Genes Varies by Polygenic Risk Score. J Clin Oncol 2021; 39:2564-2573. [PMID: 34101481 PMCID: PMC8330969 DOI: 10.1200/jco.20.01992] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2020] [Revised: 02/19/2021] [Accepted: 04/20/2021] [Indexed: 12/11/2022] Open
Abstract
PURPOSE This study assessed the joint association of pathogenic variants (PVs) in breast cancer (BC) predisposition genes and polygenic risk scores (PRS) with BC in the general population. METHODS A total of 26,798 non-Hispanic white BC cases and 26,127 controls from predominately population-based studies in the Cancer Risk Estimates Related to Susceptibility consortium were evaluated for PVs in BRCA1, BRCA2, ATM, CHEK2, PALB2, BARD1, BRIP1, CDH1, and NF1. PRS based on 105 common variants were created using effect estimates from BC genome-wide association studies; the performance of an overall BC PRS and estrogen receptor-specific PRS were evaluated. The odds of BC based on the PVs and PRS were estimated using penalized logistic regression. The results were combined with age-specific incidence rates to estimate 5-year and lifetime absolute risks of BC across percentiles of PRS by PV status and first-degree family history of BC. RESULTS The estimated lifetime risks of BC among general-population noncarriers, based on 10th and 90th percentiles of PRS, were 9.1%-23.9% and 6.7%-18.2% for women with or without first-degree relatives with BC, respectively. Taking PRS into account, more than 95% of BRCA1, BRCA2, and PALB2 carriers had > 20% lifetime risks of BC, whereas, respectively, 52.5% and 69.7% of ATM and CHEK2 carriers without first-degree relatives with BC, and 78.8% and 89.9% of those with a first-degree relative with BC had > 20% risk. CONCLUSION PRS facilitates personalization of BC risk among carriers of PVs in predisposition genes. Incorporating PRS into BC risk estimation may help identify > 30% of CHEK2 and nearly half of ATM carriers below the 20% lifetime risk threshold, suggesting the addition of PRS may prevent overscreening and enable more personalized risk management approaches.
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Affiliation(s)
- Chi Gao
- Harvard T.H. Chan School of Public Health, Boston, MA
| | | | | | - Hongyan Huang
- Harvard T.H. Chan School of Public Health, Boston, MA
| | | | | | | | | | - Jie Na
- Mayo Clinic, Rochester, MN
| | | | - Paul L. Auer
- UWM Joseph J. Zilber School of Public Health, Milwaukee, WI
| | | | | | - A. Heather Eliassen
- Harvard T.H. Chan School of Public Health, Boston, MA
- Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Mia M. Gaudet
- Department of Population Science, American Cancer Society, Atlanta, GA
| | - Christopher Haiman
- Keck School of Medicine, University of Southern California, Los Angeles, CA
| | - David J. Hunter
- Harvard T.H. Chan School of Public Health, Boston, MA
- University of Oxford, Oxford, United Kingdom
| | - Eric J. Jacobs
- Department of Population Science, American Cancer Society, Atlanta, GA
| | | | - Sara Lindström
- Department of Epidemiology, University of Washington, Seattle, WA
- Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Huiyan Ma
- Beckman Research Institute of City of Hope, Duarte, CA
| | | | - Polly A. Newcomb
- Department of Epidemiology, University of Washington, Seattle, WA
- Fred Hutchinson Cancer Research Center, Seattle, WA
| | | | | | | | - Alpa V. Patel
- Department of Population Science, American Cancer Society, Atlanta, GA
| | - Julie R. Palmer
- Boston University School of Medicine and Slone Epidemiology Center, Boston, MA
| | - Dale P. Sandler
- National Institute of Environmental Health Sciences, Durham, NC
| | - Rulla Tamimi
- Population Health Sciences Department, Weill Cornell Medicine, New York, NY
| | - Jack A. Taylor
- National Institute of Environmental Health Sciences, Durham, NC
| | - Lauren R. Teras
- Department of Population Science, American Cancer Society, Atlanta, GA
| | | | | | | | - Song Yao
- Roswell Park Comprehensive Cancer Center, Buffalo, NY
| | | | | | - Susan M. Domchek
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | | | | | - Peter Kraft
- Harvard T.H. Chan School of Public Health, Boston, MA
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17
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Borde J, Ernst C, Wappenschmidt B, Niederacher D, Weber-Lassalle K, Schmidt G, Hauke J, Quante AS, Weber-Lassalle N, Horváth J, Pohl-Rescigno E, Arnold N, Rump A, Gehrig A, Hentschel J, Faust U, Dutrannoy V, Meindl A, Kuzyakova M, Wang-Gohrke S, Weber BHF, Sutter C, Volk AE, Giannakopoulou O, Lee A, Engel C, Schmidt MK, Antoniou AC, Schmutzler RK, Kuchenbaecker K, Hahnen E. Performance of Breast Cancer Polygenic Risk Scores in 760 Female CHEK2 Germline Mutation Carriers. J Natl Cancer Inst 2021; 113:893-899. [PMID: 33372680 PMCID: PMC8246885 DOI: 10.1093/jnci/djaa203] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Revised: 09/17/2020] [Accepted: 12/08/2020] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND Genome-wide association studies suggest that the combined effects of breast cancer (BC)-associated single nucleotide polymorphisms (SNPs) can improve BC risk stratification using polygenic risk scores (PRSs). The performance of PRSs in genome-wide association studies-independent clinical cohorts is poorly studied in individuals carrying mutations in moderately penetrant BC predisposition genes such as CHEK2. METHODS A total of 760 female CHEK2 mutation carriers were included; 561 women were affected with BC, of whom 74 developed metachronous contralateral BC (mCBC). For PRS calculations, 2 SNP sets covering 77 (SNP set 1, developed for BC risk stratification in women unselected for their BRCA1/2 germline mutation status) and 88 (SNP set 2, developed for BC risk stratification in female BRCA1/2 mutation carriers) BC-associated SNPs were used. All statistical tests were 2-sided. RESULTS Both SNP sets provided concordant PRS results at the individual level (r = 0.91, P < 2.20 × 10-16). Weighted cohort Cox regression analyses revealed statistically significant associations of PRSs with the risk for first BC. For SNP set 1, a hazard ratio of 1.71 per SD of the PRS was observed (95% confidence interval = 1.36 to 2.15, P = 3.87 × 10-6). PRSs identify a subgroup of CHEK2 mutation carriers with a predicted lifetime risk for first BC that exceeds the surveillance thresholds defined by international guidelines. Association of PRS with mCBC was examined via Cox regression analysis (SNP set 1 hazard ratio = 1.23, 95% confidence interval = 0.86 to 1.78, P = .26). CONCLUSIONS PRSs may be used to personalize risk-adapted preventive measures for women with CHEK2 mutations. Larger studies are required to assess the role of PRSs in mCBC predisposition.
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Affiliation(s)
- Julika Borde
- Center for Familial Breast and Ovarian Cancer, Center for Integrated Oncology (CIO), University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Corinna Ernst
- Center for Familial Breast and Ovarian Cancer, Center for Integrated Oncology (CIO), University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Barbara Wappenschmidt
- Center for Familial Breast and Ovarian Cancer, Center for Integrated Oncology (CIO), University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Dieter Niederacher
- Department of Gynecology and Obstetrics, University Hospital Duesseldorf, Heinrich-Heine University Duesseldorf, Duesseldorf, Germany
| | - Konstantin Weber-Lassalle
- Center for Familial Breast and Ovarian Cancer, Center for Integrated Oncology (CIO), University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Gunnar Schmidt
- Institute of Human Genetics, Hannover Medical School, Hannover, Germany
| | - Jan Hauke
- Center for Familial Breast and Ovarian Cancer, Center for Integrated Oncology (CIO), University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Anne S Quante
- Department of Gynecology and Obstetrics, Technical University Munich, University Hospital Rechts der Isar, Munich, Germany
| | - Nana Weber-Lassalle
- Center for Familial Breast and Ovarian Cancer, Center for Integrated Oncology (CIO), University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Judit Horváth
- Institute for Human Genetics, University Hospital Muenster, Muenster, Germany
| | - Esther Pohl-Rescigno
- Center for Familial Breast and Ovarian Cancer, Center for Integrated Oncology (CIO), University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Norbert Arnold
- Institute of Clinical Molecular Biology, Department of Gynaecology and Obstetrics, University Hospital of Schleswig-Holstein, Campus Kiel, Christian-Albrechts University Kiel, Kiel, Germany
| | - Andreas Rump
- Institute for Clinical Genetics, Technische Universitaet Dresden, Dresden, Germany
| | - Andrea Gehrig
- Institute of Human Genetics, Julius-Maximilians-Universität Würzburg, Würzburg, Germany
| | - Julia Hentschel
- Institute of Human Genetics, University of Leipzig Hospitals and Clinics, Leipzig, Germany
| | - Ulrike Faust
- Institute of Medical Genetics and Applied Genomics, University Hospital Tuebingen, Tuebingen, Germany
| | - Véronique Dutrannoy
- Institute of Medical and Human Genetics, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Alfons Meindl
- Department of Gynecology and Obstetrics, Ludwig-Maximilians-University Munich, University Hospital Munich, Munich, Germany
| | - Maria Kuzyakova
- Institute of Human Genetics, University Medical Center, Georg August University, Goettingen, Germany
| | - Shan Wang-Gohrke
- Department of Gynaecology and Obstetrics, University Hospital Ulm, Ulm, Germany
| | - Bernhard H. F Weber
- Institute of Human Genetics, University of Regensburg, Regensburg, Germany
- Institute of Clinical Human Genetics, University Hospital Regensburg, Regensburg, Germany
| | - Christian Sutter
- Institute of Human Genetics, University of Heidelberg, Heidelberg, Germany
| | - Alexander E Volk
- Institute of Human Genetics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Olga Giannakopoulou
- Division of Psychiatry, University College London, London, UK
- UCL Genetics Institute, University College London, London, UK
| | - Andrew Lee
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Christoph Engel
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
| | - Marjanka K Schmidt
- Division of Molecular Pathology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Antonis C Antoniou
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Rita K Schmutzler
- Center for Familial Breast and Ovarian Cancer, Center for Integrated Oncology (CIO), University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Karoline Kuchenbaecker
- Division of Psychiatry, University College London, London, UK
- UCL Genetics Institute, University College London, London, UK
| | - Eric Hahnen
- Center for Familial Breast and Ovarian Cancer, Center for Integrated Oncology (CIO), University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
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18
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van den Broek JJ, Schechter CB, van Ravesteyn NT, Janssens ACJW, Wolfson MC, Trentham-Dietz A, Simard J, Easton DF, Mandelblatt JS, Kraft P, de Koning HJ. Personalizing Breast Cancer Screening Based on Polygenic Risk and Family History. J Natl Cancer Inst 2021; 113:434-442. [PMID: 32853342 PMCID: PMC8599807 DOI: 10.1093/jnci/djaa127] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Revised: 08/10/2020] [Accepted: 08/18/2020] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND We assessed the clinical utility of a first-degree breast cancer family history and polygenic risk score (PRS) to inform screening decisions among women aged 30-50 years. METHODS Two established breast cancer models evaluated digital mammography screening strategies in the 1985 US birth cohort by risk groups defined by family history and PRS based on 313 single nucleotide polymorphisms. Strategies varied in initiation age (30, 35, 40, 45, and 50 years) and interval (annual, hybrid, biennial, triennial). The benefits (breast cancer deaths averted, life-years gained) and harms (false-positive mammograms, overdiagnoses) were compared with those seen with 3 established screening guidelines. RESULTS Women with a breast cancer family history who initiated biennial screening at age 40 years (vs 50 years) had a 36% (model range = 29%-40%) increase in life-years gained and 20% (model range = 16%-24%) more breast cancer deaths averted, but 21% (model range = 17%-23%) more overdiagnoses and 63% (model range = 62%-64%) more false positives. Screening tailored to PRS vs biennial screening from 50 to 74 years had smaller positive effects on life-years gained (20%) and breast cancer deaths averted (11%) but also smaller increases in overdiagnoses (10%) and false positives (26%). Combined use of family history and PRS vs biennial screening from 50 to 74 years had the greatest increase in life-years gained (29%) and breast cancer deaths averted (18%). CONCLUSIONS Our results suggest that breast cancer family history and PRS could guide screening decisions before age 50 years among women at increased risk for breast cancer but expected increases in overdiagnoses and false positives should be expected.
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Affiliation(s)
- Jeroen J van den Broek
- Department of Public Health, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Clyde B Schechter
- Departments of Family and Social Medicine and Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | | | | | - Michael C Wolfson
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada
| | - Amy Trentham-Dietz
- Carbone Cancer Center and Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Jacques Simard
- Department of Medicine, Centre de recherche du CHU de Québec-Université Laval, Québec, QC, Canada
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department Public Health, and Primary Care, University of Cambridge, Cambridge, UK
- Department of Oncology, University of Cambridge, Cambridge, UK
| | - Jeanne S Mandelblatt
- Department of Oncology, Georgetown-Lombardi Comprehensive Cancer Center, Georgetown University School of Medicine, Washington, DC, USA
| | - Peter Kraft
- Department of Biostatistics and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Harry J de Koning
- Department of Public Health, Erasmus University Medical Center, Rotterdam, the Netherlands
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19
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Usher‐Smith JA, Harvey‐Kelly LLW, Rossi SH, Harrison H, Griffin SJ, Stewart GD. Acceptability and potential impact on uptake of using different risk stratification approaches to determine eligibility for screening: A population-based survey. Health Expect 2021; 24:341-351. [PMID: 33264472 PMCID: PMC8077132 DOI: 10.1111/hex.13175] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Revised: 10/15/2020] [Accepted: 11/15/2020] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Using risk stratification approaches to determine eligibility has the potential to improve efficiency of screening. OBJECTIVES To compare the public acceptability and potential impact on uptake of using different approaches to determine eligibility for screening. DESIGN An online population-based survey of 668 adults in the UK aged 45-79 including a series of scenarios in the context of a potential kidney cancer screening programme in which eligibility was determined by age, sex, age and sex combined, a simple risk score (age, sex, body mass index, smoking status), a complex risk score additionally incorporating family history and lifestyle, or a genetic risk score. OUTCOME MEASURES We used multi-level ordinal logistic regression to compare acceptability and potential uptake within individuals and multivariable ordinal logistic regression differences between individuals. RESULTS Using sex, age and sex, or the simple risk score were less acceptable than age (P < .0001). All approaches were less acceptable to women than men. Over 70% were comfortable waiting until they were older if the complex risk score or genetics indicated a low risk. If told they were high risk, 85% would be more likely to take up screening. Being told they were low risk had no overall influence on uptake. CONCLUSIONS Varying the starting age of screening based on estimated risk from models incorporating phenotypic or genetic risk factors would be acceptable to most individuals and may increase uptake. PATIENT OR PUBLIC CONTRIBUTION Two members of the public contributed to the development of the survey and have commented on this paper.
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Affiliation(s)
- Juliet A. Usher‐Smith
- The Primary Care UnitDepartment of Public Health and Primary CareUniversity of CambridgeCambridgeUK
| | | | - Sabrina H. Rossi
- Department of OncologyUniversity of Cambridge, Addenbrooke’s Hospital, Cambridge Biomedical CampusCambridgeUK
| | - Hannah Harrison
- The Primary Care UnitDepartment of Public Health and Primary CareUniversity of CambridgeCambridgeUK
| | - Simon J. Griffin
- The Primary Care UnitDepartment of Public Health and Primary CareUniversity of CambridgeCambridgeUK
| | - Grant D. Stewart
- Department of SurgeryUniversity of Cambridge, Addenbrooke’s Hospital, Cambridge Biomedical CampusCambridgeUK
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20
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Pashayan N, Antoniou AC, Ivanus U, Esserman LJ, Easton DF, French D, Sroczynski G, Hall P, Cuzick J, Evans DG, Simard J, Garcia-Closas M, Schmutzler R, Wegwarth O, Pharoah P, Moorthie S, De Montgolfier S, Baron C, Herceg Z, Turnbull C, Balleyguier C, Rossi PG, Wesseling J, Ritchie D, Tischkowitz M, Broeders M, Reisel D, Metspalu A, Callender T, de Koning H, Devilee P, Delaloge S, Schmidt MK, Widschwendter M. Personalized early detection and prevention of breast cancer: ENVISION consensus statement. Nat Rev Clin Oncol 2020; 17:687-705. [PMID: 32555420 PMCID: PMC7567644 DOI: 10.1038/s41571-020-0388-9] [Citation(s) in RCA: 154] [Impact Index Per Article: 38.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/06/2020] [Indexed: 02/07/2023]
Abstract
The European Collaborative on Personalized Early Detection and Prevention of Breast Cancer (ENVISION) brings together several international research consortia working on different aspects of the personalized early detection and prevention of breast cancer. In a consensus conference held in 2019, the members of this network identified research areas requiring development to enable evidence-based personalized interventions that might improve the benefits and reduce the harms of existing breast cancer screening and prevention programmes. The priority areas identified were: 1) breast cancer subtype-specific risk assessment tools applicable to women of all ancestries; 2) intermediate surrogate markers of response to preventive measures; 3) novel non-surgical preventive measures to reduce the incidence of breast cancer of poor prognosis; and 4) hybrid effectiveness-implementation research combined with modelling studies to evaluate the long-term population outcomes of risk-based early detection strategies. The implementation of such programmes would require health-care systems to be open to learning and adapting, the engagement of a diverse range of stakeholders and tailoring to societal norms and values, while also addressing the ethical and legal issues. In this Consensus Statement, we discuss the current state of breast cancer risk prediction, risk-stratified prevention and early detection strategies, and their implementation. Throughout, we highlight priorities for advancing each of these areas.
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Affiliation(s)
- Nora Pashayan
- Department of Applied Health Research, Institute of Epidemiology and Healthcare, University College London, London, UK
| | - Antonis C Antoniou
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Urska Ivanus
- Epidemiology and Cancer Registry, Institute of Oncology Ljubljana, Ljubljana, Slovenia
| | - Laura J Esserman
- Carol Franc Buck Breast Care Center, University of California, San Francisco, CA, USA
| | - Douglas F Easton
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - David French
- Division of Psychology & Mental Health, School of Health Sciences, University of Manchester, Manchester, UK
| | - Gaby Sroczynski
- Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT-University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
- Division of Health Technology Assessment, Oncotyrol - Center for Personalized Cancer Medicine, Innsbruck, Austria
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Oncology, Södersjukhuset, Stockholm, Sweden
| | - Jack Cuzick
- Wolfson Institute of Preventive Medicine, Barts and The London, Centre for Cancer Prevention, Queen Mary University of London, London, UK
| | - D Gareth Evans
- Division of Evolution and Genomic Sciences, University of Manchester, Manchester, UK
| | - Jacques Simard
- Genomics Center, CHU de Québec - Université Laval Research Center, Québec, Canada
| | | | - Rita Schmutzler
- Center of Family Breast and Ovarian Cancer, University Hospital Cologne, Cologne, Germany
| | - Odette Wegwarth
- Max Planck Institute for Human Development, Center for Adaptive Rationality, Harding Center for Risk Literacy, Berlin, Germany
| | - Paul Pharoah
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Department of Oncology, University of Cambridge, Cambridge, UK
| | | | | | | | - Zdenko Herceg
- Epigenetic Group, International Agency for Research on Cancer (IARC), WHO, Lyon, France
| | - Clare Turnbull
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
| | | | - Paolo Giorgi Rossi
- Epidemiology Unit, Azienda USL di Reggio Emilia - IRCCS, Reggio Emilia, Italy
| | - Jelle Wesseling
- Division of Molecular Pathology, Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, Netherlands
| | - David Ritchie
- Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Marc Tischkowitz
- Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, UK
| | - Mireille Broeders
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, Netherlands
| | - Dan Reisel
- Department of Women's Cancer, Institute for Women's Health, University College London, London, UK
| | - Andres Metspalu
- The Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Thomas Callender
- Department of Applied Health Research, Institute of Epidemiology and Healthcare, University College London, London, UK
| | - Harry de Koning
- Department of Public Health, Erasmus MC, Rotterdam, Netherlands
| | - Peter Devilee
- Department of Human Genetics, Department of Pathology, Leiden University Medical Centre, Leiden, Netherlands
| | - Suzette Delaloge
- Breast Cancer Department, Gustave Roussy Institute, Paris, France
| | - Marjanka K Schmidt
- Division of Molecular Pathology, Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, Netherlands
| | - Martin Widschwendter
- Department of Women's Cancer, Institute for Women's Health, University College London, London, UK.
- Universität Innsbruck, Innsbruck, Austria.
- European Translational Oncology Prevention and Screening (EUTOPS) Institute, Hall in Tirol, Austria.
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21
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Sipeky C, Talala KM, Tammela TLJ, Taari K, Auvinen A, Schleutker J. Prostate cancer risk prediction using a polygenic risk score. Sci Rep 2020; 10:17075. [PMID: 33051487 PMCID: PMC7553910 DOI: 10.1038/s41598-020-74172-z] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Accepted: 09/24/2020] [Indexed: 01/29/2023] Open
Abstract
Hereditary factors have a strong influence on prostate cancer (PC) risk and poorer outcomes, thus stratification by genetic factors addresses a critical need for targeted PC screening and risk-adapted follow-up. In this Finnish population-based retrospective study 2283 clinically diagnosed and 455 screen-detected patients from the Finnish Randomised Study of Screening for Prostate Cancer (FinRSPC), 2400 healthy individuals have been involved. Individual genetic risk through establishment of a polygenic risk score based on 55 PC risk SNPs identified through the Finnish subset of the Collaborative Oncological Gene-Environment Study was assessed. Men with PC had significantly higher median polygenic risk score compared to the controls (6.59 vs. 3.83, P < 0.0001). The polygenic risk score above the control median was a significant predictor of PC (OR 2.13, 95% CI 1.90-2.39). The polygenic risk score predicted the risk of PC with an AUC of 0.618 (95% CI 0.60-0.63). Men in the highest polygenic risk score quartile were 2.8-fold (95% CI 2.4-3.30) more likely to develop PC compared with men in the lowest quartile. In the FinRSPC cohort, a significantly higher percentage of men had a PSA level of ≥ 4 ng/mL in polygenic risk score quartile four compared to quartile one (18.7% vs 8.3%, P < 0.00001). Adding the PRS to a PSA-only model contributed additional information in predicting PC in the FinRSPC model. Results strongly suggest that use of the polygenic risk score would facilitate the identification of men at increased risk for PC.
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Affiliation(s)
- Csilla Sipeky
- Institute of Biomedicine, University of Turku, Kiinamyllynkatu 10, 20520, Turku, Finland
| | - Kirsi M Talala
- Finnish Cancer Registry, Mass Screening Registry, Helsinki, Finland
| | - Teuvo L J Tammela
- Department of Urology, Tampere University Hospital and Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Kimmo Taari
- Department of Urology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Anssi Auvinen
- Unit of Health Sciences, Faculty of Social Sciences, Tampere University, Tampere, Finland
| | - Johanna Schleutker
- Institute of Biomedicine, University of Turku, Kiinamyllynkatu 10, 20520, Turku, Finland.
- Department of Medical Genetics, Genomics, Laboratory Division, Turku University Hospital, Turku, Finland.
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22
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Lo SN, Smit AK, Espinoza D, Cust AE. The Melanoma Genomics Managing Your Risk Study randomised controlled trial: statistical analysis plan. Trials 2020; 21:594. [PMID: 32605576 PMCID: PMC7329549 DOI: 10.1186/s13063-020-04351-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Accepted: 04/25/2020] [Indexed: 01/11/2023] Open
Abstract
Background The Melanoma Genomics Managing Your Risk Study is a randomised controlled trial that aims to evaluate the efficacy of providing information on personal genomic risk of melanoma in reducing ultraviolet radiation (UV) exposure, stratified by traditional risk group (low or high phenotypic risk) in the general population. The primary outcome is objectively measured total daily Standard Erythemal Doses at 12 months. Secondary outcomes include UV exposure at specific time periods, self-reported sun protection and skin-examination behaviours, psychosocial outcomes, and ethical considerations surrounding offering genomic testing at a population level. A within-trial and modelled economic evaluation will be undertaken from an Australian health system perspective to assess the cost-effectiveness of the intervention. Objective To publish the pre-determined statistical analysis plan (SAP) before database lock and the start of analysis. Methods This SAP describes the data synthesis, analysis principles and statistical procedures for analysing the outcomes from this trial. The SAP was approved after closure of recruitment and before completion of patient follow-up. It outlines the planned primary analyses and a range of subgroup and sensitivity analyses. Health economic outcomes are not included in this plan but will be analysed separately. The SAP will be adhered to for the final data analysis of this trial to avoid potential analysis bias that may arise from knowledge of the outcome data. Results This SAP is consistent with best practice and should enable transparent reporting. Conclusion This SAP has been developed for the Melanoma Genomics Managing Your Risk Study and will be followed to ensure high-quality standards of internal validity and to minimise analysis bias. Trial registration Prospectively registered with the Australian New Zealand Clinical Trials Registry, ID: ACTR N12617000691347. Registered on 15 May 2017.
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Affiliation(s)
- Serigne N Lo
- The University of Sydney, Melanoma Institute Australia, Sydney, NSW, Australia
| | - Amelia K Smit
- The University of Sydney, Melanoma Institute Australia, Sydney, NSW, Australia.,The University of Sydney, Faculty of Medicine and Health, Sydney School of Public Health, Cancer Epidemiology and Prevention Research, Sydney, NSW, Australia.,The University of Sydney, Faculty of Medicine and Health, Sydney School of Public Health, Sydney Health Ethics, Sydney, NSW, Australia
| | - David Espinoza
- The University of Sydney, NHMRC Clinical Trials Centre, Sydney, NSW, Australia
| | - Anne E Cust
- The University of Sydney, Melanoma Institute Australia, Sydney, NSW, Australia. .,The University of Sydney, Faculty of Medicine and Health, Sydney School of Public Health, Cancer Epidemiology and Prevention Research, Sydney, NSW, Australia.
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23
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Rainey L, van der Waal D, Jervaeus A, Donnelly LS, Evans DG, Hammarström M, Hall P, Wengström Y, Broeders MJM. European women's perceptions of the implementation and organisation of risk-based breast cancer screening and prevention: a qualitative study. BMC Cancer 2020; 20:247. [PMID: 32209062 PMCID: PMC7092605 DOI: 10.1186/s12885-020-06745-0] [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: 01/08/2020] [Accepted: 03/12/2020] [Indexed: 01/28/2023] Open
Abstract
Background Increased knowledge of breast cancer risk factors has meant that we are currently exploring risk-based screening, i.e. determining screening strategies based on women’s varying levels of risk. This also enables risk management through primary prevention strategies, e.g. a lifestyle programme or risk-reducing medication. However, future implementation of risk-based screening and prevention will warrant significant changes in current practice and policy. The present study explores women’s perceptions of the implementation and organisation of risk-based breast cancer screening and prevention to optimise acceptability and uptake. Methods A total of 143 women eligible for breast cancer screening in the Netherlands, the United Kingdom, and Sweden participated in focus group discussions. The focus group discussions were transcribed verbatim and the qualitative data was analysed using thematic analysis. Results Women from all three countries generally agreed on the overall proceedings, e.g. a risk assessment after which the risk estimate is communicated via letter (for below average and average risk) or consultation (for moderate and high risk). However, discrepancies in information needs, preferred risk communication format and risk counselling professional were identified between countries. Additionally, a need to educate healthcare professionals on all aspects of the risk-based screening and prevention programme was established. Conclusion Women’s insights identified the need for country-specific standardised protocols regarding the assessment and communication of risk, and the provision of heterogeneous screening and prevention recommendations, monitoring the principle of solidarity in healthcare policy.
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Affiliation(s)
- Linda Rainey
- Radboud Institute for Health Sciences, Radboud university medical center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands.
| | - Daniëlle van der Waal
- Radboud Institute for Health Sciences, Radboud university medical center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands
| | - Anna Jervaeus
- Department of Neurobiology, Care Sciences and Society, Division of Nursing, Karolinska Institutet, Alfred, Nobels allé 23, 23300, 14183, Huddinge, Sweden
| | - Louise S Donnelly
- Prevent Breast Cancer Research Unit, The Nightingale Centre, Manchester University NHS Foundation Trust, Southmoor Road, Manchester, M23 9LT, UK
| | - D Gareth Evans
- Prevent Breast Cancer Research Unit, The Nightingale Centre, Manchester University NHS Foundation Trust, Southmoor Road, Manchester, M23 9LT, UK.,Genomic Medicine, Division of Evolution and Genomic Sciences, Manchester Academic Health Sciences Centre, Manchester University NHS Foundation Trust, Manchester, M13 9WL, UK.,The Christie NHS Foundation Trust, Withington, Manchester, M20 4BX, UK
| | - Mattias Hammarström
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, 171 77, Stockholm, Sweden
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, 171 77, Stockholm, Sweden.,Department of Oncology, Södersjukhuset, Sjukhusbacken 10, 118 83, Stockholm, Sweden
| | - Yvonne Wengström
- Department of Neurobiology, Care Sciences and Society, Division of Nursing, Karolinska Institutet, Alfred, Nobels allé 23, 23300, 14183, Huddinge, Sweden.,Theme Cancer, Karolinska University Hospital, Alfred Nobels allé 23, 23300, 14183, Huddinge, Sweden
| | - Mireille J M Broeders
- Radboud Institute for Health Sciences, Radboud university medical center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands.,Dutch Expert Centre for Screening, PO Box 6873, 6503 GJ, Nijmegen, The Netherlands
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24
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25
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Bayne M, Fairey M, Silarova B, Griffin SJ, Sharp SJ, Klein WMP, Sutton S, Usher-Smith JA. Effect of interventions including provision of personalised cancer risk information on accuracy of risk perception and psychological responses: A systematic review and meta-analysis. PATIENT EDUCATION AND COUNSELING 2020; 103:83-95. [PMID: 31439435 PMCID: PMC6919334 DOI: 10.1016/j.pec.2019.08.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Revised: 07/23/2019] [Accepted: 08/08/2019] [Indexed: 05/21/2023]
Abstract
OBJECTIVE To synthesize the literature on the effect of provision of personalised cancer risk information to individuals at population level risk on accuracy of risk perception and psychological responses. METHODS A systematic review and random effects meta-analysis of articles published from 01/01/2000 to 01/07/2017. RESULTS We included 23 studies. Immediately after provision of risk information 87% of individuals were able to recall the absolute risk estimate. Less than half believed that to be their risk, with up to 71% believing their risk to be higher than the estimate. Provision of risk information increased accuracy of perceived absolute risk immediately after risk information compared with no information (pooled RR 4.16 (95%CI 1.28-13.49), 3 studies). There was no significant effect on comparative risk accuracy (pooled RR 1.39 (0.72-2.69), 2 studies) and either no change or a reduction in cancer worry, anxiety and fear. CONCLUSION These findings highlight the complex cognitive processes involved in the conceptualisation of risk. PRACTICE IMPLICATIONS Individuals who appear to understand and are able to recall risk information most likely do not believe it reflects their own risk.
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Affiliation(s)
- Max Bayne
- University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Madi Fairey
- University of Cambridge School of Clinical Medicine, Cambridge, UK
| | | | - Simon J Griffin
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Stephen J Sharp
- MRC Epidemiology Unit, University of Cambridge, Cambridge UK
| | - William M P Klein
- Behavioral Research Program, National Cancer Institute, Rockville, MD, USA
| | - Stephen Sutton
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Juliet A Usher-Smith
- The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
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26
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Abraham G, Malik R, Yonova-Doing E, Salim A, Wang T, Danesh J, Butterworth AS, Howson JMM, Inouye M, Dichgans M. Genomic risk score offers predictive performance comparable to clinical risk factors for ischaemic stroke. Nat Commun 2019; 10:5819. [PMID: 31862893 PMCID: PMC6925280 DOI: 10.1038/s41467-019-13848-1] [Citation(s) in RCA: 84] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Accepted: 11/28/2019] [Indexed: 01/17/2023] Open
Abstract
Recent genome-wide association studies in stroke have enabled the generation of genomic risk scores (GRS) but their predictive power has been modest compared to established stroke risk factors. Here, using a meta-scoring approach, we develop a metaGRS for ischaemic stroke (IS) and analyse this score in the UK Biobank (n = 395,393; 3075 IS events by age 75). The metaGRS hazard ratio for IS (1.26, 95% CI 1.22-1.31 per metaGRS standard deviation) doubles that of a previous GRS, identifying a subset of individuals at monogenic levels of risk: the top 0.25% of metaGRS have three-fold risk of IS. The metaGRS is similarly or more predictive compared to several risk factors, such as family history, blood pressure, body mass index, and smoking. We estimate the reductions needed in modifiable risk factors for individuals with different levels of genomic risk and suggest that, for individuals with high metaGRS, achieving risk factor levels recommended by current guidelines may be insufficient to mitigate risk.
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Affiliation(s)
- Gad Abraham
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- Department of Clinical Pathology, University of Melbourne, Parkville, VIC, Australia.
| | - Rainer Malik
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universität LMU, Munich, Germany
| | - Ekaterina Yonova-Doing
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Agus Salim
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- Department of Mathematics and Statistics, La Trobe University, Melbourne, VIC, Australia
| | - Tingting Wang
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - John Danesh
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- Department of Human Genetics, Wellcome Sanger Institute, Hinxton, UK
| | - Adam S Butterworth
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- Department of Human Genetics, Wellcome Sanger Institute, Hinxton, UK
| | - Joanna M M Howson
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- Department of Clinical Pathology, University of Melbourne, Parkville, VIC, Australia.
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.
- The Alan Turing Institute, London, UK.
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universität LMU, Munich, Germany.
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.
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27
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Callender T, Emberton M, Morris S, Eeles R, Kote-Jarai Z, Pharoah PDP, Pashayan N. Polygenic risk-tailored screening for prostate cancer: A benefit-harm and cost-effectiveness modelling study. PLoS Med 2019; 16:e1002998. [PMID: 31860675 PMCID: PMC6924639 DOI: 10.1371/journal.pmed.1002998] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Accepted: 11/19/2019] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND The United States Preventive Services Task Force supports individualised decision-making for prostate-specific antigen (PSA)-based screening in men aged 55-69. Knowing how the potential benefits and harms of screening vary by an individual's risk of developing prostate cancer could inform decision-making about screening at both an individual and population level. This modelling study examined the benefit-harm tradeoffs and the cost-effectiveness of a risk-tailored screening programme compared to age-based and no screening. METHODS AND FINDINGS A life-table model, projecting age-specific prostate cancer incidence and mortality, was developed of a hypothetical cohort of 4.48 million men in England aged 55 to 69 years with follow-up to age 90. Risk thresholds were based on age and polygenic profile. We compared no screening, age-based screening (quadrennial PSA testing from 55 to 69), and risk-tailored screening (men aged 55 to 69 years with a 10-year absolute risk greater than a threshold receive quadrennial PSA testing from the age they reach the risk threshold). The analysis was undertaken from the health service perspective, including direct costs borne by the health system for risk assessment, screening, diagnosis, and treatment. We used probabilistic sensitivity analyses to account for parameter uncertainty and discounted future costs and benefits at 3.5% per year. Our analysis should be considered cautiously in light of limitations related to our model's cohort-based structure and the uncertainty of input parameters in mathematical models. Compared to no screening over 35 years follow-up, age-based screening prevented the most deaths from prostate cancer (39,272, 95% uncertainty interval [UI]: 16,792-59,685) at the expense of 94,831 (95% UI: 84,827-105,630) overdiagnosed cancers. Age-based screening was the least cost-effective strategy studied. The greatest number of quality-adjusted life-years (QALYs) was generated by risk-based screening at a 10-year absolute risk threshold of 4%. At this threshold, risk-based screening led to one-third fewer overdiagnosed cancers (64,384, 95% UI: 57,382-72,050) but averted 6.3% fewer (9,695, 95% UI: 2,853-15,851) deaths from prostate cancer by comparison with age-based screening. Relative to no screening, risk-based screening at a 4% 10-year absolute risk threshold was cost-effective in 48.4% and 57.4% of the simulations at willingness-to-pay thresholds of GBP£20,000 (US$26,000) and £30,000 ($39,386) per QALY, respectively. The cost-effectiveness of risk-tailored screening improved as the threshold rose. CONCLUSIONS Based on the results of this modelling study, offering screening to men at higher risk could potentially reduce overdiagnosis and improve the benefit-harm tradeoff and the cost-effectiveness of a prostate cancer screening program. The optimal threshold will depend on societal judgements of the appropriate balance of benefits-harms and cost-effectiveness.
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Affiliation(s)
- Tom Callender
- Department of Applied Health Research, Institute of Epidemiology & Health Care, University College London, London, United Kingdom
| | - Mark Emberton
- Faculty of Medical Sciences, School of Life & Medical Sciences, University College London, London, United Kingdom
| | - Steve Morris
- Department of Applied Health Research, Institute of Epidemiology & Health Care, University College London, London, United Kingdom
| | - Ros Eeles
- The Institute of Cancer Research, London, United Kingdom
| | | | - Paul D. P. Pharoah
- Departments of Oncology, and Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, Cambridge, United Kingdom
| | - Nora Pashayan
- Department of Applied Health Research, Institute of Epidemiology & Health Care, University College London, London, United Kingdom
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Dutil J, Teer JK, Golubeva V, Yoder S, Tong WL, Arroyo N, Karam R, Echenique M, Matta JL, Monteiro AN. Germline variants in cancer genes in high-risk non-BRCA patients from Puerto Rico. Sci Rep 2019; 9:17769. [PMID: 31780696 PMCID: PMC6882826 DOI: 10.1038/s41598-019-54170-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2019] [Accepted: 11/05/2019] [Indexed: 12/30/2022] Open
Abstract
Inherited pathogenic variants in genes that confer moderate to high risk of breast cancer may explain up to 50% of familial breast cancer. This study aimed at identifying inherited pathogenic variants in breast cancer cases from Puerto Rico that were not linked to BRCA1 or BRCA2. Forty-eight breast cancer patients that met the clinical criteria for BRCA testing but had received a negative BRCA1/2 result were recruited. Fifty-three genes previously implicated in hereditary cancer predisposition were captured using the BROCA Agilent cancer risk panel followed by massively parallel sequencing. Missense variants of uncertain clinical significance in CHEK2 were evaluated using an in vitro kinase assays to determine their impact on function. Pathogenic variants were identified in CHEK2, MUTYH, and RAD51B in four breast cancer patients, which represented 8.3% of the cohort. We identified three rare missense variants of uncertain significance in CHEK2 and two variants (p.Pro484Leu and p.Glu239Lys) showed markedly decreased kinase activity in vitro comparable to a known pathogenic variant. Interestingly, the local ancestry at the RAD51B locus in the carrier of p.Arg47* was predicted to be of African origin. In this cohort, 12.5% of the BRCA-negative breast cancer patients were found to carry a known pathogenic variant or a variant affecting protein activity. This study reveals an unmet clinical need of genetic testing that could benefit a significant proportion of at-risk Latinas. It also highlights the complexity of Hispanic populations as pathogenic factors may originate from any of the ancestral populations that make up their genetic backgrounds.
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Affiliation(s)
- Julie Dutil
- Cancer Biology Division, Ponce Research Institute, Ponce Health Sciences University, Ponce, PR, USA.
| | - Jamie K Teer
- Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Volha Golubeva
- Cancer Epidemiology Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Sean Yoder
- Molecular Genomics Core, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Wei Lue Tong
- University of South Florida Morsani College of Medicine, Tampa, FL, USA
| | - Nelly Arroyo
- Cancer Biology Division, Ponce Research Institute, Ponce Health Sciences University, Ponce, PR, USA
| | | | - Miguel Echenique
- Auxilio Cancer Center, Auxilio Mutuo Hospital, San Juan, PR, USA
| | - Jaime L Matta
- Cancer Biology Division, Ponce Research Institute, Ponce Health Sciences University, Ponce, PR, USA
| | - Alvaro N Monteiro
- Cancer Epidemiology Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
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Guan Z, Raut JR, Weigl K, Schöttker B, Holleczek B, Zhang Y, Brenner H. Individual and joint performance of DNA methylation profiles, genetic risk score and environmental risk scores for predicting breast cancer risk. Mol Oncol 2019; 14:42-53. [PMID: 31677238 PMCID: PMC6944111 DOI: 10.1002/1878-0261.12594] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 08/30/2019] [Accepted: 10/24/2019] [Indexed: 12/24/2022] Open
Abstract
DNA methylation patterns in the blood, genetic risk scores (GRSs), and environmental risk factors can potentially improve breast cancer (BC) risk prediction. We assessed the individual and joint predictive performance of methylation, GRS, and environmental risk factors for BC incidence in a prospective cohort study. In a cohort of 5462 women aged 50–75 from Germany, 101 BC cases were identified during 14 years of follow‐up and were compared to 263 BC‐free controls in a nested case–control design. Three previously suggested methylation risk scores (MRSs) based on methylation of 423, 248, and 131 cytosine‐phosphate‐guanine (CpG) loci, and a GRS based on the risk alleles from 269 recently identified single nucleotide polymorphisms were constructed. Additionally, multiple previously proposed environmental risk scores (ERSs) were built based on environmental variables. Areas under the receiver operating characteristic curves (AUCs) were estimated for evaluating BC risk prediction performance. MRS and ERS showed limited accuracy in predicting BC incidence, with AUCs ranging from 0.52 to 0.56 and from 0.52 to 0.59, respectively. The GRS predicted BC incidence with a higher accuracy (AUC = 0.61). Adjusted odds ratios per standard deviation increase (95% confidence interval) were 1.07 (0.84–1.36) and 1.40 (1.09–1.80) for the best performing MRS and ERS, respectively, and 1.48 (1.16–1.90) for the GRS. A full risk model combining the MRS, GRS, and ERS predicted BC incidence with the highest accuracy (AUC = 0.64) and might be useful for identifying high‐risk populations for BC screening.
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Affiliation(s)
- Zhong Guan
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Medical Faculty Heidelberg, University of Heidelberg, Germany
| | - Janhavi R Raut
- Medical Faculty Heidelberg, University of Heidelberg, Germany.,Division of Preventive Oncology, German Cancer Research Center (DKFZ), National Center for Tumor Diseases (NCT), Heidelberg, Germany
| | - Korbinian Weigl
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.,German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Ben Schöttker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Network Aging Research, University of Heidelberg, Germany
| | | | - Yan Zhang
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.,German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Division of Preventive Oncology, German Cancer Research Center (DKFZ), National Center for Tumor Diseases (NCT), Heidelberg, Germany.,German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
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Briggs S, Slade I. Evaluating the Integration of Genomics into Cancer Screening Programmes: Challenges and Opportunities. CURRENT GENETIC MEDICINE REPORTS 2019; 7:63-74. [PMID: 32117599 PMCID: PMC7019642 DOI: 10.1007/s40142-019-00162-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
PURPOSE OF REVIEW As the costs of genomic testing have fallen, and our understanding of genetic susceptibility to cancers has grown, there has been increasing interest in incorporating testing for cancer susceptibility genes, and polygenic risk estimates, into population cancer screening. A growing body of evidence suggests that this would be both clinically and cost-effective. In this article, we aim to explore the frameworks used to evaluate screening programmes, evaluate whether population screening for cancer susceptibility can be assessed using these standards, and consider additional issues and outcomes of importance in this context. RECENT FINDINGS There are tensions between traditional approaches of genetic testing (utilising tests with high sensitivity and specificity) and the principles of population screening (in which the screening test typically has low specificity), as well as the frameworks used to evaluate the two. Despite the existence of many screening guidelines, including consensus papers, these often do not align fully with broader considerations of genetic test evaluation. Population screening for genetic risk in cancer shifts the focus from diagnostics to prognostication and has wider implications for personal and familial health than existing screening programmes. In addition, understanding of the prevalence and penetrance of cancer susceptibility genes, required by many screening guidelines, may only be obtainable through population-level testing; prospective multi-disciplinary research alongside implementation will be essential. SUMMARY Appropriate evaluation of genetic screening for cancer risk will require modification of existing screening frameworks to incorporate additional complexity of outcomes and population values. As evidence supporting population screening for cancer susceptibility mounts, development of an appropriate evaluative framework, and expansion of public dialogue will be key to informing policy.
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Affiliation(s)
- Sarah Briggs
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN UK
| | - Ingrid Slade
- Wellcome Centre for Ethics and Humanities and Ethox Centre, Nuffield Department of Population Health, Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Old Road Campus, Oxford, OX3 7LF UK
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Veron L, Gelot A, Gusto G, Arveux P, Delaloge S, Boutron‐Ruault M. Modifiable risk factors for advanced
vs
. early breast cancer in the French E3N cohort. Int J Cancer 2019; 146:850-860. [DOI: 10.1002/ijc.32354] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Revised: 03/05/2019] [Accepted: 03/25/2019] [Indexed: 12/16/2022]
Affiliation(s)
- Lucie Veron
- Inserm U1018, Center for Research in Epidemiology and Population Health (CESP) Villejuif France
- Paris‐South Saclay University Villejuif France
| | - Amandine Gelot
- Inserm U1018, Center for Research in Epidemiology and Population Health (CESP) Villejuif France
| | - Gaelle Gusto
- Inserm U1018, Center for Research in Epidemiology and Population Health (CESP) Villejuif France
| | - Patrick Arveux
- Inserm U1018, Center for Research in Epidemiology and Population Health (CESP) Villejuif France
| | | | - Marie‐Christine Boutron‐Ruault
- Inserm U1018, Center for Research in Epidemiology and Population Health (CESP) Villejuif France
- Paris‐South Saclay University Villejuif France
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GP attitudes to and expectations for providing personal genomic risk information to the public: a qualitative study. BJGP Open 2019; 3:bjgpopen18X101633. [PMID: 31049413 PMCID: PMC6480852 DOI: 10.3399/bjgpopen18x101633] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Accepted: 08/20/2018] [Indexed: 01/16/2023] Open
Abstract
Background As part of a pilot randomised controlled trial examining the impact of personal melanoma genomic risk information on behavioural and psychosocial outcomes, GPs were sent a booklet containing their patient’s genomic risk of melanoma. Aim Using this booklet as an example of genomic risk information that might be offered on a population-level in the future, this study explored GP attitudes towards communicating genomic risk information and resources needed to support this process. Design & setting Semi-structured interviews were conducted with 22 Australian GPs. Method The interviews were recorded and transcribed, and data were analysed thematically. Results GPs in this sample believed that communicating genomic risk may become a responsibility within primary care and they recommended a shared decisionmaking approach to guide the testing process. Factors were identified that may influence how and when GPs communicate genomic risk information. GPs view genomics-based risk as one of many disease risk factors and feel that this type of information could be applied in practice in the context of overall risk assessment for diseases for which prevention and early detection strategies are available. They believe it is important to ensure that patients understand their genomic risk and do not experience long-term adverse psychological responses. GPs desire clinical practice guidelines that specify recommendations for genomic risk assessment and patient management, point-of-care resources, and risk prediction tools that include genomic and traditional risk factors. Conclusion These findings will inform the development of resources for preparing GPs to manage and implement genomic risk information in practice.
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Mavaddat N, Michailidou K, Dennis J, Lush M, Fachal L, Lee A, Tyrer JP, Chen TH, Wang Q, Bolla MK, Yang X, Adank MA, Ahearn T, Aittomäki K, Allen J, Andrulis IL, Anton-Culver H, Antonenkova NN, Arndt V, Aronson KJ, Auer PL, Auvinen P, Barrdahl M, Beane Freeman LE, Beckmann MW, Behrens S, Benitez J, Bermisheva M, Bernstein L, Blomqvist C, Bogdanova NV, Bojesen SE, Bonanni B, Børresen-Dale AL, Brauch H, Bremer M, Brenner H, Brentnall A, Brock IW, Brooks-Wilson A, Brucker SY, Brüning T, Burwinkel B, Campa D, Carter BD, Castelao JE, Chanock SJ, Chlebowski R, Christiansen H, Clarke CL, Collée JM, Cordina-Duverger E, Cornelissen S, Couch FJ, Cox A, Cross SS, Czene K, Daly MB, Devilee P, Dörk T, Dos-Santos-Silva I, Dumont M, Durcan L, Dwek M, Eccles DM, Ekici AB, Eliassen AH, Ellberg C, Engel C, Eriksson M, Evans DG, Fasching PA, Figueroa J, Fletcher O, Flyger H, Försti A, Fritschi L, Gabrielson M, Gago-Dominguez M, Gapstur SM, García-Sáenz JA, Gaudet MM, Georgoulias V, Giles GG, Gilyazova IR, Glendon G, Goldberg MS, Goldgar DE, González-Neira A, Grenaker Alnæs GI, Grip M, Gronwald J, Grundy A, Guénel P, Haeberle L, Hahnen E, Haiman CA, Håkansson N, Hamann U, Hankinson SE, Harkness EF, Hart SN, He W, Hein A, Heyworth J, Hillemanns P, Hollestelle A, Hooning MJ, Hoover RN, Hopper JL, Howell A, Huang G, Humphreys K, Hunter DJ, Jakimovska M, Jakubowska A, Janni W, John EM, Johnson N, Jones ME, Jukkola-Vuorinen A, Jung A, Kaaks R, Kaczmarek K, Kataja V, Keeman R, Kerin MJ, Khusnutdinova E, Kiiski JI, Knight JA, Ko YD, Kosma VM, Koutros S, Kristensen VN, Krüger U, Kühl T, Lambrechts D, Le Marchand L, Lee E, Lejbkowicz F, Lilyquist J, Lindblom A, Lindström S, Lissowska J, Lo WY, Loibl S, Long J, Lubiński J, Lux MP, MacInnis RJ, Maishman T, Makalic E, Maleva Kostovska I, Mannermaa A, Manoukian S, Margolin S, Martens JWM, Martinez ME, Mavroudis D, McLean C, Meindl A, Menon U, Middha P, Miller N, Moreno F, Mulligan AM, Mulot C, Muñoz-Garzon VM, Neuhausen SL, Nevanlinna H, Neven P, Newman WG, Nielsen SF, Nordestgaard BG, Norman A, Offit K, Olson JE, Olsson H, Orr N, Pankratz VS, Park-Simon TW, Perez JIA, Pérez-Barrios C, Peterlongo P, Peto J, Pinchev M, Plaseska-Karanfilska D, Polley EC, Prentice R, Presneau N, Prokofyeva D, Purrington K, Pylkäs K, Rack B, Radice P, Rau-Murthy R, Rennert G, Rennert HS, Rhenius V, Robson M, Romero A, Ruddy KJ, Ruebner M, Saloustros E, Sandler DP, Sawyer EJ, Schmidt DF, Schmutzler RK, Schneeweiss A, Schoemaker MJ, Schumacher F, Schürmann P, Schwentner L, Scott C, Scott RJ, Seynaeve C, Shah M, Sherman ME, Shrubsole MJ, Shu XO, Slager S, Smeets A, Sohn C, Soucy P, Southey MC, Spinelli JJ, Stegmaier C, Stone J, Swerdlow AJ, Tamimi RM, Tapper WJ, Taylor JA, Terry MB, Thöne K, Tollenaar RAEM, Tomlinson I, Truong T, Tzardi M, Ulmer HU, Untch M, Vachon CM, van Veen EM, Vijai J, Weinberg CR, Wendt C, Whittemore AS, Wildiers H, Willett W, Winqvist R, Wolk A, Yang XR, Yannoukakos D, Zhang Y, Zheng W, Ziogas A, Dunning AM, Thompson DJ, Chenevix-Trench G, Chang-Claude J, Schmidt MK, Hall P, Milne RL, Pharoah PDP, Antoniou AC, Chatterjee N, Kraft P, García-Closas M, Simard J, Easton DF. Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes. Am J Hum Genet 2019; 104:21-34. [PMID: 30554720 PMCID: PMC6323553 DOI: 10.1016/j.ajhg.2018.11.002] [Citation(s) in RCA: 568] [Impact Index Per Article: 113.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Accepted: 11/03/2018] [Indexed: 12/29/2022] Open
Abstract
Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.
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Affiliation(s)
- Nasim Mavaddat
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK.
| | - Kyriaki Michailidou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; Department of Electron Microscopy/Molecular Pathology, The Cyprus Institute of Neurology and Genetics, 1683 Nicosia, Cyprus
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Michael Lush
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Laura Fachal
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Andrew Lee
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Jonathan P Tyrer
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Ting-Huei Chen
- Department of Mathematics and Statistics, Laval University, Québec City, QC G1V 0A6, Canada
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Manjeet K Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Xin Yang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Muriel A Adank
- Family Cancer Clinic, the Netherlands Cancer Institute - Antoni van Leeuwenhoek hospital, Amsterdam, 1066 CX, the Netherlands
| | - Thomas Ahearn
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20850, USA
| | - Kristiina Aittomäki
- Department of Clinical Genetics, Helsinki University Hospital, University of Helsinki, Helsinki 00290, Finland
| | - Jamie Allen
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Irene L Andrulis
- Fred A. Litwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, ON M5G 1X5, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Hoda Anton-Culver
- Department of Epidemiology, Genetic Epidemiology Research Institute, University of California Irvine, Irvine, CA 92617, USA
| | - Natalia N Antonenkova
- NN Alexandrov Research Institute of Oncology and Medical Radiology, Minsk 223040, Belarus
| | - Volker Arndt
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany
| | - Kristan J Aronson
- Department of Public Health Sciences, and Cancer Research Institute, Queen's University, Kingston, ON K7L 3N6, Canada
| | - Paul L Auer
- Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA; Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI 53205, USA
| | - Päivi Auvinen
- Cancer Center, Kuopio University Hospital, Kuopio 70210, Finland; Institute of Clinical Medicine, Oncology, University of Eastern Finland, Kuopio 70210, Finland; Translational Cancer Research Area, University of Eastern Finland, Kuopio 70210, Finland
| | - Myrto Barrdahl
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany
| | - Laura E Beane Freeman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20850, USA
| | - Matthias W Beckmann
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen 91054, Germany
| | - Sabine Behrens
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany
| | - Javier Benitez
- Human Cancer Genetics Programme, Spanish National Cancer Research Centre (CNIO), Madrid 28029, Spain; Biomedical Network on Rare Diseases (CIBERER), Madrid 28029, Spain
| | - Marina Bermisheva
- Institute of Biochemistry and Genetics, Ufa Scientific Center of Russian Academy of Sciences, Ufa 450054, Russia
| | - Leslie Bernstein
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Carl Blomqvist
- Department of Oncology, Helsinki University Hospital, University of Helsinki, Helsinki 00290, Finland; Department of Oncology, Örebro University Hospital, Örebro 70185, Sweden
| | - Natalia V Bogdanova
- NN Alexandrov Research Institute of Oncology and Medical Radiology, Minsk 223040, Belarus; Department of Radiation Oncology, Hannover Medical School, Hannover 30625, Germany; Gynaecology Research Unit, Hannover Medical School, Hannover 30625, Germany
| | - Stig E Bojesen
- Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev 2730, Denmark; Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev 2730, Denmark; Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Bernardo Bonanni
- Division of Cancer Prevention and Genetics, IEO, European Institute of Oncology IRCCS, Milan 20141, Italy
| | - Anne-Lise Børresen-Dale
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital-Radiumhospitalet, Oslo 0379, Norway; Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo 0450, Norway
| | - Hiltrud Brauch
- Dr Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart 70376, Germany; University of Tübingen, Tübingen 72074, Germany; German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg 69120, Germany
| | - Michael Bremer
- Department of Radiation Oncology, Hannover Medical School, Hannover 30625, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany; German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg 69120, Germany; Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg 69120, Germany
| | - Adam Brentnall
- Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London EC1M 6BQ, UK
| | - Ian W Brock
- Sheffield Institute for Nucleic Acids (SInFoNiA), Department of Oncology and Metabolism, University of Sheffield, Sheffield S10 2TN, UK
| | - Angela Brooks-Wilson
- Genome Sciences Centre, BC Cancer Agency, Vancouver, BC V5Z 1L3, Canada; Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, BC V5A 1S6, Canada
| | - Sara Y Brucker
- Department of Gynecology and Obstetrics, University of Tübingen, Tübingen 72076, Germany
| | - Thomas Brüning
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), Bochum 44789, Germany
| | - Barbara Burwinkel
- Department of Obstetrics and Gynecology, University of Heidelberg, Heidelberg 69120, Germany; Molecular Epidemiology Group, C080, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany
| | - Daniele Campa
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany; Department of Biology, University of Pisa, Pisa 56126, Italy
| | - Brian D Carter
- Epidemiology Research Program, American Cancer Society, Atlanta, GA 30303, USA
| | - Jose E Castelao
- Oncology and Genetics Unit, Instituto de Investigacion Sanitaria Galicia Sur (IISGS), Xerencia de Xestion Integrada de Vigo-SERGAS, Vigo 36312, Spain
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20850, USA
| | - Rowan Chlebowski
- Division of Medical Oncology and Hematology, University of California at Los Angeles, Los Angeles, CA 90024, USA
| | - Hans Christiansen
- Department of Radiation Oncology, Hannover Medical School, Hannover 30625, Germany
| | - Christine L Clarke
- Westmead Institute for Medical Research, University of Sydney, Sydney, NSW 2145, Australia
| | - J Margriet Collée
- Department of Clinical Genetics, Erasmus University Medical Center, Rotterdam 3015 CN, the Netherlands
| | - Emilie Cordina-Duverger
- Cancer & Environment Group, Center for Research in Epidemiology and Population Health (CESP), INSERM, University Paris-Sud, University Paris-Saclay, Villejuif 94805, France
| | - Sten Cornelissen
- Division of Molecular Pathology, the Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam 1066 CX, the Netherlands
| | - Fergus J Couch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Angela Cox
- Sheffield Institute for Nucleic Acids (SInFoNiA), Department of Oncology and Metabolism, University of Sheffield, Sheffield S10 2TN, UK
| | - Simon S Cross
- Academic Unit of Pathology, Department of Neuroscience, University of Sheffield, Sheffield S10 2TN, UK
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 171 65, Sweden
| | - Mary B Daly
- Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, PA 19111, USA
| | - Peter Devilee
- Department of Pathology, Leiden University Medical Center, Leiden 2333 ZA, the Netherlands; Department of Human Genetics, Leiden University Medical Center, Leiden 2333 ZA, the Netherlands
| | - Thilo Dörk
- Gynaecology Research Unit, Hannover Medical School, Hannover 30625, Germany
| | - Isabel Dos-Santos-Silva
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
| | - Martine Dumont
- Genomics Center, Centre Hospitalier Universitaire de Québec - Université Laval Research Center, Université Laval, Québec City, QC G1V 4G2, Canada
| | - Lorraine Durcan
- Southampton Clinical Trials Unit, Faculty of Medicine, University of Southampton, Southampton SO17 6YD, UK; Cancer Sciences Academic Unit, Faculty of Medicine, University of Southampton, Southampton SO17 6YD, UK
| | - Miriam Dwek
- School of Life Sciences, University of Westminster, London W1B 2HW, UK
| | - Diana M Eccles
- Cancer Sciences Academic Unit, Faculty of Medicine, University of Southampton, Southampton SO17 6YD, UK
| | - Arif B Ekici
- Institute of Human Genetics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen 91054, Germany
| | - A Heather Eliassen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA 02115, USA
| | - Carolina Ellberg
- Department of Cancer Epidemiology, Clinical Sciences, Lund University, Lund 222 42, Sweden
| | - Christoph Engel
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig 04107, Germany; LIFE - Leipzig Research Centre for Civilization Diseases, University of Leipzig, Leipzig 04103, Germany
| | - Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 171 65, Sweden
| | - D Gareth Evans
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester M13 9WL, UK; North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 9WL, UK
| | - Peter A Fasching
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen 91054, Germany; David Geffen School of Medicine, Department of Medicine Division of Hematology and Oncology, University of California at Los Angeles, Los Angeles, CA 90095, USA
| | - Jonine Figueroa
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20850, USA; Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh Medical School, Edinburgh EH16 4TJ, UK; Cancer Research UK Edinburgh Centre, Edinburgh EH4 2XR, UK
| | - Olivia Fletcher
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London SW7 3RP, UK
| | - Henrik Flyger
- Department of Breast Surgery, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev 2730, Denmark
| | - Asta Försti
- Division of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany; Center for Primary Health Care Research, Clinical Research Center, Lund University, Malmö 205 02, Sweden
| | - Lin Fritschi
- School of Public Health, Curtin University, Perth, WA 6102, Australia
| | - Marike Gabrielson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 171 65, Sweden
| | - Manuela Gago-Dominguez
- Genomic Medicine Group, Galician Foundation of Genomic Medicine, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago, SERGAS, Santiago de Compostela 15706, Spain; Moores Cancer Center, University of California San Diego, La Jolla, CA 92093, USA
| | - Susan M Gapstur
- Epidemiology Research Program, American Cancer Society, Atlanta, GA 30303, USA
| | - José A García-Sáenz
- Medical Oncology Department, Hospital Clínico San Carlos, Instituto de Investigación Sanitaria San Carlos (IdISSC), Centro Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid 28040, Spain
| | - Mia M Gaudet
- Epidemiology Research Program, American Cancer Society, Atlanta, GA 30303, USA
| | - Vassilios Georgoulias
- Department of Medical Oncology, University Hospital of Heraklion, Heraklion 711 10, Greece
| | - Graham G Giles
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC 3004, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Irina R Gilyazova
- Institute of Biochemistry and Genetics, Ufa Scientific Center of Russian Academy of Sciences, Ufa 450054, Russia; Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa 450076, Russia
| | - Gord Glendon
- Fred A. Litwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, ON M5G 1X5, Canada
| | - Mark S Goldberg
- Department of Medicine, McGill University, Montréal, QC H4A 3J1, Canada; Division of Clinical Epidemiology, Royal Victoria Hospital, McGill University, Montréal, QC H4A 3J1, Canada
| | - David E Goldgar
- Department of Dermatology and Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, UT 84112, USA
| | - Anna González-Neira
- Human Cancer Genetics Programme, Spanish National Cancer Research Centre (CNIO), Madrid 28029, Spain
| | - Grethe I Grenaker Alnæs
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital-Radiumhospitalet, Oslo 0379, Norway
| | - Mervi Grip
- Department of Surgery, Oulu University Hospital, University of Oulu, Oulu 90220, Finland
| | - Jacek Gronwald
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin 71-252, Poland
| | - Anne Grundy
- Centre de Recherche du Centre Hospitalier de Université de Montréal (CHUM), Université de Montréal, Montréal, QC H2X 0A9, Canada
| | - Pascal Guénel
- Cancer & Environment Group, Center for Research in Epidemiology and Population Health (CESP), INSERM, University Paris-Sud, University Paris-Saclay, Villejuif 94805, France
| | - Lothar Haeberle
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen 91054, Germany
| | - Eric Hahnen
- Center for Hereditary Breast and Ovarian Cancer, University Hospital of Cologne, Cologne 50937, Germany; Center for Molecular Medicine Cologne (CMMC), University of Cologne, Cologne 50931, Germany
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Niclas Håkansson
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm 171 77, Sweden
| | - Ute Hamann
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany
| | - Susan E Hankinson
- Department of Biostatistics & Epidemiology, University of Massachusetts, Amherst, Amherst, MA 1003, USA
| | - Elaine F Harkness
- Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester M13 9PT, UK; Nightingale Breast Screening Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester M23 9LT, UK; NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 9WL, UK
| | - Steven N Hart
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Wei He
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 171 65, Sweden
| | - Alexander Hein
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen 91054, Germany
| | - Jane Heyworth
- School of Population and Global Health, University of Western Australia, Perth, WA 6009, Australia
| | - Peter Hillemanns
- Gynaecology Research Unit, Hannover Medical School, Hannover 30625, Germany
| | - Antoinette Hollestelle
- Department of Medical Oncology, Family Cancer Clinic, Erasmus MC Cancer Institute, Rotterdam 3015 CN, the Netherlands
| | - Maartje J Hooning
- Department of Medical Oncology, Family Cancer Clinic, Erasmus MC Cancer Institute, Rotterdam 3015 CN, the Netherlands
| | - Robert N Hoover
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20850, USA
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia
| | - Anthony Howell
- Division of Cancer Sciences, University of Manchester, Manchester M13 9PL, UK
| | - Guanmengqian Huang
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany
| | - Keith Humphreys
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 171 65, Sweden
| | - David J Hunter
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA 02115, USA; Program in Genetic Epidemiology and Statistical Genetics, Harvard TH Chan School of Public Health, Boston, MA 02115, USA; Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Milena Jakimovska
- Research Centre for Genetic Engineering and Biotechnology "Georgi D. Efremov," Macedonian Academy of Sciences and Arts, Skopje 1000, Republic of Macedonia
| | - Anna Jakubowska
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin 71-252, Poland; Independent Laboratory of Molecular Biology and Genetic Diagnostics, Pomeranian Medical University, Szczecin 71-252, Poland
| | - Wolfgang Janni
- Department of Gynecology and Obstetrics, University Hospital Ulm, Ulm 89075, Germany
| | - Esther M John
- Department of Medicine, Division of Oncology, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Nichola Johnson
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London SW7 3RP, UK
| | - Michael E Jones
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London SM2 5NG, UK
| | - Arja Jukkola-Vuorinen
- Department of Oncology, Tampere University Hospital, Tampere, Finland Box 2000, 33521 Tampere, Finland
| | - Audrey Jung
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany
| | - Katarzyna Kaczmarek
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin 71-252, Poland
| | - Vesa Kataja
- Translational Cancer Research Area, University of Eastern Finland, Kuopio 70210, Finland; Central Finland Health Care District, Jyväskylä Central Hospital, Jyväskylä 40620, Finland
| | - Renske Keeman
- Division of Molecular Pathology, the Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam 1066 CX, the Netherlands
| | - Michael J Kerin
- Surgery, School of Medicine, National University of Ireland, Galway H91TK33, Ireland
| | - Elza Khusnutdinova
- Institute of Biochemistry and Genetics, Ufa Scientific Center of Russian Academy of Sciences, Ufa 450054, Russia; Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa 450076, Russia
| | - Johanna I Kiiski
- Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, Helsinki 00290, Finland
| | - Julia A Knight
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON M5T 3L9, Canada; Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5T 3M7, Canada
| | - Yon-Dschun Ko
- Department of Internal Medicine, Evangelische Kliniken Bonn gGmbH, Johanniter Krankenhaus, Bonn 53177, Germany
| | - Veli-Matti Kosma
- Translational Cancer Research Area, University of Eastern Finland, Kuopio 70210, Finland; Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio 70210, Finland; Imaging Center, Department of Clinical Pathology, Kuopio University Hospital, Kuopio 70210, Finland
| | - Stella Koutros
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20850, USA
| | - Vessela N Kristensen
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital-Radiumhospitalet, Oslo 0379, Norway; Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo 0450, Norway
| | - Ute Krüger
- Department of Cancer Epidemiology, Clinical Sciences, Lund University, Lund 222 42, Sweden
| | - Tabea Kühl
- Cancer Epidemiology Group, University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
| | - Diether Lambrechts
- VIB Center for Cancer Biology, VIB, Leuven 3000, Belgium; Laboratory for Translational Genetics, Department of Human Genetics, University of Leuven, Leuven 3000, Belgium
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI 96813, USA
| | - Eunjung Lee
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Flavio Lejbkowicz
- Clalit National Cancer Control Center, Carmel Medical Center and Technion Faculty of Medicine, Haifa 35254, Israel
| | - Jenna Lilyquist
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Annika Lindblom
- Department of Molecular Medicine and Surgery, Karolinska Institutet, and Department of Clinical Genetics, Karolinska University Hospital, Stockholm 171 76, Sweden
| | - Sara Lindström
- Department of Epidemiology, University of Washington School of Public Health, Seattle, WA 98195, USA; Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Jolanta Lissowska
- Department of Cancer Epidemiology and Prevention, M Sklodowska-Curie Cancer Center - Oncology Institute, Warsaw 02-034, Poland
| | - Wing-Yee Lo
- Dr Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart 70376, Germany; University of Tübingen, Tübingen 72074, Germany
| | - Sibylle Loibl
- German Breast Group, GmbH, Neu Isenburg 63263, Germany
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Jan Lubiński
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin 71-252, Poland
| | - Michael P Lux
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen 91054, Germany
| | - Robert J MacInnis
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC 3004, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia
| | - Tom Maishman
- Southampton Clinical Trials Unit, Faculty of Medicine, University of Southampton, Southampton SO17 6YD, UK; Cancer Sciences Academic Unit, Faculty of Medicine, University of Southampton, Southampton SO17 6YD, UK
| | - Enes Makalic
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia
| | - Ivana Maleva Kostovska
- Research Centre for Genetic Engineering and Biotechnology "Georgi D. Efremov," Macedonian Academy of Sciences and Arts, Skopje 1000, Republic of Macedonia
| | - Arto Mannermaa
- Translational Cancer Research Area, University of Eastern Finland, Kuopio 70210, Finland; Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio 70210, Finland; Imaging Center, Department of Clinical Pathology, Kuopio University Hospital, Kuopio 70210, Finland
| | - Siranoush Manoukian
- Unit of Medical Genetics, Department of Medical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori (INT), Milan 20133, Italy
| | - Sara Margolin
- Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm 118 83, Sweden; Department of Oncology, Södersjukhuset, Stockholm 118 83, Sweden
| | - John W M Martens
- Department of Medical Oncology, Family Cancer Clinic, Erasmus MC Cancer Institute, Rotterdam 3015 CN, the Netherlands
| | - Maria Elena Martinez
- Moores Cancer Center, University of California San Diego, La Jolla, CA 92093, USA; Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA 92093, USA
| | - Dimitrios Mavroudis
- Department of Medical Oncology, University Hospital of Heraklion, Heraklion 711 10, Greece
| | - Catriona McLean
- Anatomical Pathology, The Alfred Hospital, Melbourne, VIC 3004, Australia
| | - Alfons Meindl
- Department of Gynecology and Obstetrics, Ludwig Maximilian University of Munich, Munich 80336, Germany
| | - Usha Menon
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, University College London, London WC1V 6LJ, UK
| | - Pooja Middha
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany; Faculty of Medicine, University of Heidelberg, Heidelberg 69120, Germany
| | - Nicola Miller
- Surgery, School of Medicine, National University of Ireland, Galway H91TK33, Ireland
| | - Fernando Moreno
- Medical Oncology Department, Hospital Clínico San Carlos, Instituto de Investigación Sanitaria San Carlos (IdISSC), Centro Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid 28040, Spain
| | - Anna Marie Mulligan
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada; Laboratory Medicine Program, University Health Network, Toronto, ON M5G 2C4, Canada
| | - Claire Mulot
- Université Paris Sorbonne Cité, INSERM UMR-S1147, Paris 75270, France
| | | | - Susan L Neuhausen
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Heli Nevanlinna
- Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, Helsinki 00290, Finland
| | - Patrick Neven
- Leuven Multidisciplinary Breast Center, Department of Oncology, Leuven Cancer Institute, University Hospitals Leuven, Leuven 3000, Belgium
| | - William G Newman
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester M13 9WL, UK; North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 9WL, UK
| | - Sune F Nielsen
- Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev 2730, Denmark; Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev 2730, Denmark
| | - Børge G Nordestgaard
- Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev 2730, Denmark; Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev 2730, Denmark; Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Aaron Norman
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Kenneth Offit
- Clinical Genetics Research Lab, Department of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; Clinical Genetics Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Janet E Olson
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Håkan Olsson
- Department of Cancer Epidemiology, Clinical Sciences, Lund University, Lund 222 42, Sweden
| | - Nick Orr
- Centre for Cancer Research and Cell Biology, Queen's University Belfast, Belfast BT7 1NN, UK
| | - V Shane Pankratz
- University of New Mexico Health Sciences Center, University of New Mexico, Albuquerque, NM 87131, USA
| | | | - Jose I A Perez
- Servicio de Cirugía General y Especialidades, Hospital Monte Naranco, Oviedo 33012, Spain
| | - Clara Pérez-Barrios
- Medical Oncology Department, Hospital Universitario Puerta de Hierro, Madrid 28222, Spain
| | - Paolo Peterlongo
- Genome Diagnostic Program, IFOM the FIRC (Italian Foundation for Cancer Research) Institute of Molecular Oncology, Milan 20139, Italy
| | - Julian Peto
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
| | - Mila Pinchev
- Clalit National Cancer Control Center, Carmel Medical Center and Technion Faculty of Medicine, Haifa 35254, Israel
| | - Dijana Plaseska-Karanfilska
- Research Centre for Genetic Engineering and Biotechnology "Georgi D. Efremov," Macedonian Academy of Sciences and Arts, Skopje 1000, Republic of Macedonia
| | - Eric C Polley
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Ross Prentice
- Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Nadege Presneau
- School of Life Sciences, University of Westminster, London W1B 2HW, UK
| | - Darya Prokofyeva
- Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa 450076, Russia
| | - Kristen Purrington
- Department of Oncology, Wayne State University School of Medicine, Detroit, MI 48201, USA
| | - Katri Pylkäs
- Laboratory of Cancer Genetics and Tumor Biology, Cancer and Translational Medicine Research Unit, Biocenter Oulu, University of Oulu, Oulu 90220, Finland; Laboratory of Cancer Genetics and Tumor Biology, Northern Finland Laboratory Centre Oulu, Oulu 90220, Finland
| | - Brigitte Rack
- Department of Gynecology and Obstetrics, University Hospital Ulm, Ulm 89075, Germany
| | - Paolo Radice
- Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori (INT), Milan 20133, Italy
| | - Rohini Rau-Murthy
- Clinical Genetics Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Gad Rennert
- Clalit National Cancer Control Center, Carmel Medical Center and Technion Faculty of Medicine, Haifa 35254, Israel
| | - Hedy S Rennert
- Clalit National Cancer Control Center, Carmel Medical Center and Technion Faculty of Medicine, Haifa 35254, Israel
| | - Valerie Rhenius
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Mark Robson
- Clinical Genetics Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Atocha Romero
- Medical Oncology Department, Hospital Universitario Puerta de Hierro, Madrid 28222, Spain
| | - Kathryn J Ruddy
- Department of Oncology, Mayo Clinic, Rochester, MN 55905, USA
| | - Matthias Ruebner
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen 91054, Germany
| | | | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA
| | - Elinor J Sawyer
- Research Oncology, Guy's Hospital, King's College London, London SE1 9RT, UK
| | - Daniel F Schmidt
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia; Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia
| | - Rita K Schmutzler
- Center for Hereditary Breast and Ovarian Cancer, University Hospital of Cologne, Cologne 50937, Germany; Center for Molecular Medicine Cologne (CMMC), University of Cologne, Cologne 50931, Germany
| | - Andreas Schneeweiss
- National Center for Tumor Diseases, University Hospital and German Cancer Research Center, Heidelberg 69120, Germany
| | - Minouk J Schoemaker
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London SM2 5NG, UK
| | - Fredrick Schumacher
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Peter Schürmann
- Gynaecology Research Unit, Hannover Medical School, Hannover 30625, Germany
| | - Lukas Schwentner
- Department of Gynecology and Obstetrics, University Hospital Ulm, Ulm 89075, Germany
| | - Christopher Scott
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Rodney J Scott
- Division of Molecular Medicine, Pathology North, John Hunter Hospital, Newcastle, NSW 2305, Australia; Discipline of Medical Genetics, School of Biomedical Sciences and Pharmacy, Faculty of Health, University of Newcastle, Callaghan, NSW 2308, Australia; Hunter Medical Research Institute, John Hunter Hospital, Newcastle, NSW 2305, Australia
| | - Caroline Seynaeve
- Department of Medical Oncology, Family Cancer Clinic, Erasmus MC Cancer Institute, Rotterdam 3015 CN, the Netherlands
| | - Mitul Shah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Mark E Sherman
- Department of Health Sciences Research, Mayo Clinic College of Medicine, Jacksonville, FL 32224, USA
| | - Martha J Shrubsole
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Susan Slager
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Ann Smeets
- Leuven Multidisciplinary Breast Center, Department of Oncology, Leuven Cancer Institute, University Hospitals Leuven, Leuven 3000, Belgium
| | - Christof Sohn
- National Center for Tumor Diseases, University Hospital and German Cancer Research Center, Heidelberg 69120, Germany
| | - Penny Soucy
- Genomics Center, Centre Hospitalier Universitaire de Québec - Université Laval Research Center, Université Laval, Québec City, QC G1V 4G2, Canada
| | - Melissa C Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; Department of Clinical Pathology, The University of Melbourne, Melbourne, VIC 3010, Australia
| | - John J Spinelli
- Population Oncology, BC Cancer, Vancouver, BC V5Z 1G1, Canada; School of Population and Public Health, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
| | | | - Jennifer Stone
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia; The Curtin UWA Centre for Genetic Origins of Health and Disease, Curtin University and University of Western Australia, Perth, WA 6000, Australia
| | - Anthony J Swerdlow
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London SM2 5NG, UK; Division of Breast Cancer Research, The Institute of Cancer Research, London SW7 3RP, UK
| | - Rulla M Tamimi
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA 02115, USA; Program in Genetic Epidemiology and Statistical Genetics, Harvard TH Chan School of Public Health, Boston, MA 02115, USA
| | - William J Tapper
- Faculty of Medicine, University of Southampton, Southampton SO17 1BJ, UK
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA; Epigenetic and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA
| | - Mary Beth Terry
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
| | - Kathrin Thöne
- Cancer Epidemiology Group, University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
| | - Rob A E M Tollenaar
- Department of Surgery, Leiden University Medical Center, Leiden 2333 ZA, the Netherlands
| | - Ian Tomlinson
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham B15 2TT, UK; Wellcome Trust Centre for Human Genetics and Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford OX3 7BN, UK
| | - Thérèse Truong
- Cancer & Environment Group, Center for Research in Epidemiology and Population Health (CESP), INSERM, University Paris-Sud, University Paris-Saclay, Villejuif 94805, France
| | - Maria Tzardi
- Department of Pathology, University Hospital of Heraklion, Heraklion 711 10, Greece
| | - Hans-Ulrich Ulmer
- Frauenklinik der Stadtklinik Baden-Baden, Baden-Baden 76532, Germany
| | - Michael Untch
- Department of Gynecology and Obstetrics, Helios Clinics Berlin-Buch, Berlin 13125, Germany
| | - Celine M Vachon
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Elke M van Veen
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester M13 9WL, UK; North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 9WL, UK
| | - Joseph Vijai
- Clinical Genetics Research Lab, Department of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; Clinical Genetics Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Clarice R Weinberg
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA
| | - Camilla Wendt
- Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm 118 83, Sweden; Department of Oncology, Södersjukhuset, Stockholm 118 83, Sweden
| | - Alice S Whittemore
- Department of Health Research and Policy - Epidemiology, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Hans Wildiers
- Leuven Multidisciplinary Breast Center, Department of Oncology, Leuven Cancer Institute, University Hospitals Leuven, Leuven 3000, Belgium
| | - Walter Willett
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA 02115, USA; Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA 02115, USA; Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Robert Winqvist
- Laboratory of Cancer Genetics and Tumor Biology, Cancer and Translational Medicine Research Unit, Biocenter Oulu, University of Oulu, Oulu 90220, Finland; Laboratory of Cancer Genetics and Tumor Biology, Northern Finland Laboratory Centre Oulu, Oulu 90220, Finland
| | - Alicja Wolk
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm 171 77, Sweden; Department of Surgical Sciences, Uppsala University, Uppsala 751 05, Sweden
| | - Xiaohong R Yang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20850, USA
| | - Drakoulis Yannoukakos
- Molecular Diagnostics Laboratory, INRASTES, National Centre for Scientific Research "Demokritos," Athens 15310, Greece
| | - Yan Zhang
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Argyrios Ziogas
- Department of Epidemiology, Genetic Epidemiology Research Institute, University of California Irvine, Irvine, CA 92617, USA
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Deborah J Thompson
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Georgia Chenevix-Trench
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany; Cancer Epidemiology Group, University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
| | - Marjanka K Schmidt
- Division of Molecular Pathology, the Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam 1066 CX, the Netherlands; Division of Psychosocial Research and Epidemiology, the Netherlands Cancer Institute - Antoni van Leeuwenhoek hospital, Amsterdam 1066 CX, the Netherlands
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 171 65, Sweden; Department of Oncology, Södersjukhuset, Stockholm 118 83, Sweden
| | - Roger L Milne
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC 3004, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia
| | - Paul D P Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Antonis C Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Nilanjan Chatterjee
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20850, USA; Department of Biostatistics, Bloomberg School of Public Health, John Hopkins University, Baltimore, MD 21205, USA; Department of Oncology, School of Medicine, John Hopkins University, Baltimore, MD 21205, USA
| | - Peter Kraft
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA 02115, USA; Program in Genetic Epidemiology and Statistical Genetics, Harvard TH Chan School of Public Health, Boston, MA 02115, USA
| | - Montserrat García-Closas
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20850, USA
| | - Jacques Simard
- Genomics Center, Centre Hospitalier Universitaire de Québec - Université Laval Research Center, Université Laval, Québec City, QC G1V 4G2, Canada
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge CB1 8RN, UK
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Abstract
OBJECTIVE The purpose of this article is to compare commonly used breast cancer risk assessment models, describe the machine learning approach and big data in risk prediction, and summarize the potential benefits and harms of restrictive risk-based screening. CONCLUSION The commonly used risk assessment models for breast cancer can be complex and cumbersome to use. Each model incorporates different sets of risk factors, which are weighted differently and can produce different results for the same patient. No model is appropriate for all subgroups of the general population and only one model incorporates mammographic breast density. Future development of risk prediction tools that are generalizable and simpler to use are needed in guiding clinical decisions.
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Hann KEJ, Ali N, Gessler S, Fraser LSM, Side L, Waller J, Sanderson SC, Lanceley A. Attitudes towards a programme of risk assessment and stratified management for ovarian cancer: a focus group study of UK South Asians' perspectives. BMJ Open 2018; 8:e021782. [PMID: 30021754 PMCID: PMC6059306 DOI: 10.1136/bmjopen-2018-021782] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
Abstract
OBJECTIVE Population-based risk assessment, using genetic testing and the provision of appropriate risk management, could lead to prevention, early detection and improved clinical management of ovarian cancer (OC). Previous research with mostly white British participants found positive attitudes towards such a programme. The current study aimed to explore the attitudes of South Asian (SA) women and men in the UK with the aim of identifying how best to implement such a programme to minimise distress and maximise uptake. DESIGN Semistructured qualitative focus group discussions. SETTING Community centres across North London and Luton. PARTICIPANTS 49 women and 13 men who identified as SA (Indian, Pakistani or Bangladeshi), which constitutes the largest non-European ethnic minority group in the UK. METHODS Seven community-based focus groups were held. Group discussions were transcribed verbatim, coded and analysed thematically. RESULTS Awareness and knowledge of OC symptoms and specific risk factors was low. The programme was acceptable to most participants and attitudes to it were generally positive. Participants' main concerns related to receiving a high-risk result following the genetic test. Younger women may be more cautious of genetic testing, screening or risk-reducing surgery due to the importance of marriage and childbearing in their SA cultures. CONCLUSIONS A crucial first step to enable implementation of population-based genetic risk assessment and management in OC is to raise awareness of OC within SA communities. It will be important to engage with the SA community early on in programme implementation to address their specific concerns and to ensure culturally tailored decision support.
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Affiliation(s)
- Katie E J Hann
- Department of Women’s Cancer, EGA UCL Institute for Women’s Health, University College London, London, UK
- Health Psychology Research Unit, Royal Holloway, University of London, Egham, UK
| | - Nasreen Ali
- Institute for Health Research, University of Bedfordshire, Luton, UK
| | - Sue Gessler
- Department of Women’s Cancer, EGA UCL Institute for Women’s Health, University College London, London, UK
| | | | - Lucy Side
- Department of Women’s Cancer, EGA UCL Institute for Women’s Health, University College London, London, UK
- Department of Clinical Genetics, University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Jo Waller
- Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, UK
| | - Saskia C Sanderson
- Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, UK
- Department of Clinical Genetics, Great Ormond Street Hospital, London, UK
| | - Anne Lanceley
- Department of Women’s Cancer, EGA UCL Institute for Women’s Health, University College London, London, UK
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Smit AK, Newson AJ, Morton RL, Kimlin M, Keogh L, Law MH, Kirk J, Dobbinson S, Kanetsky PA, Fenton G, Allen M, Butow P, Dunlop K, Trevena L, Lo S, Savard J, Dawkins H, Wordsworth S, Jenkins M, Mann GJ, Cust AE. The melanoma genomics managing your risk study: A protocol for a randomized controlled trial evaluating the impact of personal genomic risk information on skin cancer prevention behaviors. Contemp Clin Trials 2018; 70:106-116. [PMID: 29802966 DOI: 10.1016/j.cct.2018.05.014] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 05/17/2018] [Accepted: 05/22/2018] [Indexed: 02/08/2023]
Abstract
BACKGROUND Reducing ultraviolet radiation (UV) exposure and improving early detection may reduce melanoma incidence, mortality and health system costs. This study aims to evaluate the efficacy and cost-effectiveness of providing information on personal genomic risk of melanoma in reducing UV exposure at 12 months, according to low and high traditional risk. METHODS In this randomized controlled trial, participants (target sample = 892) will be recruited from the general population, and randomized (1:1 ratio, intervention versus control). Intervention arm participants provide a saliva sample, receive personalized melanoma genomic risk information, a genetic counselor phone call, and an educational booklet on melanoma prevention. Control arm participants receive only the educational booklet. Eligible participants are aged 18-69 years, have European ancestry and no personal history of melanoma. All participants will complete a questionnaire and wear a UV dosimeter to objectively measure their sun exposure at baseline, 1- and 12-month time-points, except 1-month UV dosimetry will be limited to ~250 participants. The primary outcome is total daily Standard Erythemal Doses at 12 months. Secondary outcomes include objectively measured UV exposure for specific time periods (e.g. midday hours), self-reported sun protection and skin-examination behaviors, psycho-social outcomes, and ethical considerations surrounding offering genomic testing at a population level. A within-trial and modelled economic evaluation will be undertaken from an Australian health system perspective to assess the intervention costs and outcomes. DISCUSSION This trial will inform the clinical and personal utility of introducing genomic testing into the health system for melanoma prevention and early detection at a population-level. TRIAL REGISTRATION Australian New Zealand Clinical Trials Registry ACTRN12617000691347.
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Affiliation(s)
- Amelia K Smit
- Cancer Epidemiology and Prevention Research, Sydney School of Public Health, The University of Sydney, NSW 2006, Australia; Sydney Health Ethics, Sydney School of Public Health, The University of Sydney, NSW 2006, Australia; Melanoma Institute Australia, The University of Sydney, NSW 2006, Australia.
| | - Ainsley J Newson
- Sydney Health Ethics, Sydney School of Public Health, The University of Sydney, NSW 2006, Australia
| | - Rachael L Morton
- NHMRC Clinical Trials Centre, The University of Sydney, NSW 2006, Australia
| | - Michael Kimlin
- University of the Sunshine Coast and Cancer Council Queensland, PO Box 201, Spring Hill, QLD 4004, Australia
| | - Louise Keogh
- Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Matthew H Law
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Locked Bag 2000, Brisbane, QLD 4029, Australia
| | - Judy Kirk
- Westmead Clinical School and Westmead Institute for Medical Research, Sydney Medical School, The University of Sydney, NSW 2006, Australia
| | - Suzanne Dobbinson
- Cancer Council Victoria, 615 St Kilda Road, Melbourne, VIC 3004, Australia
| | - Peter A Kanetsky
- H. Lee Moffitt Cancer Center and Research Institute and University of South Florida, 4202 E Fowler Ave, Tampa, FL 33620, USA
| | - Georgina Fenton
- Cancer Epidemiology and Prevention Research, Sydney School of Public Health, The University of Sydney, NSW 2006, Australia
| | - Martin Allen
- Electrical and Computer Engineering, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand
| | - Phyllis Butow
- Centre for Medical Psychology and Evidence-based Decision-making, School of Psychology, The University of Sydney, NSW 2006, Australia
| | - Kate Dunlop
- The Centre for Genetics Education, NSW Health, Level 5 2c Herbert Street St Leonards, NSW 2065, Australia
| | - Lyndal Trevena
- Sydney School of Public Health, The University of Sydney, NSW 2006, Australia
| | - Serigne Lo
- Melanoma Institute Australia, The University of Sydney, NSW 2006, Australia
| | - Jacqueline Savard
- Sydney Health Ethics, Sydney School of Public Health, The University of Sydney, NSW 2006, Australia
| | - Hugh Dawkins
- Office of Population Health Genomics, Public Health Division, Government of Western Australia, Level 3 C Block 189 Royal Street, East Perth, WA 6004, Australia
| | - Sarah Wordsworth
- Health Economics Research Centre, The University of Oxford, Oxford OX1 2JD, UK
| | - Mark Jenkins
- Centre for Epidemiology & Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Graham J Mann
- Melanoma Institute Australia, The University of Sydney, NSW 2006, Australia; Centre for Cancer Research, Westmead Institute for Medical Research, The University of Sydney, NSW 2006, Australia
| | - Anne E Cust
- Cancer Epidemiology and Prevention Research, Sydney School of Public Health, The University of Sydney, NSW 2006, Australia; Melanoma Institute Australia, The University of Sydney, NSW 2006, Australia
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Näslund-Koch C, Nordestgaard BG, Bojesen SE. Common breast cancer risk alleles and risk assessment: a study on 35 441 individuals from the Danish general population. Ann Oncol 2018; 28:175-181. [PMID: 28177461 DOI: 10.1093/annonc/mdw536] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Background We hypothesized that common breast cancer risk alleles are associated with incidences of breast cancer and other cancers in the general population, and identify low risk women among those invited for screening mammography. Participants and Methods About 35 441 individuals from the Danish general population were followed in Danish health registries for up to 21 years after blood sampling. After genotyping 72 breast cancer risk loci, each with 0–2 alleles, the sum for each individual was calculated. We used the simple allele sum instead of the conventional polygenic risk score, as it is likely more sensitive in detecting associations with risks of other endpoints than breast cancer. Results Breast cancer incidence in the 19 010 women was increased across allele sum quintiles (log-rank trend test; P = 1×10 − 12), but not incidence of other cancers (P = 0.41). Age- and study-adjusted hazard ratio for the fifth versus the first allele sum quintile was 1.82 (95% confidence interval; 1.53–2.18). Corresponding hazard ratios per allele were 1.04 (1.03–1.05) and 1.05 (1.02–1.08) for breast cancer incidence and mortality, similar across risk factors. In 50-year-old women, the starting age for screening mammography in Denmark, the average 5-year breast cancer risk was 1.5%, overall and 1.1%, 1.4%, 1.6%, 1.7%, 2.1%, for the first through fifth quintile, respectively. Based on age, nulliparity, familial history, and allele sum, 25% of women aged 50–69 years, and 94% of women aged 40–49 years, had absolute 5-year breast cancer risks ≤ 1.5%. Using polygenic risk score led to similar results. Conclusion Common breast cancer risk alleles are associated with incidence and mortality of breast cancer in the general population, but not with other cancers. After including breast cancer allele sum in risk assessment, 25% of women currently being offered screening mammography had an absolute 5-year risk below the cutoff of average risk for a 50-year-old woman.
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Affiliation(s)
- C Näslund-Koch
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev,The Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen,Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen
| | - B G Nordestgaard
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev,The Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen,Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen,The Copenhagen City Heart Study, Frederiksberg Hospital, Copenhagen University Hospital, Copenhagen, Denmark
| | - S E Bojesen
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev,The Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen,Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen,The Copenhagen City Heart Study, Frederiksberg Hospital, Copenhagen University Hospital, Copenhagen, Denmark
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Smit AK, Newson AJ, Best M, Badcock CA, Butow PN, Kirk J, Dunlop K, Fenton G, Cust AE. Distress, uncertainty, and positive experiences associated with receiving information on personal genomic risk of melanoma. Eur J Hum Genet 2018; 26:1094-1100. [PMID: 29706632 DOI: 10.1038/s41431-018-0145-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2017] [Revised: 03/06/2018] [Accepted: 03/20/2018] [Indexed: 12/13/2022] Open
Abstract
The aim of this research was to understand how genomics-based personal melanoma risk information impacts psychological and emotional health outcomes in the general population. In a pilot randomized controlled trial, participants (n = 103) completed the Multidimensional Impact of Cancer Risk Assessment (MICRA) questionnaire, 3 months after receiving personal melanoma genomic risk information. Mean scores for MICRA items and subscales were stratified by genomic risk group (low, average, high), gender, education, age, and family history of melanoma. P values were obtained from t-tests and analysis of variance tests. We found that overall, participants (mean age: 53 years, range: 21-69; 52% female) had a total MICRA mean score of 18.6 (standard deviation: 11.1, range: 1-70; possible range: 0-105). The high genomic risk group had higher mean scores for the total (24.2, F2,100 = 6.7, P = 0.0019), distress (3.3, F2,100 = 9.4, P = 0.0002) and uncertainty (8.5, F2,100 = 6.5, P = 0.0021) subscales compared with average (17.6, 1.1, and 4.5, respectively) and low-risk groups (14.1, 0.5, and 2.5, respectively). Positive experiences scores were consistent across risk groups. In conclusion, MICRA scores for the total, distress and uncertainty subscales in our study were relatively low overall, but people who receive a high genomic risk result may benefit from increased support following testing.
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Affiliation(s)
- Amelia K Smit
- Cancer Epidemiology and Prevention Research, Sydney School of Public Health, The University of Sydney, Sydney, Australia. .,Sydney Health Ethics, Sydney School of Public Health, The University of Sydney, Sydney, Australia. .,Melanoma Institute Australia, The University of Sydney, Sydney, Australia.
| | - Ainsley J Newson
- Sydney Health Ethics, Sydney School of Public Health, The University of Sydney, Sydney, Australia
| | - Megan Best
- Sydney Health Ethics, Sydney School of Public Health, The University of Sydney, Sydney, Australia.,Psycho-Oncology Co-operative Research Group (PoCoG), The University of Sydney, Sydney, Australia
| | - Caro-Anne Badcock
- Cancer Epidemiology and Prevention Research, Sydney School of Public Health, The University of Sydney, Sydney, Australia
| | - Phyllis N Butow
- Centre for Medical Psychology and Evidence-based Decision-making, School of Psychology, The University of Sydney, Sydney, Australia
| | - Judy Kirk
- Westmead Clinical School, and Westmead Institute for Medical Research, Sydney Medical School, The University of Sydney, Sydney, Australia
| | - Kate Dunlop
- The Centre for Genetics Education, NSW Health, Sydney, Australia
| | - Georgina Fenton
- Cancer Epidemiology and Prevention Research, Sydney School of Public Health, The University of Sydney, Sydney, Australia
| | - Anne E Cust
- Cancer Epidemiology and Prevention Research, Sydney School of Public Health, The University of Sydney, Sydney, Australia.,Melanoma Institute Australia, The University of Sydney, Sydney, Australia
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40
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Rudolph A, Song M, Brook MN, Milne RL, Mavaddat N, Michailidou K, Bolla MK, Wang Q, Dennis J, Wilcox AN, Hopper JL, Southey MC, Keeman R, Fasching PA, Beckmann MW, Gago-Dominguez M, Castelao JE, Guénel P, Truong T, Bojesen SE, Flyger H, Brenner H, Arndt V, Brauch H, Brüning T, Mannermaa A, Kosma VM, Lambrechts D, Keupers M, Couch FJ, Vachon C, Giles GG, MacInnis RJ, Figueroa J, Brinton L, Czene K, Brand JS, Gabrielson M, Humphreys K, Cox A, Cross SS, Dunning AM, Orr N, Swerdlow A, Hall P, Pharoah PDP, Schmidt MK, Easton DF, Chatterjee N, Chang-Claude J, García-Closas M. Joint associations of a polygenic risk score and environmental risk factors for breast cancer in the Breast Cancer Association Consortium. Int J Epidemiol 2018; 47:526-536. [PMID: 29315403 PMCID: PMC5913605 DOI: 10.1093/ije/dyx242] [Citation(s) in RCA: 68] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Revised: 10/25/2017] [Accepted: 11/23/2017] [Indexed: 12/20/2022] Open
Abstract
Background Polygenic risk scores (PRS) for breast cancer can be used to stratify the population into groups at substantially different levels of risk. Combining PRS and environmental risk factors will improve risk prediction; however, integrating PRS into risk prediction models requires evaluation of their joint association with known environmental risk factors. Methods Analyses were based on data from 20 studies; datasets analysed ranged from 3453 to 23 104 invasive breast cancer cases and similar numbers of controls, depending on the analysed environmental risk factor. We evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS with reproductive history, alcohol consumption, menopausal hormone therapy (MHT), height and body mass index (BMI). We tested the null hypothesis of multiplicative joint associations for PRS and each of the environmental factors, and performed global and tail-based goodness-of-fit tests in logistic regression models. The outcomes were breast cancer overall and by estrogen receptor (ER) status. Results The strongest evidence for a non-multiplicative joint associations with the 77-SNP PRS was for alcohol consumption (P-interaction = 0.009), adult height (P-interaction = 0.025) and current use of combined MHT (P-interaction = 0.038) in ER-positive disease. Risk associations for these factors by percentiles of PRS did not follow a clear dose-response. In addition, global and tail-based goodness of fit tests showed little evidence for departures from a multiplicative risk model, with alcohol consumption showing the strongest evidence for ER-positive disease (P = 0.013 for global and 0.18 for tail-based tests). Conclusions The combined effects of the 77-SNP PRS and environmental risk factors for breast cancer are generally well described by a multiplicative model. Larger studies are required to confirm possible departures from the multiplicative model for individual risk factors, and assess models specific for ER-negative disease.
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Affiliation(s)
- Anja Rudolph
- Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
- Real World Insights, CESE, QuintilesIMS, Frankfurt, Germany
| | - Minsun Song
- Department of Statistics, Sookmyung Women’s University, Seoul, Korea
| | - Mark N Brook
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
| | - Roger L Milne
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
- Centre for Epidemiology and Biostatistics, University of Melbourne, Melbourne, VIC, Australia
| | - Nasim Mavaddat
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Kyriaki Michailidou
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
- Department of Electron Microscopy/Molecular Pathology, Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
| | - Manjeet K Bolla
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Qin Wang
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Joe Dennis
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Amber N Wilcox
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, University of Melbourne, Melbourne, VIC, Australia
| | - Melissa C Southey
- Department of Pathology, University of Melbourne, Melbourne, VIC, Australia
| | - Renske Keeman
- Division of Molecular Pathology, The Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Peter A Fasching
- Department of Gynaecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany
- David Geffen School of Medicine, Division of Hematology and Oncology, University of California at Los Angeles, Los Angeles, CA, USA
| | - Matthias W Beckmann
- Department of Gynaecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany
| | - Manuela Gago-Dominguez
- Genomic Medicine Group, Galician Foundation of Genomic Medicine, Instituto de Investigación Sanitaria de Santiago, IDIS, Complejo Hospitalario Universitario de Santiago, Santiago de Compostela, Spain
- Moores Cancer Center, University of California San Diego, La Jolla, CA, USA
| | - Jose E Castelao
- Oncology and Genetics Unit, Complejo Hospitalario Universitario de Vigo, Instituto de Investigacion Sanitaria Galicia Sur, Vigo, Spain
| | - Pascal Guénel
- Center for Research in Epidemiology and Population Health, University Paris-Sud, University Paris-Saclay, Villejuif, France
| | - Thérèse Truong
- Center for Research in Epidemiology and Population Health, University Paris-Sud, University Paris-Saclay, Villejuif, France
| | - Stig E Bojesen
- Copenhagen General Population Study
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Henrik Flyger
- Department of Breast Surgery, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research
- Division of Preventive Oncology, National Center for Tumor Diseases (NCT)
- German Cancer Consortium, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Volker Arndt
- Division of Clinical Epidemiology and Aging Research
| | - Hiltrud Brauch
- German Cancer Consortium, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Dr Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany
- Department of Clinical Pharmacology, University of Tübingen, Tübingen, Germany
| | - Thomas Brüning
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum, Bochum, Germany
| | - Arto Mannermaa
- Translational Cancer Research Area
- Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Clinical Pathology, Kuopio University Hospital, Kuopio, Finland
| | - Veli-Matti Kosma
- Translational Cancer Research Area
- Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Clinical Pathology, Kuopio University Hospital, Kuopio, Finland
| | - Diether Lambrechts
- VIB Center for Cancer Biology, Leuven, Belgium
- Laboratory for Translational Genetics, University of Leuven, Leuven, Belgium
| | - Machteld Keupers
- Department of Radiation Oncology, University Hospitals Leuven, Leuven, Belgium
| | | | - Celine Vachon
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Graham G Giles
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
- Centre for Epidemiology and Biostatistics, University of Melbourne, Melbourne, VIC, Australia
| | - Robert J MacInnis
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
- Centre for Epidemiology and Biostatistics, University of Melbourne, Melbourne, VIC, Australia
| | - Jonine Figueroa
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Louise Brinton
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Judith S Brand
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Marike Gabrielson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Keith Humphreys
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | | | - Simon S Cross
- Department of Neuroscience, University of Sheffield, Sheffield, UK
| | - Alison M Dunning
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Nick Orr
- Division of Breast Cancer Research, Institute of Cancer Research, London, UK
| | - Anthony Swerdlow
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
- Division of Breast Cancer Research, Institute of Cancer Research, London, UK
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Paul D P Pharoah
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Marjanka K Schmidt
- Division of Molecular Pathology, The Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
- Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Douglas F Easton
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Nilanjan Chatterjee
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
- Bloomberg School of Public Health
- Department of Oncology, Johns Hopkins University, Baltimore, MD, USA
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
- University Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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Rainey L, van der Waal D, Jervaeus A, Wengström Y, Evans DG, Donnelly LS, Broeders MJM. Are we ready for the challenge of implementing risk-based breast cancer screening and primary prevention? Breast 2018. [PMID: 29529454 DOI: 10.1016/j.breast.2018.02.029] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND Increased knowledge of breast cancer risk factors provides opportunities to shift from a one-size-fits-all screening programme to a personalised approach, where screening and prevention is based on a woman's risk of developing breast cancer. However, potential implementation of this new paradigm could present considerable challenges which the present review aims to explore. METHODS Bibliographic databases were searched to identify studies evaluating potential implications of the implementation of personalised risk-based screening and primary prevention for breast cancer. Identified themes were evaluated using thematic analysis. RESULTS The search strategy identified 5699 unique publications, of which 59 were selected for inclusion. Significant changes in policy and practice are warranted. The organisation of breast cancer screening spans several healthcare delivery systems and clinical settings. Feasibility of implementation depends on how healthcare is funded and arranged, and potentially varies between countries. Piloting risk assessment and prevention counselling in primary care settings has highlighted implications relating to the need for extensive additional training on risk (communication) and prevention, impact on workflow, and professionals' personal discomfort breaching the topic with women. Additionally, gaps in risk estimation, psychological, ethical and legal consequences will need to be addressed. CONCLUSION The present review identified considerable unresolved issues and challenges. Potential implementation will require a more complex framework, in which a country's healthcare regulations, resources, and preferences related to screening and prevention services are taken into account. However, with the insights gained from the present overview, countries expecting to implement risk-based screening and prevention can start to inventory and address the issues that were identified.
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Affiliation(s)
- Linda Rainey
- Radboud Institute for Health Sciences, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands.
| | - Daniëlle van der Waal
- Radboud Institute for Health Sciences, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands
| | - Anna Jervaeus
- Department of Neurobiology, Care Sciences and Society, Division of Nursing, Karolinska Institutet & Theme Cancer, Karolinska University Hospital, Alfred Nobels allé 23, 23300, 14183, Huddinge, Sweden
| | - Yvonne Wengström
- Department of Neurobiology, Care Sciences and Society, Division of Nursing, Karolinska Institutet & Theme Cancer, Karolinska University Hospital, Alfred Nobels allé 23, 23300, 14183, Huddinge, Sweden
| | - D Gareth Evans
- Prevent Breast Cancer Research Unit, The Nightingale Centre, Manchester University NHS Foundation Trust, Southmoor Road, Manchester M23 9LT, United Kingdom; Genomic Medicine, Division of Evolution and Genomic Sciences, Manchester Academic Health Sciences Centre, Manchester University NHS Foundation Trust, Manchester M13 9WL, United Kingdom; The Christie NHS Foundation Trust, Withington, Manchester M20 4BX, United Kingdom
| | - Louise S Donnelly
- Prevent Breast Cancer Research Unit, The Nightingale Centre, Manchester University NHS Foundation Trust, Southmoor Road, Manchester M23 9LT, United Kingdom
| | - Mireille J M Broeders
- Radboud Institute for Health Sciences, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands; Dutch Expert Center for Screening, PO Box 6873, 6503 GJ Nijmegen, The Netherlands
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42
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Campos-Verdes LM, Costa-Silva DR, da Silva-Sampaio JP, Barros-Oliveira MDC, Escórcio-Dourado CS, Martins LM, Sampaio FA, Revoredo C, Alves-Ribeiro FA, da Silva BB. Review of Polymorphism of the Calcium-Sensing Receptor Gene and Breast Cancer Risk. Cancer Invest 2018; 36:1-7. [PMID: 29504802 DOI: 10.1080/07357907.2018.1430817] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Polymorphism of the calcium-sensing receptor gene (CaSR or CaR) has been associated with an increased risk for breast cancer. This receptor plays an important role in calcium homeostasis, and has also been detected in several tissues that are unrelated to calcium metabolism, such as the skin, brain, and breast. The calcium-sensing receptor on cellular level, it regulates cell differentiation, proliferation, cell death, and gene expression. In breast cancer cells, CaSR seems to stimulate secretion of the parathyroid hormone-related protein (PTHrP), which stimulates cellular proliferation. Likewise, some studies have supported not only an association between calcium receptor gene polymorphism and breast cancer risk, but also a higher aggressiveness and unfavorable outcomes in breast cancer, which led us to make a survey in Pubmed on the subject in the last 10 years. Thus, in the literature there is a paucity of studies on the subject and the aim of this review was to show the role of calcium-sensing receptor and its association with breast cancer risk.
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Affiliation(s)
- Larysse Maira Campos-Verdes
- a Postgraduate Program of Health in Sciences , Federal University of Piauí , 2280 Frei Serafim Avenue, Teresina , Piauí , Brazil
| | - Danylo Rafhael Costa-Silva
- b Postgraduate Program of the Northeast Network of Biotechnology (RENORBIO) , Federal University of Piauí , Teresina , Brazil
| | - João Paulo da Silva-Sampaio
- a Postgraduate Program of Health in Sciences , Federal University of Piauí , 2280 Frei Serafim Avenue, Teresina , Piauí , Brazil
| | | | - Carla Solange Escórcio-Dourado
- b Postgraduate Program of the Northeast Network of Biotechnology (RENORBIO) , Federal University of Piauí , Teresina , Brazil
| | - Luana Mota Martins
- b Postgraduate Program of the Northeast Network of Biotechnology (RENORBIO) , Federal University of Piauí , Teresina , Brazil
| | - Fabiane Araújo Sampaio
- b Postgraduate Program of the Northeast Network of Biotechnology (RENORBIO) , Federal University of Piauí , Teresina , Brazil
| | - Camila Revoredo
- b Postgraduate Program of the Northeast Network of Biotechnology (RENORBIO) , Federal University of Piauí , Teresina , Brazil
| | - Francisco Adelton Alves-Ribeiro
- b Postgraduate Program of the Northeast Network of Biotechnology (RENORBIO) , Federal University of Piauí , Teresina , Brazil
| | - Benedito Borges da Silva
- a Postgraduate Program of Health in Sciences , Federal University of Piauí , 2280 Frei Serafim Avenue, Teresina , Piauí , Brazil.,b Postgraduate Program of the Northeast Network of Biotechnology (RENORBIO) , Federal University of Piauí , Teresina , Brazil
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Widschwendter M, Jones A, Evans I, Reisel D, Dillner J, Sundström K, Steyerberg EW, Vergouwe Y, Wegwarth O, Rebitschek FG, Siebert U, Sroczynski G, de Beaufort ID, Bolt I, Cibula D, Zikan M, Bjørge L, Colombo N, Harbeck N, Dudbridge F, Tasse AM, Knoppers BM, Joly Y, Teschendorff AE, Pashayan N. Epigenome-based cancer risk prediction: rationale, opportunities and challenges. Nat Rev Clin Oncol 2018; 15:292-309. [PMID: 29485132 DOI: 10.1038/nrclinonc.2018.30] [Citation(s) in RCA: 103] [Impact Index Per Article: 17.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The incidence of cancer is continuing to rise and risk-tailored early diagnostic and/or primary prevention strategies are urgently required. The ideal risk-predictive test should: integrate the effects of both genetic and nongenetic factors and aim to capture these effects using an approach that is both biologically stable and technically reproducible; derive a score from easily accessible biological samples that acts as a surrogate for the organ in question; and enable the effectiveness of risk-reducing measures to be monitored. Substantial evidence has accumulated suggesting that the epigenome and, in particular, DNA methylation-based tests meet all of these requirements. However, the development and implementation of DNA methylation-based risk-prediction tests poses considerable challenges. In particular, the cell type specificity of DNA methylation and the extensive cellular heterogeneity of the easily accessible surrogate cells that might contain information relevant to less accessible tissues necessitates the use of novel methods in order to account for these confounding issues. Furthermore, the engagement of the scientific community with health-care professionals, policymakers and the public is required in order to identify and address the organizational, ethical, legal, social and economic challenges associated with the routine use of epigenetic testing.
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Affiliation(s)
- Martin Widschwendter
- Department of Women's Cancer, Institute for Women's Health, University College London, London, UK
| | - Allison Jones
- Department of Women's Cancer, Institute for Women's Health, University College London, London, UK
| | - Iona Evans
- Department of Women's Cancer, Institute for Women's Health, University College London, London, UK
| | - Daniel Reisel
- Department of Women's Cancer, Institute for Women's Health, University College London, London, UK
| | - Joakim Dillner
- Department of Laboratory Medicine, Karolinska Institutet, Stockholm, Sweden.,Karolinska University Laboratory, Karolinska University Hospital, Stockholm, Sweden
| | - Karin Sundström
- Department of Laboratory Medicine, Karolinska Institutet, Stockholm, Sweden.,Karolinska University Laboratory, Karolinska University Hospital, Stockholm, Sweden
| | - Ewout W Steyerberg
- Center for Medical Decision Sciences, Department of Public Health, Erasmus MC, Rotterdam, Netherlands.,Department of Biomedical Data Sciences, LUMC, Leiden, Netherlands
| | - Yvonne Vergouwe
- Center for Medical Decision Sciences, Department of Public Health, Erasmus MC, Rotterdam, Netherlands
| | - Odette Wegwarth
- Max Planck Institute for Human Development, Harding Center for Risk Literacy, Berlin, Germany.,Max Planck Institute for Human Development, Center for Adaptive Rationality, Berlin, Germany
| | - Felix G Rebitschek
- Max Planck Institute for Human Development, Harding Center for Risk Literacy, Berlin, Germany
| | - Uwe Siebert
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research, and HTA, UMIT-University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria.,Harvard T. C. Chan School of Public Health, Center for Health Decision Science, Department of Health Policy and Management, Boston, MA, USA.,Oncotyrol: Center for Personalized Medicine, Innsbruck, Austria
| | - Gaby Sroczynski
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research, and HTA, UMIT-University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
| | - Inez D de Beaufort
- Department of Medical Ethics and Philosophy of Medicine, Erasmus Medical Center, Rotterdam, Netherlands
| | - Ineke Bolt
- Department of Medical Ethics and Philosophy of Medicine, Erasmus Medical Center, Rotterdam, Netherlands
| | - David Cibula
- Department of Obstetrics and Gynaecology, First Medical Faculty of the Charles University and General Faculty Hospital, Prague, Czech Republic
| | - Michal Zikan
- Department of Obstetrics and Gynaecology, First Medical Faculty of the Charles University and General Faculty Hospital, Prague, Czech Republic
| | - Line Bjørge
- Department of Obstetrics and Gynecology, Haukeland University Hospital, and Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Nicoletta Colombo
- European Institute of Oncology and University Milan-Bicocca, Milan, Italy
| | - Nadia Harbeck
- Breast Center, Department of Gynaecology and Obstetrics, University of Munich (LMU), Munich, Germany
| | - Frank Dudbridge
- Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.,Department of Health Sciences, University of Leicester, Leicester, UK
| | - Anne-Marie Tasse
- Public Population Project in Genomics and Society, McGill University and Genome Quebec Innovation Centre, Montreal, Canada
| | | | - Yann Joly
- Centre of Genomics and Policy, McGill University, Montreal, Canada
| | - Andrew E Teschendorff
- Department of Women's Cancer, Institute for Women's Health, University College London, London, UK
| | - Nora Pashayan
- Department of Applied Health Research, Institute of Epidemiology and Healthcare, University College London, UK
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Wang S, Qian F, Zheng Y, Ogundiran T, Ojengbede O, Zheng W, Blot W, Nathanson KL, Hennis A, Nemesure B, Ambs S, Olopade OI, Huo D. Genetic variants demonstrating flip-flop phenomenon and breast cancer risk prediction among women of African ancestry. Breast Cancer Res Treat 2018; 168:703-712. [PMID: 29302764 DOI: 10.1007/s10549-017-4638-1] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2017] [Accepted: 12/23/2017] [Indexed: 01/19/2023]
Abstract
BACKGROUND Few studies have evaluated the performance of existing breast cancer risk prediction models among women of African ancestry. In replication studies of genetic variants, a change in direction of the risk association is a common phenomenon. Termed flip-flop, it means that a variant is risk factor in one population but protective in another, affecting the performance of risk prediction models. METHODS We used data from the genome-wide association study (GWAS) of breast cancer in the African diaspora (The Root consortium), which included 3686 participants of African ancestry from Nigeria, USA, and Barbados. Polygenic risk scores (PRSs) were constructed from the published odds ratios (ORs) of four sets of susceptibility loci for breast cancer. Discrimination capacity was measured using the area under the receiver operating characteristic curve (AUC). RESULTS Flip-flop phenomenon was observed among 30~40% of variants across studies. Using the 34 variants with consistent directionality among previous studies, we constructed a PRS with AUC of 0.531 (95% confidence interval [CI]: 0.512-0.550), which is similar to the PRS using 93 variants and ORs from European ancestry populations (AUC = 0.525, 95% CI: 0.506-0.544). Additionally, we found the 34-variant PRS has good discriminative accuracy in women with family history of breast cancer (AUC = 0.586, 95% CI: 0.532-0.640). CONCLUSIONS We found that PRS based on variants identified from prior GWASs conducted in women of European and Asian ancestries did not provide a comparable degree of risk stratification for women of African ancestry. Further large-scale fine-mapping studies in African ancestry populations are desirable to discover population-specific genetic risk variants.
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Affiliation(s)
- Shengfeng Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.,Center for Clinical Cancer Genetics & Global Health, Department of Medicine, University of Chicago, 5841 S. Maryland Ave., MC 2020, Chicago, IL, 60637, USA
| | - Frank Qian
- Department of Medicine, University of Chicago, Chicago, USA
| | - Yonglan Zheng
- Center for Clinical Cancer Genetics & Global Health, Department of Medicine, University of Chicago, 5841 S. Maryland Ave., MC 2020, Chicago, IL, 60637, USA
| | - Temidayo Ogundiran
- Department of Surgery, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Oladosu Ojengbede
- Center for Population and Reproductive Health, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, USA
| | - William Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, USA
| | | | - Anselm Hennis
- Chronic Disease Research Centre, Tropical Medicine Research Institute, University of the West Indies, Bridgetown, Barbados
| | - Barbara Nemesure
- Department of Preventive Medicine, State University of New York, Stony Brook, USA
| | - Stefan Ambs
- Laboratory of Human Carcinogenesis, National Cancer Institute, Rockville, USA
| | - Olufunmilayo I Olopade
- Center for Clinical Cancer Genetics & Global Health, Department of Medicine, University of Chicago, 5841 S. Maryland Ave., MC 2020, Chicago, IL, 60637, USA.
| | - Dezheng Huo
- Department of Public Health Sciences, University of Chicago, 5841 S. Maryland Ave, MC 2007, Chicago, IL, 60637, USA.
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Development and Evaluation of a Telephone Communication Protocol for the Delivery of Personalized Melanoma Genomic Risk to the General Population. J Genet Couns 2017; 27:370-380. [DOI: 10.1007/s10897-017-0183-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2017] [Accepted: 11/21/2017] [Indexed: 12/13/2022]
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Dalpé G, Ngueng Feze I, Salman S, Joly Y, Hagan J, Lévesque E, Dorval V, Blouin-Bougie J, Amara N, Dorval M, Simard J. Breast Cancer Risk Estimation and Personal Insurance: A Qualitative Study Presenting Perspectives from Canadian Patients and Decision Makers. Front Genet 2017; 8:128. [PMID: 28983318 PMCID: PMC5613157 DOI: 10.3389/fgene.2017.00128] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2017] [Accepted: 09/04/2017] [Indexed: 12/28/2022] Open
Abstract
Genetic stratification approaches in personalized medicine may considerably improve our ability to predict breast cancer risk for women at higher risk of developing breast cancer. Notwithstanding these advantages, concerns have been raised about the use of the genetic information derived in these processes, outside of the research and medical health care settings, by third parties such as insurers. Indeed, insurance applicants are asked to consent to insurers accessing their medical information (implicitly including genetic) to verify or determine their insurability level, or eligibility to certain insurance products. This use of genetic information may result in the differential treatment of individuals based on their genetic information, which could lead to higher premium, exclusionary clauses or even the denial of coverage. This phenomenon has been commonly referred to as "Genetic Discrimination" (GD). In the Canadian context, where federal Bill S-201, An Act to prohibit and prevent genetic discrimination, has recently been enacted but may be subject to constitutional challenges, information about potential risks to insurability may raise issues in the clinical context. We conducted a survey with women in Quebec who have never been diagnosed with breast cancer to document their perspectives. We complemented the research with data from 14 semi-structured interviews with decision-makers in Quebec to discuss institutional issues raised by the use of genetic information by insurers. Our results provide findings on five main issues: (1) the reluctance to undergo genetic screening test due to insurability concerns, (2) insurers' interest in genetic information, (3) the duty to disclose genetic information to insurers, (4) the disclosure of potential impacts on insurability before genetic testing, and (5) the status of genetic information compared to other health data. Overall, both groups of participants (the women surveyed and the decision-makers interviewed) acknowledged having concerns about GD and reported a need for better communication tools discussing insurability risk. Our conclusions regarding concerns about GD and the need for better communication tools in the clinical setting may be transferable to the broader Canadian context.
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Affiliation(s)
- Gratien Dalpé
- Department of Human Genetics, Faculty of Medicine, Centre of Genomics and Policy, McGill UniversityMontreal, QC, Canada
| | - Ida Ngueng Feze
- Department of Human Genetics, Faculty of Medicine, Centre of Genomics and Policy, McGill UniversityMontreal, QC, Canada
| | - Shahad Salman
- Department of Human Genetics, Faculty of Medicine, Centre of Genomics and Policy, McGill UniversityMontreal, QC, Canada
| | - Yann Joly
- Department of Human Genetics, Faculty of Medicine, Centre of Genomics and Policy, McGill UniversityMontreal, QC, Canada
| | - Julie Hagan
- Department of Human Genetics, Faculty of Medicine, Centre of Genomics and Policy, McGill UniversityMontreal, QC, Canada
| | - Emmanuelle Lévesque
- Department of Human Genetics, Faculty of Medicine, Centre of Genomics and Policy, McGill UniversityMontreal, QC, Canada
| | - Véronique Dorval
- Centre de Recherche du CHU de Quebec, Laval UniversityQuebec, QC, Canada
| | | | - Nabil Amara
- Faculty of Science of Administration, Laval UniversityQuebec, QC, Canada
| | - Michel Dorval
- Centre de Recherche du CHU de Quebec, Laval UniversityQuebec, QC, Canada
- Faculty of Pharmacy, Laval UniversityQuebec, QC, Canada
| | - Jacques Simard
- Centre de Recherche du CHU de Quebec, Laval UniversityQuebec, QC, Canada
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Meagher KM, McGowan ML, Settersten RA, Fishman JR, Juengst ET. Precisely Where Are We Going? Charting the New Terrain of Precision Prevention. Annu Rev Genomics Hum Genet 2017; 18:369-387. [PMID: 28441061 PMCID: PMC6203331 DOI: 10.1146/annurev-genom-091416-035222] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
In addition to genetic data, precision medicine research gathers information about three factors that modulate gene expression: lifestyles, environments, and communities. The relevant research tools-epidemiology, environmental assessment, and socioeconomic analysis-are those of public health sciences rather than molecular biology. Because these methods are designed to support inferences and interventions addressing population health, the aspirations of this research are expanding from individualized treatment toward precision prevention in public health. The purpose of this review is to explore the emerging goals and challenges of such a shift to help ensure that the genomics community and public policy makers understand the ethical issues at stake in embracing and pursuing precision prevention. Two emerging goals bear special attention in this regard: (a) public health risk reduction strategies, such as screening, and (b) the application of genomic variation studies to understand and reduce health disparities among population groups.
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Affiliation(s)
- Karen M Meagher
- Center for Genomics and Society, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599;
| | - Michelle L McGowan
- Ethics Center, Division of General and Community Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio 45229;
- Department of Pediatrics, University of Cincinnati, Cincinnati, Ohio 45229
- Department of Women's, Gender, and Sexuality Studies, University of Cincinnati, Cincinnati, Ohio 45221
| | - Richard A Settersten
- Human Development and Family Sciences, College of Public Health and Human Sciences, Oregon State University, Corvallis, Oregon 97331;
| | - Jennifer R Fishman
- Biomedical Ethics Unit, Department of Social Studies of Medicine, McGill University, Montreal, Quebec H3A 1X1, Canada;
| | - Eric T Juengst
- Center for Bioethics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599;
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Abstract
While environmental factors can greatly increase cancer risk, it is clear that an individual’s genetic constitution has strong impact on tumor formation. Hereby we present an alternative cancer predisposition model built on the assumption that efficiencies of DNA maintenance mechanisms in normal cells are similar but not identical for each person. Small variations in an individual’s genetic constitution may result in slightly increased genomic instability and generate typical mutational signatures in normal cells. With recent and expected advances in the next-generation sequencing field, qualitative and quantitative establishment of such mutational signatures in normal tissue must become feasible, and may meanwhile provide a more accurate estimation of individual cancer risks, even in persons without familial antecedents. An additional advantage of this approach is that cancer risk assessment will not strictly rely on the individual’s genetic identity, but will also consider other factors (e.g., environmental and age) that can affect genomic integrity.
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Comparison of the efficiency of colorectal cancer screening programs based on age and genetic risk for reduction of colorectal cancer mortality. Eur J Hum Genet 2017; 25:832-838. [PMID: 28488675 DOI: 10.1038/ejhg.2017.60] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2016] [Revised: 03/05/2017] [Accepted: 03/28/2017] [Indexed: 12/11/2022] Open
Abstract
Given that colorectal cancer risk depends partly on inherited factors, screening program efficiency may be increased by incorporating genetic factors. We compared the efficiency of screening based on age and genetic risk in a simulated population. We simulated a population matching the size, age distribution and colorectal cancer incidence and mortality of Australia. We also simulated the distribution of genetic risk for colorectal cancer based on the expected number of inherited risk alleles of 45 single-nucleotide polymorphisms (SNPs) previously reported as associated with colorectal cancer. We compared the expected colorectal cancer deaths under three screening programs; age-based, genetic-based and combined age-based and genetic-based. The age-based program would prevent 25.4 deaths per 100 000 invited to screen, none of which would be under age 50; the genetic program would prevent 26.2 deaths per 100 000 invited to screen, 16 of which would be under age 50; and the combined program would prevent 24.4 deaths per 100 000 invited to screen, 16 of which would be under age 50. Genetic testing of 1.5 million 45-49 year olds would identify 91% of the people aged under 50 at sufficient risk to warrant screening, potentially saving 16 colorectal cancer deaths each year. Screening eligibility based on genetic risk profile for age is as efficient as eligibility based on age alone for preventing colorectal cancer mortality, but identifies an additional 7% of the population at sufficient risk to benefit from screening who would not normally be screened given they are aged under 50 years.
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