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Rodriguez J, Grassmann F, Xiao Q, Eriksson M, Mao X, Bajalica-Lagercrantz S, Hall P, Czene K. Investigation of Genetic Alterations Associated With Interval Breast Cancer. JAMA Oncol 2024; 10:372-379. [PMID: 38270937 PMCID: PMC10811589 DOI: 10.1001/jamaoncol.2023.6287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 10/16/2023] [Indexed: 01/26/2024]
Abstract
Importance Breast cancers (BCs) diagnosed between 2 screening examinations are called interval cancers (ICs), and they have worse clinicopathological characteristics and poorer prognosis than screen-detected cancers (SDCs). However, the association of rare germline genetic variants with IC have not been studied. Objective To evaluate whether rare germline deleterious protein-truncating variants (PTVs) can be applied to discriminate between IC and SDC while considering mammographic density. Design, Setting, and Participants This population-based genetic association study was based on women aged 40 to 76 years who were attending mammographic screening in Sweden. All women with a diagnosis of BC between January 2001 and January 2016 were included, together with age-matched controls. Patients with BC were followed up for survival until 2021. Statistical analysis was performed from September 2021 to December 2022. Exposure Germline PTVs in 34 BC susceptibility genes as analyzed by targeted sequencing. Main Outcomes and Measures Odds ratios (ORs) were used to compare IC with SDC using logistic regression. Hazard ratios were used to investigate BC-specific survival using Cox regression. Results All 4121 patients with BC (IC, n = 1229; SDC, n = 2892) were female, with a mean (SD) age of 55.5 (7.1) years. There were 5631 age-matched controls. The PTVs of the ATM, BRCA1, BRCA2, CHEK2, and PALB2 genes were more common in patients with IC compared with SDC (OR, 1.48; 95% CI, 1.06-2.05). This association was primarily influenced by BRCA1/2 and PALB2 variants. A family history of BC together with PTVs of any of these genes synergistically increased the probability of receiving a diagnosis of IC rather than SDC (OR, 3.95; 95% CI, 1.97-7.92). Furthermore, 10-year BC-specific survival revealed that if a patient received a diagnosis of an IC, carriers of PTVs in any of these 5 genes had significantly worse survival compared with patients not carrying any of them (hazard ratio, 2.04; 95% CI, 1.06-3.92). All of these associations were further pronounced in a subset of patients with IC who had a low mammographic density at prior screening examination. Conclusions and Relevance The results of this study may be helpful in future optimizations of screening programs that aim to lower mortality as well as the clinical treatment of patients with BC.
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Affiliation(s)
- Juan Rodriguez
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Felix Grassmann
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Health and Medical University, Potsdam, Germany
| | - Qingyang Xiao
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Xinhe Mao
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | | | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Oncology, Södersjukhuset, Stockholm, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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Hanson H, Astiazaran-Symonds E, Amendola LM, Balmaña J, Foulkes WD, James P, Klugman S, Ngeow J, Schmutzler R, Voian N, Wick MJ, Pal T, Tischkowitz M, Stewart DR. Management of individuals with germline pathogenic/likely pathogenic variants in CHEK2: A clinical practice resource of the American College of Medical Genetics and Genomics (ACMG). Genet Med 2023; 25:100870. [PMID: 37490054 PMCID: PMC10623578 DOI: 10.1016/j.gim.2023.100870] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 04/21/2023] [Accepted: 04/24/2023] [Indexed: 07/26/2023] Open
Abstract
PURPOSE Although the role of CHEK2 germline pathogenic variants in cancer predisposition is well known, resources for managing CHEK2 heterozygotes in clinical practice are limited. METHODS An international workgroup developed guidance on clinical management of CHEK2 heterozygotes informed by peer-reviewed publications from PubMed. RESULTS Although CHEK2 is considered a moderate penetrance gene, cancer risks may be considered as a continuous variable, which are influenced by family history and other modifiers. Consequently, early cancer detection and prevention for CHEK2 heterozygotes should be guided by personalized risk estimates. Such estimates may result in both downgrading lifetime breast cancer risks to those similar to the general population or upgrading lifetime risk to a level at which CHEK2 heterozygotes are offered high-risk breast surveillance according to country-specific guidelines. Risk-reducing mastectomy should be guided by personalized risk estimates and shared decision making. Colorectal and prostate cancer surveillance should be considered based on assessment of family history. For CHEK2 heterozygotes who develop cancer, no specific targeted medical treatment is recommended at this time. CONCLUSION Systematic prospective data collection is needed to establish the spectrum of CHEK2-associated cancer risks and to determine yet-unanswered questions, such as the outcomes of surveillance, response to cancer treatment, and survival after cancer diagnosis.
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Affiliation(s)
- Helen Hanson
- Southwest Thames Regional Genetics Service, St George's University Hospitals NHS Foundation Trust, London, United Kingdom
| | - Esteban Astiazaran-Symonds
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD; Department of Medicine, College of Medicine-Tucson, University of Arizona, Tucson, AZ
| | | | - Judith Balmaña
- Hereditary Cancer Genetics Group, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain; Medical Oncology Department, Hospital Universitari Vall d'Hebron, Vall d'Hebron Hospital Campus, Barcelona, Spain
| | - William D Foulkes
- Departments of Human Genetics, Oncology and Medicine, McGill University, Montréal, QC, Canada
| | - Paul James
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC, Australia; Parkville Familial Cancer Centre, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Susan Klugman
- Division of Reproductive & Medical Genetics, Department of Obstetrics & Gynecology and Women's Health, Montefiore Medical Center/Albert Einstein College of Medicine, Bronx, NY
| | - Joanne Ngeow
- Genomic Medicine, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore; Cancer Genetics Service, Division of Medical Oncology, National Cancer Centre Singapore, Singapore
| | - Rita Schmutzler
- Center of Integrated Oncology (CIO), University of Cologne, Cologne, Germany; Center for Hereditary Breast and Ovarian Cancer, University Hospital of Cologne, Cologne, Germany
| | - Nicoleta Voian
- Providence Genetic Risk Clinic, Providence Cancer Institute, Portland, OR
| | - Myra J Wick
- Departments of Obstetrics and Gynecology and Clinical Genomics, Mayo Clinic, Rochester, MN
| | - Tuya Pal
- Department of Medicine, Vanderbilt University Medical Center/Vanderbilt-Ingram Cancer Center, Nashville, TN
| | - Marc Tischkowitz
- Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom
| | - Douglas R Stewart
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD
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Moreno PG, Knoppers T, Zawati MH, Lang M, Knoppers BM, Wolfson M, Nabi H, Dorval M, Simard J, Joly Y. Regulating cancer risk prediction: legal considerations and stakeholder perspectives on the Canadian context. Hum Genet 2023:10.1007/s00439-023-02576-8. [PMID: 37365297 DOI: 10.1007/s00439-023-02576-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 05/22/2023] [Indexed: 06/28/2023]
Abstract
Risk prediction models hold great promise to reduce the impact of cancer in society through advanced warning of risk and improved preventative modalities. These models are evolving and becoming more complex, increasingly integrating genetic screening data and polygenic risk scores as well as calculating risk for multiple types of a disease. However, unclear regulatory compliance requirements applicable to these models raise significant legal uncertainty and new questions about the regulation of medical devices. This paper aims to address these novel regulatory questions by presenting an initial assessment of the legal status likely applicable to risk prediction models in Canada, using the CanRisk tool for breast and ovarian cancer as an exemplar. Legal analysis is supplemented with qualitative perspectives from expert stakeholders regarding the accessibility and compliance challenges of the Canadian regulatory framework. While the paper focuses on the Canadian context, it also refers to European and U.S. regulations in this domain to contrast them. Legal analysis and stakeholder perspectives highlight the need to clarify and update the Canadian regulatory framework for Software as a Medical Device as it applies to risk prediction models. Findings demonstrate how normative guidance perceived as convoluted, contradictory or overly burdensome can discourage innovation, compliance, and ultimately, implementation. This contribution aims to initiate discussion about a more optimal legal framework for risk prediction models as they continue to evolve and are increasingly integrated into landscape for public health.
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Affiliation(s)
- Palmira Granados Moreno
- Centre of Genomics and Policy, Faculty of Medicine, McGill University, Montréal, Québec, Canada
| | - Terese Knoppers
- Centre of Genomics and Policy, Faculty of Medicine, McGill University, Montréal, Québec, Canada.
| | - Ma'n H Zawati
- Centre of Genomics and Policy, Faculty of Medicine, McGill University, Montréal, Québec, Canada
| | - Michael Lang
- Centre of Genomics and Policy, Faculty of Medicine, McGill University, Montréal, Québec, Canada
| | - Bartha M Knoppers
- Centre of Genomics and Policy, Faculty of Medicine, McGill University, Montréal, Québec, Canada
| | - Michael Wolfson
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
| | - Hermann Nabi
- Oncology Division, CHU de Québec-Université Laval Research Center, Québec City, Québec, Canada
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Québec City, Québec, Canada
| | - Michel Dorval
- Oncology Division, CHU de Québec-Université Laval Research Center, Québec City, Québec, Canada
- Faculty of Pharmacy, Université Laval, Québec City, Québec, Canada
- CISSS Chaudière-Appalaches Research Centre, Lévis, Québec, Canada
| | - Jacques Simard
- Genomics Center, CHU de Québec-Université Laval Research Center, Québec City, Québec, Canada
- Department of Molecular Medicine, Université Laval, Québec City, Québec, Canada
| | - Yann Joly
- Centre of Genomics and Policy, Faculty of Medicine, McGill University, Montréal, Québec, Canada
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Møller NB, Boonen DS, Feldner ES, Hao Q, Larsen M, Lænkholm AV, Borg Å, Kvist A, Törngren T, Jensen UB, Boonen SE, Thomassen M, Terkelsen T. Validation of the BOADICEA model for predicting the likelihood of carrying pathogenic variants in eight breast and ovarian cancer susceptibility genes. Sci Rep 2023; 13:8536. [PMID: 37237042 PMCID: PMC10220031 DOI: 10.1038/s41598-023-35755-8] [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: 11/01/2022] [Accepted: 05/23/2023] [Indexed: 05/28/2023] Open
Abstract
BOADICEA is a comprehensive risk prediction model for breast and/or ovarian cancer (BC/OC) and for carrying pathogenic variants (PVs) in cancer susceptibility genes. In addition to BRCA1 and BRCA2, BOADICEA version 6 includes PALB2, CHEK2, ATM, BARD1, RAD51C and RAD51D. To validate its predictions for these genes, we conducted a retrospective study including 2033 individuals counselled at clinical genetics departments in Denmark. All counselees underwent comprehensive genetic testing by next generation sequencing on suspicion of hereditary susceptibility to BC/OC. Likelihoods of PVs were predicted from information about diagnosis, family history and tumour pathology. Calibration was examined using the observed-to-expected ratio (O/E) and discrimination using the area under the receiver operating characteristics curve (AUC). The O/E was 1.11 (95% CI 0.97-1.26) for all genes combined. At sub-categories of predicted likelihood, the model performed well with limited misestimation at the extremes of predicted likelihood. Discrimination was acceptable with an AUC of 0.70 (95% CI 0.66-0.74), although discrimination was better for BRCA1 and BRCA2 than for the other genes in the model. This suggests that BOADICEA remains a valid decision-making aid for determining which individuals to offer comprehensive genetic testing for hereditary susceptibility to BC/OC despite suboptimal calibration for individual genes in this population.
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Affiliation(s)
- Nanna Bæk Møller
- Department of Clinical Genetics, Aarhus University Hospital, Brendstrupgårdsvej 21, 8200, Aarhus N, Denmark
| | - Desirée Sofie Boonen
- Department of Clinical Genetics, Odense University Hospital, J. B. Winsløws Vej 4, 5000, Odense, Denmark
| | - Elisabeth Simone Feldner
- Department of Clinical Genetics, Odense University Hospital, J. B. Winsløws Vej 4, 5000, Odense, Denmark
| | - Qin Hao
- Department of Clinical Genetics, Odense University Hospital, J. B. Winsløws Vej 4, 5000, Odense, Denmark
| | - Martin Larsen
- Department of Clinical Genetics, Odense University Hospital, J. B. Winsløws Vej 4, 5000, Odense, Denmark
| | - Anne-Vibeke Lænkholm
- Department of Surgical Pathology, Zealand University Hospital, Roskilde, Denmark
| | - Åke Borg
- Division of Oncology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Anders Kvist
- Division of Oncology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Therese Törngren
- Division of Oncology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Uffe Birk Jensen
- Department of Clinical Genetics, Aarhus University Hospital, Brendstrupgårdsvej 21, 8200, Aarhus N, Denmark
| | - Susanne Eriksen Boonen
- Department of Clinical Genetics, Odense University Hospital, J. B. Winsløws Vej 4, 5000, Odense, Denmark
| | - Mads Thomassen
- Department of Clinical Genetics, Odense University Hospital, J. B. Winsløws Vej 4, 5000, Odense, Denmark.
| | - Thorkild Terkelsen
- Department of Clinical Genetics, Aarhus University Hospital, Brendstrupgårdsvej 21, 8200, Aarhus N, Denmark.
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5
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McVeigh TP, Sweeney KJ, Brennan DJ, McVeigh UM, Ward S, Strydom A, Seal S, Astbury K, Donnellan P, Higgins J, Keane M, Kerin MJ, Malone C, McGough P, McLaughlin R, O'Leary M, Rushe M, Barry MK, MacGregor G, Sugrue M, Yousif A, Al-Azawi D, Berkeley E, Boyle TJ, Connolly EM, Nolan C, Richardson E, Giffney C, Doyle SB, Broderick S, Boyd W, McVey R, Walsh T, Farrell M, Gallagher DJ, Rahman N, George AJ. A pilot study investigating feasibility of mainstreaming germline BRCA1 and BRCA2 testing in high-risk patients with breast and/or ovarian cancer in three tertiary Cancer Centres in Ireland. Fam Cancer 2023; 22:135-149. [PMID: 36029389 DOI: 10.1007/s10689-022-00313-0] [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: 06/20/2022] [Accepted: 08/13/2022] [Indexed: 11/24/2022]
Abstract
In the Republic of Ireland (ROI), BRCA1/BRCA2 genetic testing has been traditionally undertaken in eligible individuals, after pre-test counselling by a Clinical Geneticist/Genetic Counsellor. Clinical Genetics services in ROI are poorly resourced, with routine waiting times for appointments at the time of this pilot often extending beyond a year. The consequent prolonged waiting times are unacceptable where therapeutic decision-making depends on the patient's BRCA status. "Mainstreaming" BRCA1/BRCA2 testing through routine oncology/surgical clinics has been implemented successfully in other centres in the UK and internationally. We aimed to pilot this pathway in three Irish tertiary centres. A service evaluation project was undertaken over a 6-month period between January and July 2017. Eligible patients, fulfilling pathology and age-based inclusion criteria defined by TGL clinical, were identified, and offered constitutional BRCA1/BRCA2 testing after pre-test counselling by treating clinicians. Tests were undertaken by TGL Clinical. Results were returned to clinicians by secure email. Onward referrals of patients with uncertain/pathogenic results, or suspicious family histories, to Clinical Genetics were made by the treating team. Surveys assessing patient and clinician satisfaction were sent to participating clinicians and a sample of participating patients. Data was collected with respect to diagnostic yield, turnaround time, onward referral rates, and patient and clinician feedback. A total of 101 patients underwent diagnostic germline BRCA1/BRCA2 tests through this pathway. Pathogenic variants were identified in 12 patients (12%). All patients in whom variants were identified were appropriately referred to Clinical Genetics. At least 12 additional patients with uninformative BRCA1/BRCA2 tests were also referred for formal assessment by Clinical Geneticist or Genetic Counsellor. Issues were noted in terms of time pressures and communication of results to patients. Results from a representative sample of participants completing the satisfaction survey indicated that the pathway was acceptable to patients and clinicians. Mainstreaming of constitutional BRCA1/BRCA2 testing guided by age- and pathology-based criteria is potentially feasible for patients with breast cancer as well as patients with ovarian cancer in Ireland.
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Affiliation(s)
- Terri Patricia McVeigh
- Cancer Genetics Unit, Royal Marsden NHS Foundation Trust, London, UK.
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK.
| | - Karl J Sweeney
- Saolta Health Care Group, Galway University Hospital, Galway, Ireland
| | - Donal J Brennan
- Mater Misericordiae University Hospital, Dublin, Ireland
- The National Maternity Hospital, Holles St, Dublin, Ireland
| | | | - Simon Ward
- Cancer Genetics Unit, Royal Marsden NHS Foundation Trust, London, UK
| | | | | | - Katherine Astbury
- Saolta Health Care Group, Galway University Hospital, Galway, Ireland
| | - Paul Donnellan
- Saolta Health Care Group, Galway University Hospital, Galway, Ireland
| | - Joanne Higgins
- Saolta Health Care Group, Galway University Hospital, Galway, Ireland
| | - Maccon Keane
- Saolta Health Care Group, Galway University Hospital, Galway, Ireland
| | - Michael J Kerin
- Saolta Health Care Group, Galway University Hospital, Galway, Ireland
- National University of Ireland, Galway, Ireland
| | - Carmel Malone
- Saolta Health Care Group, Galway University Hospital, Galway, Ireland
- National University of Ireland, Galway, Ireland
| | - Pauline McGough
- Saolta Health Care Group, Galway University Hospital, Galway, Ireland
| | - Ray McLaughlin
- Saolta Health Care Group, Galway University Hospital, Galway, Ireland
| | - Michael O'Leary
- Saolta Health Care Group, Galway University Hospital, Galway, Ireland
| | - Margaret Rushe
- Saolta Health Care Group, Galway University Hospital, Galway, Ireland
| | - Michael Kevin Barry
- Saolta Health Care Group, Mayo University Hospital, Co Mayo, Castlebar, Ireland
| | - Geraldine MacGregor
- Saolta University Health Care Group, Letterkenny University Hospital, Co Donegal, Letterkenny, Ireland
| | - Michael Sugrue
- Saolta University Health Care Group, Letterkenny University Hospital, Co Donegal, Letterkenny, Ireland
| | - Ala Yousif
- Saolta University Hospital Group, Sligo University Hospital, Sligo, Ireland
| | | | | | | | | | | | | | | | | | | | - William Boyd
- Mater Misericordiae University Hospital, Dublin, Ireland
| | - Ruaidhri McVey
- Mater Misericordiae University Hospital, Dublin, Ireland
| | - Thomas Walsh
- Mater Misericordiae University Hospital, Dublin, Ireland
| | | | - David J Gallagher
- St James's University Hospital, Dublin, Ireland
- Mater Private Hospital, Dublin, Ireland
| | | | - Angela J George
- Cancer Genetics Unit, Royal Marsden NHS Foundation Trust, London, UK
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
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6
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Psychological factors and the uptake of preventative measures in BRCA1/2 pathogenic variant carriers: results of a prospective cohort study. Hered Cancer Clin Pract 2022; 20:38. [PMID: 36536421 PMCID: PMC9761978 DOI: 10.1186/s13053-022-00244-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 11/23/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Women carrying BRCA1/2 pathogenic variants are exposed to elevated risks of developing breast cancer (BC) and are faced by a complex decision-making process on preventative measures, i.e., risk-reducing mastectomy (RRM), and intensified breast surveillance (IBS). In this prospective cohort study we investigated the effect of anxiety, personality factors and coping styles on the decision-making process on risk management options in women with pathogenic variants in BRCA1/2. METHODS Breast cancer unaffected and affected women with a pathogenic variant in the BRCA1 or BRCA2 gene were psychologically evaluated immediately before (T0), 6 to 8 weeks (T1) and 6 to 8 months (T2) after the disclosure of their genetic test results. Uptake of RRM and IBS was assessed at T2. Psychological data were gathered using questionnaires on risk perception, personality factors, coping styles, decisional conflict, depression and anxiety, including the Hospital Anxiety and Depression Scale (HADS). We performed tests on statistical significance and fitted a logistic regression based on significance level. RESULTS A total of 98 women were included in the analysis. Baseline anxiety levels in women opting for RRM were high but decreased over time, while they increased in women opting for intensified breast surveillance (IBS). Elevated levels of anxiety after genetic test result disclosure (T1) were associated with the decision to undergo RRM (p < 0.01; OR = 1.2, 95% CI = 1.05-1.42), while personal BC history and personality factors seemed to be less relevant. CONCLUSIONS Considering psychosocial factors influencing the decision-making process of women with pathogenic variants in BRCA1/2 may help improving their genetic and psychological counselling. When opting for IBS they may profit from additional medical and psychological counselling. TRIAL REGISTRATION Retrospectively registered at the German Clinical Trials Register under DRKS00027566 on January 13, 2022.
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7
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Lee A, Mavaddat N, Cunningham A, Carver T, Ficorella L, Archer S, Walter FM, Tischkowitz M, Roberts J, Usher-Smith J, Simard J, Schmidt MK, Devilee P, Zadnik V, Jürgens H, Mouret-Fourme E, De Pauw A, Rookus M, Mooij TM, Pharoah PP, Easton DF, Antoniou AC. Enhancing the BOADICEA cancer risk prediction model to incorporate new data on RAD51C, RAD51D, BARD1 updates to tumour pathology and cancer incidence. J Med Genet 2022; 59:1206-1218. [PMID: 36162851 PMCID: PMC9691826 DOI: 10.1136/jmedgenet-2022-108471] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 04/23/2022] [Indexed: 01/12/2023]
Abstract
BACKGROUND BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) for breast cancer and the epithelial tubo-ovarian cancer (EOC) models included in the CanRisk tool (www.canrisk.org) provide future cancer risks based on pathogenic variants in cancer-susceptibility genes, polygenic risk scores, breast density, questionnaire-based risk factors and family history. Here, we extend the models to include the effects of pathogenic variants in recently established breast cancer and EOC susceptibility genes, up-to-date age-specific pathology distributions and continuous risk factors. METHODS BOADICEA was extended to further incorporate the associations of pathogenic variants in BARD1, RAD51C and RAD51D with breast cancer risk. The EOC model was extended to include the association of PALB2 pathogenic variants with EOC risk. Age-specific distributions of oestrogen-receptor-negative and triple-negative breast cancer status for pathogenic variant carriers in these genes and CHEK2 and ATM were also incorporated. A novel method to include continuous risk factors was developed, exemplified by including adult height as continuous. RESULTS BARD1, RAD51C and RAD51D explain 0.31% of the breast cancer polygenic variance. When incorporated into the multifactorial model, 34%-44% of these carriers would be reclassified to the near-population and 15%-22% to the high-risk categories based on the UK National Institute for Health and Care Excellence guidelines. Under the EOC multifactorial model, 62%, 35% and 3% of PALB2 carriers have lifetime EOC risks of <5%, 5%-10% and >10%, respectively. Including height as continuous, increased the breast cancer relative risk variance from 0.002 to 0.010. CONCLUSIONS These extensions will allow for better personalised risks for BARD1, RAD51C, RAD51D and PALB2 pathogenic variant carriers and more informed choices on screening, prevention, risk factor modification or other risk-reducing options.
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Affiliation(s)
- Andrew Lee
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Nasim Mavaddat
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Alex Cunningham
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Tim Carver
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Lorenzo Ficorella
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Stephanie Archer
- Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Fiona M Walter
- Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Marc Tischkowitz
- Department of Medical Genetics and National Institute for Health Research, Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, UK
| | - Jonathan Roberts
- Department of Medical Genetics and National Institute for Health Research, Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, UK
| | - Juliet Usher-Smith
- Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Jacques Simard
- Centre Hospitalier Universitaire de Québec-Université Laval Research Center, Université Laval, Quebec, Quebec, Canada
| | - Marjanka K Schmidt
- Division of Molecular Pathology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Peter Devilee
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Vesna Zadnik
- Epidemiology and Cancer Registry, Institute of Oncology, Ljubljana, Slovenia
| | - Hannes Jürgens
- Clinic of Hematology and Oncology, Tartu University Hospital, Tartu, Estonia
| | | | | | - Matti Rookus
- Department of Epidemiology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Thea M Mooij
- Department of Epidemiology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Paul Pd 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
| | - 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
| | - Antonis C Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
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8
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Familial history and prevalence of BRCA1, BRCA2 and TP53 pathogenic variants in HBOC Brazilian patients from a public healthcare service. Sci Rep 2022; 12:18629. [PMID: 36329109 PMCID: PMC9633799 DOI: 10.1038/s41598-022-23012-3] [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: 04/25/2022] [Accepted: 10/21/2022] [Indexed: 11/06/2022] Open
Abstract
Several studies have demonstrated the cost-effectiveness of genetic testing for surveillance and treatment of carriers of germline pathogenic variants associated with hereditary breast/ovarian cancer syndrome (HBOC). In Brazil, seventy percent of the population is assisted by the public Unified Health System (SUS), where genetic testing is still unavailable. And few studies were performed regarding the prevalence of HBOC pathogenic variants in this context. Here, we estimated the prevalence of germline pathogenic variants in BRCA1, BRCA2 and TP53 genes in Brazilian patients suspected of HBOC and referred to public healthcare service. Predictive power of risk prediction models for detecting mutation carriers was also evaluated. We found that 41 out of 257 tested patients (15.9%) were carriers of pathogenic variants in the analyzed genes. Most frequent pathogenic variant was the founder Brazilian mutation TP53 c.1010G > A (p.Arg337His), adding to the accumulated evidence that supports inclusion of TP53 in routine testing of Brazilian HBOC patients. Surprisingly, BRCA1 c.5266dupC (p.Gln1756fs), a frequently reported pathogenic variant in Brazilian HBOC patients, was not observed. Regarding the use of predictive models, we found that familial history of cancer might be used to improve selection or prioritization of patients for genetic testing, especially in a context of limited resources.
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9
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Li S, MacInnis RJ, Lee A, Nguyen-Dumont T, Dorling L, Carvalho S, Dite GS, Shah M, Luccarini C, Wang Q, Milne RL, Jenkins MA, Giles GG, Dunning AM, Pharoah PDP, Southey MC, Easton DF, Hopper JL, Antoniou AC. Segregation analysis of 17,425 population-based breast cancer families: Evidence for genetic susceptibility and risk prediction. Am J Hum Genet 2022; 109:1777-1788. [PMID: 36206742 PMCID: PMC9606477 DOI: 10.1016/j.ajhg.2022.09.006] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 09/12/2022] [Indexed: 01/25/2023] Open
Abstract
Rare pathogenic variants in known breast cancer-susceptibility genes and known common susceptibility variants do not fully explain the familial aggregation of breast cancer. To investigate plausible genetic models for the residual familial aggregation, we studied 17,425 families ascertained through population-based probands, 86% of whom were screened for pathogenic variants in BRCA1, BRCA2, PALB2, CHEK2, ATM, and TP53 via gene-panel sequencing. We conducted complex segregation analyses and fitted genetic models in which breast cancer incidence depended on the effects of known susceptibility genes and other unidentified major genes and a normally distributed polygenic component. The proportion of familial variance explained by the six genes was 46% at age 20-29 years and decreased steadily with age thereafter. After allowing for these genes, the best fitting model for the residual familial variance included a recessive risk component with a combined genotype frequency of 1.7% (95% CI: 0.3%-5.4%) and a penetrance to age 80 years of 69% (95% CI: 38%-95%) for homozygotes, which may reflect the combined effects of multiple variants acting in a recessive manner, and a polygenic variance of 1.27 (95% CI: 0.94%-1.65), which did not vary with age. The proportion of the residual familial variance explained by the recessive risk component was 40% at age 20-29 years and decreased with age thereafter. The model predicted age-specific familial relative risks consistent with those observed by large epidemiological studies. The findings have implications for strategies to identify new breast cancer-susceptibility genes and improve disease-risk prediction, especially at a young age.
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Affiliation(s)
- Shuai Li
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, 207 Bouverie Street, Carlton, VIC 3053, Australia; Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, VIC 3051, Australia.
| | - Robert J MacInnis
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, 207 Bouverie Street, Carlton, VIC 3053, Australia; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC 3004, Australia
| | - Andrew Lee
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Tu Nguyen-Dumont
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; Department of Clinical Pathology, The University of Melbourne, Parkville, VIC 3051, Australia
| | - Leila Dorling
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Sara Carvalho
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Gillian S Dite
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, 207 Bouverie Street, Carlton, VIC 3053, Australia; Genetic Technologies Ltd., Fitzroy, VIC 3065, Australia
| | - Mitul Shah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Craig Luccarini
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Roger L Milne
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, 207 Bouverie Street, Carlton, VIC 3053, Australia; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC 3004, Australia
| | - Mark A Jenkins
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, 207 Bouverie Street, Carlton, VIC 3053, Australia
| | - Graham G Giles
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, 207 Bouverie Street, Carlton, VIC 3053, Australia; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC 3004, Australia
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Paul D P Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Melissa C Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC 3004, Australia; Department of Clinical Pathology, The University of Melbourne, Parkville, VIC 3051, Australia
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, 207 Bouverie Street, Carlton, VIC 3053, Australia
| | - Antonis C Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
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10
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Fonseca MM, Alhassan T, Nisha Y, Koszycki D, Schwarz BA, Segal R, Arnaout A, Ramsay T, Lau J, Seely JM. Randomized trial of surveillance with abbreviated MRI in women with a personal history of breast cancer- impact on patient anxiety and cancer detection. BMC Cancer 2022; 22:774. [PMID: 35840916 PMCID: PMC9287889 DOI: 10.1186/s12885-022-09792-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Accepted: 06/17/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Abbreviated breast MRI (A-MRI) substantially reduces the image acquisition and reading times and has been reported to have similar diagnostic accuracy as a full diagnostic protocol but has not been evaluated prospectively with respect to impact on psychological distress in women with a prior history of breast cancer (PHBC). This study aimed to determine if surveillance mammography (MG) plus A-MRI reduced psychological distress and if A-MRI improved cancer detection rates (CDR) as compared to MG alone. METHODS This prospective controlled trial of parallel design was performed at a tertiary cancer center on asymptomatic women with PHBC who were randomized into two groups: routine surveillance with MG or intervention of MG plus A-MRI in a 1:1 ratio. Primary outcome was anxiety measured by four validated questionnaires at three different time-points during the study. Other parameters including CDR and positive predictive value for biopsy (PPV3) were compared between imaging modalities of MG and A-MRI. Tissue diagnoses or 1 year of follow-up were used to establish the reference standard. Linear mixed models were used to analyze anxiety measures and Fisher's exact test to compare imaging outcomes. RESULTS One hundred ninety-eight patients were allocated to either MG alone (94) or MG plus A-MRI (104). No significant group difference emerged for improvement in trait anxiety, worry and perceived health status (all Time-by-surveillance group interaction ps > .05). There was some advantage of A-MRI in reducing state anxiety at Time 2 (p < .05). Anxiety scores in all questionnaires were similarly elevated in both groups (50.99 ± 4.6 with MG alone vs 51.73 ± 2.56 with MG plus A-MRI, p > 0.05) and did not change over time. A-MRI detected 5 invasive cancers and 1 ductal carcinoma in situ (DCIS), and MG detected 1 DCIS. A-MRI had higher incremental CDR (48/1000(5/104) vs MG 5/1000(1/198, p = 0.01)) and higher biopsy rates (19.2% (20/104) vs MG 2.1% (2/94), p < 0.00001) with no difference in PPV3 (A-MRI 28.6% (6/21) vs MG 16.7% (1/6, p > .05). CONCLUSION There was no significant impact of A-MRI to patient anxiety or perceived health status. Compared to MG alone, A-MRI had significantly higher incremental cancer detection in PHBC. Despite a higher rate of biopsies, A-MRI had no demonstrable impact on anxiety, worry, and perceived health status. TRIAL REGISTRATION ClinicalTrials.gov ( NCT02244593 ). Prospectively registered on Sept. 14, 2014.
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Affiliation(s)
| | - Tasneen Alhassan
- Breast Imaging fellow 2016-2017, Former University of Ottawa, Now Dubai, United Arab Emirates
| | - Yashmin Nisha
- University of Ottawa, Breast Imaging fellow, Ottawa, 2019-2020, Canada
| | - Diana Koszycki
- Research Chair in Mental Health, Institut du Savoir Montfort, Ottawa, Canada.,Faculty of Education (Counselling Psychology), Faculty of Medicine (Psychiatry), Institut du Savoir Monfort, Ottawa, Canada
| | | | - Roanne Segal
- Department of Medicine, Oncology, The Ottawa Hospital Cancer Center, University of Ottawa, Ottawa, Canada
| | - Angel Arnaout
- Breast Surgical Oncology and Oncoplastic Surgery, University of Ottawa, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Tim Ramsay
- Clinical Epidemiology Program, School of Epidemiology and Public Health, Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Canada
| | - Jacqueline Lau
- Department of Radiology, University of Ottawa, Ottawa, Canada
| | - Jean M Seely
- Departments of Radiology and Surgery, Department of Medical Imaging, The Ottawa Hospital, Ottawa Hospital Research Institute, University of Ottawa, General Campus, 501 Smyth Rd, Ottawa, ON, K1H 8L6, Canada.
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11
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Liberto JM, Chen SY, Shih IM, Wang TH, Wang TL, Pisanic TR. Current and Emerging Methods for Ovarian Cancer Screening and Diagnostics: A Comprehensive Review. Cancers (Basel) 2022; 14:2885. [PMID: 35740550 PMCID: PMC9221480 DOI: 10.3390/cancers14122885] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 06/06/2022] [Accepted: 06/08/2022] [Indexed: 02/04/2023] Open
Abstract
With a 5-year survival rate of less than 50%, ovarian high-grade serous carcinoma (HGSC) is one of the most highly aggressive gynecological malignancies affecting women today. The high mortality rate of HGSC is largely attributable to delays in diagnosis, as most patients remain undiagnosed until the late stages of -disease. There are currently no recommended screening tests for ovarian cancer and there thus remains an urgent need for new diagnostic methods, particularly those that can detect the disease at early stages when clinical intervention remains effective. While diagnostics for ovarian cancer share many of the same technical hurdles as for other cancer types, the low prevalence of the disease in the general population, coupled with a notable lack of sensitive and specific biomarkers, have made the development of a clinically useful screening strategy particularly challenging. Here, we present a detailed review of the overall landscape of ovarian cancer diagnostics, with emphasis on emerging methods that employ novel protein, genetic, epigenetic and imaging-based biomarkers and/or advanced diagnostic technologies for the noninvasive detection of HGSC, particularly in women at high risk due to germline mutations such as BRCA1/2. Lastly, we discuss the translational potential of these approaches for achieving a clinically implementable solution for screening and diagnostics of early-stage ovarian cancer as a means of ultimately improving patient outcomes in both the general and high-risk populations.
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Affiliation(s)
- Juliane M. Liberto
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA; (J.M.L.); (I.-M.S.); (T.-L.W.)
| | - Sheng-Yin Chen
- School of Medicine, Chang Gung University, 33302 Taoyuan, Taiwan;
| | - Ie-Ming Shih
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA; (J.M.L.); (I.-M.S.); (T.-L.W.)
- Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA;
| | - Tza-Huei Wang
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA;
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
- Johns Hopkins Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Tian-Li Wang
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA; (J.M.L.); (I.-M.S.); (T.-L.W.)
- Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA;
| | - Thomas R. Pisanic
- Johns Hopkins Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD 21218, USA
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12
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Mavaddat N, Dorling L, Carvalho S, Allen J, González-Neira A, Keeman R, Bolla MK, Dennis J, Wang Q, Ahearn TU, Andrulis IL, Beckmann MW, Behrens S, Benitez J, Bermisheva M, Blomqvist C, Bogdanova NV, Bojesen SE, Briceno I, Brüning T, Camp NJ, Campbell A, Castelao JE, Chang-Claude J, Chanock SJ, Chenevix-Trench G, Christiansen H, Czene K, Dörk T, Eriksson M, Evans DG, Fasching PA, Figueroa JD, Flyger H, Gabrielson M, Gago-Dominguez M, Geisler J, Giles GG, Guénel P, Hadjisavvas A, Hahnen E, Hall P, Hamann U, Hartikainen JM, Hartman M, Hoppe R, Howell A, Jakubowska A, Jung A, Khusnutdinova EK, Kristensen VN, Li J, Lim SH, Lindblom A, Loizidou MA, Lophatananon A, Lubinski J, Madsen MJ, Mannermaa A, Manoochehri M, Margolin S, Mavroudis D, Milne RL, Mohd Taib NA, Morra A, Muir K, Obi N, Osorio A, Park-Simon TW, Peterlongo P, Radice P, Saloustros E, Sawyer EJ, Schmutzler RK, Shah M, Sim X, Southey MC, Thorne H, Tomlinson I, Torres D, Truong T, Yip CH, Spurdle AB, Vreeswijk MPG, Dunning AM, García-Closas M, Pharoah PDP, Kvist A, Muranen TA, Nevanlinna H, Teo SH, Devilee P, Schmidt MK, Easton DF. Pathology of Tumors Associated With Pathogenic Germline Variants in 9 Breast Cancer Susceptibility Genes. JAMA Oncol 2022; 8:e216744. [PMID: 35084436 PMCID: PMC8796069 DOI: 10.1001/jamaoncol.2021.6744] [Citation(s) in RCA: 42] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
IMPORTANCE Rare germline genetic variants in several genes are associated with increased breast cancer (BC) risk, but their precise contributions to different disease subtypes are unclear. This information is relevant to guidelines for gene panel testing and risk prediction. OBJECTIVE To characterize tumors associated with BC susceptibility genes in large-scale population- or hospital-based studies. DESIGN, SETTING, AND PARTICIPANTS The multicenter, international case-control analysis of the BRIDGES study included 42 680 patients and 46 387 control participants, comprising women aged 18 to 79 years who were sampled independently of family history from 38 studies. Studies were conducted between 1991 and 2016. Sequencing and analysis took place between 2016 and 2021. EXPOSURES Protein-truncating variants and likely pathogenic missense variants in ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51C, RAD51D, and TP53. MAIN OUTCOMES AND MEASURES The intrinsic-like BC subtypes as defined by estrogen receptor, progesterone receptor, and ERBB2 (formerly known as HER2) status, and tumor grade; morphology; size; stage; lymph node involvement; subtype-specific odds ratios (ORs) for carrying protein-truncating variants and pathogenic missense variants in the 9 BC susceptibility genes. RESULTS The mean (SD) ages at interview (control participants) and diagnosis (cases) were 55.1 (11.9) and 55.8 (10.6) years, respectively; all participants were of European or East Asian ethnicity. There was substantial heterogeneity in the distribution of intrinsic subtypes by gene. RAD51C, RAD51D, and BARD1 variants were associated mainly with triple-negative disease (OR, 6.19 [95% CI, 3.17-12.12]; OR, 6.19 [95% CI, 2.99-12.79]; and OR, 10.05 [95% CI, 5.27-19.19], respectively). CHEK2 variants were associated with all subtypes (with ORs ranging from 2.21-3.17) except for triple-negative disease. For ATM variants, the association was strongest for the hormone receptor (HR)+ERBB2- high-grade subtype (OR, 4.99; 95% CI, 3.68-6.76). BRCA1 was associated with increased risk of all subtypes, but the ORs varied widely, being highest for triple-negative disease (OR, 55.32; 95% CI, 40.51-75.55). BRCA2 and PALB2 variants were also associated with triple-negative disease. TP53 variants were most strongly associated with HR+ERBB2+ and HR-ERBB2+ subtypes. Tumors occurring in pathogenic variant carriers were of higher grade. For most genes and subtypes, a decline in ORs was observed with increasing age. Together, the 9 genes were associated with 27.3% of all triple-negative tumors in women 40 years or younger. CONCLUSIONS AND RELEVANCE The results of this case-control study suggest that variants in the 9 BC risk genes differ substantially in their associated pathology but are generally associated with triple-negative and/or high-grade disease. Knowing the age and tumor subtype distributions associated with individual BC genes can potentially aid guidelines for gene panel testing, risk prediction, and variant classification and guide targeted screening strategies.
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Affiliation(s)
| | - Nasim Mavaddat
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, England
| | - Leila Dorling
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, England
| | - Sara Carvalho
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, England
| | - Jamie Allen
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, England
| | - Anna González-Neira
- Human Cancer Genetics Programme, Spanish National Cancer Research Centre, Madrid, Spain
| | - Renske Keeman
- Division of Molecular Pathology, the Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands
| | - Manjeet K Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, England
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, England
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, England
| | - Thomas U Ahearn
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland
| | - 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
| | - Matthias W Beckmann
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Sabine Behrens
- Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
| | - Javier Benitez
- Human Cancer Genetics Programme, Spanish National Cancer Research Centre, Madrid, Spain.,Biomedical Network on Rare Diseases, Madrid, Spain
| | - Marina Bermisheva
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre of the Russian Academy of Sciences, Ufa, Russia
| | - Carl Blomqvist
- Department of Oncology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - Natalia V Bogdanova
- Department of Radiation Oncology, Hannover Medical School, Hannover, Germany.,Gynaecology Research Unit, Hannover Medical School, Hannover, 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, University of Copenhagen, Copenhagen, Denmark
| | | | - Thomas Brüning
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum, Bochum, Germany
| | - Nicola J Camp
- Department of Internal Medicine and Huntsman Cancer Institute, University of Utah, Salt Lake City
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Edinburgh, Scotland.,Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, Scotland
| | - Jose E Castelao
- Oncology and Genetics Unit, Instituto de Investigación Sanitaria Galicia Sur, Xerencia de Xestion Integrada de Vigo-SERGAS, Vigo, Spain
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany.,Cancer Epidemiology Group, University Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland
| | - Georgia Chenevix-Trench
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Hans Christiansen
- Department of Radiation Oncology, Hannover Medical School, Hannover, Germany
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Thilo Dörk
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany
| | - Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, 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, England.,North West Genomics Laboratory Hub, Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University National Health Service Foundation Trust, Manchester Academic Health Science Centre, Manchester, England
| | - Peter A Fasching
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany.,David Geffen School of Medicine, Department of Medicine Division of Hematology and Oncology, University of California at Los Angeles
| | - Jonine D Figueroa
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, Scotland.,Cancer Research UK Edinburgh Centre, University of Edinburgh, Edinburgh, Scotland
| | - Henrik Flyger
- Department of Breast Surgery, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Marike Gabrielson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Manuela Gago-Dominguez
- Fundación Pública Galega de Medicina Xenómica, Instituto de Investigación Sanitaria de Santiago de Compostela, Complejo Hospitalario Universitario de Santiago, SERGAS, Santiago de Compostela, Spain.,Moores Cancer Center, University of California San Diego, La Jolla
| | - Jürgen Geisler
- Department of Oncology, Akershus University Hospital, Lørenskog, Norway.,Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Campus at Akershus University Hospital, Norway
| | - Graham G Giles
- Cancer Epidemiology Division, 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
| | - Pascal Guénel
- Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP, Villejuif, France
| | - Andreas Hadjisavvas
- Department of Cancer Genetics, Therapeutics and Ultrastructural Pathology, The Cyprus Institute of Neurology & Genetics, Nicosia, Cyprus.,Cyprus School of Molecular Medicine, The Cyprus Institute of Neurology & Genetics, Nicosia, Cyprus
| | - Eric Hahnen
- Center for Familial Breast and Ovarian Cancer, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Center for Integrated Oncology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - 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, Heidelberg, Germany
| | - Jaana M Hartikainen
- Translational Cancer Research Area, University of Eastern Finland, Kuopio, Finland.,Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland
| | - Mikael Hartman
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.,Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore.,Department of Surgery, National University Health System, Singapore, Singapore
| | - Reiner Hoppe
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany.,University of Tübingen, Tübingen, Germany
| | - Anthony Howell
- Division of Cancer Sciences, University of Manchester, Manchester, England
| | - 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
| | - Audrey Jung
- Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
| | - Elza K 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
| | - Vessela N Kristensen
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway.,Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Jingmei Li
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore.,Human Genetics Division, Genome Institute of Singapore, Singapore, Singapore
| | - Swee Ho Lim
- Breast Department, KK Women's and Children's Hospital, Singapore, Singapore.,SingHealth Duke-NUS Breast Centre, Singapore, Singapore
| | - Annika Lindblom
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Maria A Loizidou
- Department of Cancer Genetics, Therapeutics and Ultrastructural Pathology, The Cyprus Institute of Neurology & Genetics, Nicosia, Cyprus.,Cyprus School of Molecular Medicine, The Cyprus Institute of Neurology & Genetics, Nicosia, Cyprus
| | - Artitaya Lophatananon
- Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, England
| | - Jan Lubinski
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Michael J Madsen
- Department of Internal Medicine and Huntsman Cancer Institute, University of Utah, Salt Lake City
| | - 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, Heidelberg, Germany
| | - Sara Margolin
- Department of Oncology, Södersjukhuset, Stockholm, Sweden.,Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
| | - Dimitrios Mavroudis
- Department of Medical Oncology, University Hospital of Heraklion, Heraklion, Greece
| | - Roger L Milne
- Cancer Epidemiology Division, 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
| | - Nur Aishah Mohd Taib
- Department of Surgery, Faculty of Medicine University of Malaya, UM Cancer Research Institute, Kuala Lumpur, Malaysia
| | - Anna Morra
- Division of Molecular Pathology, the Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands
| | - Kenneth Muir
- Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, England
| | - Nadia Obi
- Institute for Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Ana Osorio
- Human Cancer Genetics Programme, Spanish National Cancer Research Centre, Madrid, Spain.,Centro de Investigación en Red de Enfermedades Raras, Madrid, Spain
| | | | - Paolo Peterlongo
- Genome Diagnostics Program, IFOM-the FIRC Institute of Molecular Oncology, Milan, Italy
| | - Paolo Radice
- Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | | | - Elinor J Sawyer
- School of Cancer & Pharmaceutical Sciences, Comprehensive Cancer Centre, Guy's Campus, King's College London, London, England
| | - Rita K Schmutzler
- Center for Familial Breast and Ovarian Cancer, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Center for Integrated Oncology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Center for Molecular Medicine Cologne, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Mitul Shah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, England
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Melissa C Southey
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.,Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.,Department of Clinical Pathology, University of Melbourne, Melbourne, Victoria, Australia
| | - Heather Thorne
- Research Department, Peter MacCallum Cancer Center, Melbourne, Victoria, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Ian Tomlinson
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, England.,Wellcome Trust Centre for Human Genetics and Oxford National Institute for Health Research Biomedical Research Centre, University of Oxford, Oxford, England
| | - Diana Torres
- Molecular Genetics of Breast Cancer, German Cancer Research Center, Heidelberg, Germany.,Institute of Human Genetics, Pontificia Universidad Javeriana, Bogota, Colombia
| | - Thérèse Truong
- Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP, Villejuif, France
| | - Cheng Har Yip
- Department of Surgery, Faculty of Medicine University of Malaya, UM Cancer Research Institute, Kuala Lumpur, Malaysia.,Subang Jaya Medical Centre, Subang Jaya, Selangor, Malaysia
| | - Amanda B Spurdle
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Maaike P G Vreeswijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, England
| | - Montserrat García-Closas
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland
| | - Paul D P Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, England.,Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, England
| | - Anders Kvist
- Division of Oncology and Pathology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Taru A Muranen
- Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - Heli Nevanlinna
- Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - Soo Hwang Teo
- Department of Surgery, Faculty of Medicine University of Malaya, UM Cancer Research Institute, Kuala Lumpur, Malaysia.,Breast Cancer Research Programme, Cancer Research Malaysia, Subang Jaya, Selangor, Malaysia
| | - Peter Devilee
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands.,Department of Pathology, Leiden University Medical Center, Leiden, the Netherlands
| | - Marjanka K Schmidt
- Division of Molecular Pathology, the Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands.,Department of Clinical Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, England.,Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, England
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13
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Liu J, Zhao H, Zheng Y, Dong L, Zhao S, Huang Y, Huang S, Qian T, Zou J, Liu S, Li J, Yan Z, Li Y, Zhang S, Huang X, Wang W, Li Y, Wang J, Ming Y, Li X, Xing Z, Qin L, Zhao Z, Jia Z, Li J, Liu G, Zhang M, Feng K, Wu J, Zhang J, Yang Y, Wu Z, Liu Z, Ying J, Wang X, Su J, Wang X, Wu N. DrABC: deep learning accurately predicts germline pathogenic mutation status in breast cancer patients based on phenotype data. Genome Med 2022; 14:21. [PMID: 35209950 PMCID: PMC8876403 DOI: 10.1186/s13073-022-01027-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 02/10/2022] [Indexed: 11/10/2022] Open
Abstract
Background Identifying breast cancer patients with DNA repair pathway-related germline pathogenic variants (GPVs) is important for effectively employing systemic treatment strategies and risk-reducing interventions. However, current criteria and risk prediction models for prioritizing genetic testing among breast cancer patients do not meet the demands of clinical practice due to insufficient accuracy. Methods The study population comprised 3041 breast cancer patients enrolled from seven hospitals between October 2017 and 11 August 2019, who underwent germline genetic testing of 50 cancer predisposition genes (CPGs). Associations among GPVs in different CPGs and endophenotypes were evaluated using a case-control analysis. A phenotype-based GPV risk prediction model named DNA-repair Associated Breast Cancer (DrABC) was developed based on hierarchical neural network architecture and validated in an independent multicenter cohort. The predictive performance of DrABC was compared with currently used models including BRCAPRO, BOADICEA, Myriad, PENN II, and the NCCN criteria. Results In total, 332 (11.3%) patients harbored GPVs in CPGs, including 134 (4.6%) in BRCA2, 131 (4.5%) in BRCA1, 33 (1.1%) in PALB2, and 37 (1.3%) in other CPGs. GPVs in CPGs were associated with distinct endophenotypes including the age at diagnosis, cancer history, family cancer history, and pathological characteristics. We developed a DrABC model to predict the risk of GPV carrier status in BRCA1/2 and other important CPGs. In predicting GPVs in BRCA1/2, the performance of DrABC (AUC = 0.79 [95% CI, 0.74–0.85], sensitivity = 82.1%, specificity = 63.1% in the independent validation cohort) was better than that of previous models (AUC range = 0.57–0.70). In predicting GPVs in any CPG, DrABC (AUC = 0.74 [95% CI, 0.69–0.79], sensitivity = 83.8%, specificity = 51.3% in the independent validation cohort) was also superior to previous models in their current versions (AUC range = 0.55–0.65). After training these previous models with the Chinese-specific dataset, DrABC still outperformed all other methods except for BOADICEA, which was the only previous model with the inclusion of pathological features. The DrABC model also showed higher sensitivity and specificity than the NCCN criteria in the multi-center validation cohort (83.8% and 51.3% vs. 78.8% and 31.2%, respectively, in predicting GPVs in any CPG). The DrABC model implementation is available online at http://gifts.bio-data.cn/. Conclusions By considering the distinct endophenotypes associated with different CPGs in breast cancer patients, a phenotype-driven prediction model based on hierarchical neural network architecture was created for identification of hereditary breast cancer. The model achieved superior performance in identifying GPV carriers among Chinese breast cancer patients. Supplementary Information The online version contains supplementary material available at 10.1186/s13073-022-01027-9.
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Affiliation(s)
- Jiaqi Liu
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.,Institute of Biomedical Big Data, Wenzhou Medical University, Wenzhou, 325027, China
| | - Hengqiang Zhao
- Department of Orthopedic Surgery, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, China.,Beijing Key Laboratory for Genetic Research of Skeletal Deformity, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Yu Zheng
- Fintech Innovation Center, Southwestern University of Finance and Economics, Chengdu, 611130, China
| | - Lin Dong
- Department of Pathology, National Cancer Center /National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Sen Zhao
- Department of Orthopedic Surgery, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, China.,Beijing Key Laboratory for Genetic Research of Skeletal Deformity, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Yukuan Huang
- Institute of Biomedical Big Data, Wenzhou Medical University, Wenzhou, 325027, China.,School of Biomedical Engineering, School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, 325027, China
| | - Shengkai Huang
- Department of Laboratory Medicine, National Cancer Center /National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Tianyi Qian
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Jiali Zou
- Department of Breast Surgery, Guiyang Maternal and Child Healthcare Hospital, Guiyang, 550001, China
| | - Shu Liu
- Department of Breast Surgery, the Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, China
| | - Jun Li
- Department of Molecular Pathology, the Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, 450000, China
| | - Zihui Yan
- Department of Orthopedic Surgery, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, China.,Beijing Key Laboratory for Genetic Research of Skeletal Deformity, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Yalun Li
- Department of Breast Surgery, the Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, 264000, China
| | - Shuo Zhang
- Department of Breast Surgery, the Fourth Hospital of Hebei Medical University, Shijiazhuang, 050019, Hebei, China
| | - Xin Huang
- Department of Breast Surgery, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Wenyan Wang
- Department of Breast Surgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - Yiqun Li
- Department of Oncology, National Cancer Center /National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Jie Wang
- Department of Ultrasound, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Yue Ming
- PET-CT Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Xiaoxin Li
- Medical Research Center, Beijing Key Laboratory for Genetic Research of Skeletal Deformity & Key Laboratory of Big Data for Spinal Deformities, All at Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Zeyu Xing
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Ling Qin
- Department of Breast Surgical Oncology, Cancer Hospital of HuanXing, Beijing, 100021, China
| | - Zhengye Zhao
- Department of Orthopedic Surgery, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, China.,Beijing Key Laboratory for Genetic Research of Skeletal Deformity, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Ziqi Jia
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Jiaxin Li
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Gang Liu
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Menglu Zhang
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Kexin Feng
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Jiang Wu
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Jianguo Zhang
- Department of Orthopedic Surgery, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, China.,Key Laboratory of Big Data for Spinal Deformities, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, China.,State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Yongxin Yang
- Machine Intelligence Group, University of Edinburgh, Edinburgh, EH8 9YL, UK
| | - Zhihong Wu
- Beijing Key Laboratory for Genetic Research of Skeletal Deformity, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, China.,Medical Research Center, Beijing Key Laboratory for Genetic Research of Skeletal Deformity & Key Laboratory of Big Data for Spinal Deformities, All at Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, China.,Key Laboratory of Big Data for Spinal Deformities, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, China.,State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Zhihua Liu
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Jianming Ying
- Department of Pathology, National Cancer Center /National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Xin Wang
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Jianzhong Su
- Institute of Biomedical Big Data, Wenzhou Medical University, Wenzhou, 325027, China. .,School of Biomedical Engineering, School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, 325027, China. .,Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, 325011, China.
| | - Xiang Wang
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
| | - Nan Wu
- Department of Orthopedic Surgery, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, China. .,Beijing Key Laboratory for Genetic Research of Skeletal Deformity, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, China. .,Key Laboratory of Big Data for Spinal Deformities, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, China. .,State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, China.
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14
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Saghatchian M, Abehsera M, Yamgnane A, Geyl C, Gauthier E, Hélin V, Bazire M, Villoing-Gaudé L, Reyes C, Gentien D, Golmard L, Stoppa-Lyonnet D. Feasibility of personalized screening and prevention recommendations in the general population through breast cancer risk assessment: results from a dedicated risk clinic. Breast Cancer Res Treat 2022; 192:375-383. [PMID: 34994879 PMCID: PMC8739506 DOI: 10.1007/s10549-021-06445-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 11/08/2021] [Indexed: 11/02/2022]
Abstract
PURPOSE A personalized approach to prevention and early detection based on known risk factors should contribute to early diagnosis and treatment of breast cancer. We initiated a risk assessment clinic for all women wishing to undergo an individual breast cancer risk assessment. METHODS Women underwent a complete breast cancer assessment including a questionnaire, mammogram with evaluation of breast density, collection of saliva sample, consultation with a radiologist, and a breast cancer specialist. Women aged 40 or older, with 0 or 1 first-degree relative with breast cancer diagnosed after the age of 40 were eligible for risk assessment using MammoRisk, a machine learning-based tool that provides an individual 5-year estimated risk of developing breast cancer based on the patient's clinical data and breast density, with or without polygenic risk scores (PRSs). DNA was extracted from saliva samples for genotyping of 76 single-nucleotide polymorphisms. The individual risk was communicated to the patient, with individualized screening and prevention recommendations. RESULTS A total of 290 women underwent breast cancer assessment, among which 196 women (68%) were eligible for risk assessment using MammoRisk (median age 52, range 40-72). When PRS was added to MammoRisk, 40% (n = 78) of patients were assigned a different risk category, with 28% (n = 55) of patients changing from intermediate to moderate or high risk. CONCLUSION Individual risk assessment is feasible in the general population. Screening recommendations could be given based on individual risk. The use of PRS changed the risk score and screening recommendations in 40% of women.
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Affiliation(s)
- Mahasti Saghatchian
- American Hospital of Paris, Neuilly-sur-Seine, France. .,Paris-Descartes University, Paris, France.
| | - Marc Abehsera
- American Hospital of Paris, Neuilly-sur-Seine, France
| | | | - Caroline Geyl
- American Hospital of Paris, Neuilly-sur-Seine, France
| | | | | | | | | | | | | | - Lisa Golmard
- INSERM U830 D.R.U.M. Team, Institut Curie Hospital, Paris-University, Paris, France
| | - Dominique Stoppa-Lyonnet
- Institut Curie, Paris, France.,INSERM U830 D.R.U.M. Team, Institut Curie Hospital, Paris-University, Paris, France
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15
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Unselected Women's Experiences of Receiving Genetic Research Results for Hereditary Breast and Ovarian Cancer: A Qualitative Study. Genet Test Mol Biomarkers 2021; 25:741-748. [DOI: 10.1089/gtmb.2021.0115] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
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16
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Dick J, Aue V, Wesselmann S, Brédart A, Dolbeault S, Devilee P, Stoppa-Lyonnet D, Schmutzler RK, Rhiem K. Survey on Physicians' Knowledge and Training Needs in Genetic Counseling in Germany. Breast Care (Basel) 2021; 16:389-395. [PMID: 34602945 DOI: 10.1159/000511136] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Accepted: 08/25/2020] [Indexed: 01/25/2023] Open
Abstract
Background In recent years, germline testing of women with a risk of developing breast and ovarian cancer has increased rapidly. This is due to lower costs for new high-throughput sequencing technologies and the manifold preventive and therapeutic options for germline mutation carriers. The growing demand for genetic counseling meets a shortfall of counselors and illustrates the need to involve the treating clinicians in the genetic testing process. This survey was undertaken to assess their state of knowledge and training needs in the field of genetic counseling and testing. Methods A cross-sectional survey within the European Bridges Study (Breast Cancer Risk after Diagnostic Gene Sequencing) was conducted among physician members (n = 111) of the German Cancer Society who were primarily gynecologists. It was designed to examine their experience in genetic counseling and testing. Results Overall, the study revealed a need for training in risk communication and clinical recommendations for persons at risk. One-third of respondents communicated only relative disease risks (31.5%) instead of absolute disease risks in manageable time spans. Moreover, almost one-third of the respondents (31.2%) communicated bilateral and contralateral risk-reducing mastectomy as an option for healthy women and unilateral-diseased breast cancer patients without mutations in high-risk genes (e.g. BRCA1 or BRCA2). Most respondents expressed training needs in the field of risk assessment models, the clinical interpretation of genetic test results, and the decision-making process. Conclusion The survey demonstrates a gap of genetic and risk literacy in a relevant proportion of physicians and the need for appropriate training concepts.
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Affiliation(s)
- Julia Dick
- Center for Hereditary Breast and Ovarian Cancer and Center for Integrated Oncology (CIO), Medical Faculty, University Hospital Cologne, Cologne, Germany
| | - Viktoria Aue
- Center for Hereditary Breast and Ovarian Cancer and Center for Integrated Oncology (CIO), Medical Faculty, University Hospital Cologne, Cologne, Germany
| | | | - Anne Brédart
- Supportive Care Department, Psycho-Oncology Unit, Institut Curie, Paris, France.,University Paris Descartes, Boulogne-Billancourt, France
| | - Sylvie Dolbeault
- Supportive Care Department, Psycho-Oncology Unit, Institut Curie, Paris, France.,Centre de Recherche en Épidémiologie et Santé des Populations (CESP), University Paris-Sud, UVSQ, INSERM, University Paris-Saclay, Villejuif Cedex, France
| | - Peter Devilee
- Departments of Human Genetics and Pathology, Leiden University Medical Centre, Leiden, The Netherlands
| | | | - Rita K Schmutzler
- Center for Hereditary Breast and Ovarian Cancer and Center for Integrated Oncology (CIO), Medical Faculty, University Hospital Cologne, Cologne, Germany
| | - Kerstin Rhiem
- Center for Hereditary Breast and Ovarian Cancer and Center for Integrated Oncology (CIO), Medical Faculty, University Hospital Cologne, Cologne, Germany
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17
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Macdonald C, Chamberlain JA, Mazza D, Milne RL, Phillips KA. Underutilisation of breast cancer prevention medication in Australia. Breast 2021; 60:35-37. [PMID: 34455228 PMCID: PMC8399345 DOI: 10.1016/j.breast.2021.08.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 08/09/2021] [Accepted: 08/19/2021] [Indexed: 11/17/2022] Open
Abstract
Increased implementation of proven prevention strategies is required to combat rising breast cancer incidence. We assessed use of risk reducing medication (RRMed) by Australian women at elevated breast cancer risk. Only 2.4% had ever used RRMed. Higher breast cancer risk was statistically significantly associated with use of RRMed (OR 1.82, 95%CI: 1.08–3.07, p = 0.02 for ≥30% lifetime risk compared with 16%–29% lifetime risk), but parity, education level and family history of breast cancer were not. Breast cancer prevention medications are underutilised. Efforts are needed to incorporate breast cancer risk assessment and risk management discussions into routine health assessments for women. Risk-reducing medication is infrequently used by Australian women at increased risk of breast cancer. Higher breast cancer risk is associated with greater uptake of risk reducing medication, but not with adherence. Routine breast cancer risk assessment may increase risk reducing medication use.
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Affiliation(s)
- Courtney Macdonald
- Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia
| | | | - Danielle Mazza
- Department of General Practice, Monash University, Melbourne, Australia
| | - Roger L Milne
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Melbourne, Australia
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- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia; The Research Department, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Kelly-Anne Phillips
- Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
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18
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Hassani H, Machado JAT, Avazzadeh Z, Safari E, Mehrabi S. Optimal solution of the fractional order breast cancer competition model. Sci Rep 2021; 11:15622. [PMID: 34341390 PMCID: PMC8329307 DOI: 10.1038/s41598-021-94875-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 07/09/2021] [Indexed: 12/21/2022] Open
Abstract
In this article, a fractional order breast cancer competition model (F-BCCM) under the Caputo fractional derivative is analyzed. A new set of basis functions, namely the generalized shifted Legendre polynomials, is proposed to deal with the solutions of F-BCCM. The F-BCCM describes the dynamics involving a variety of cancer factors, such as the stem, tumor and healthy cells, as well as the effects of excess estrogen and the body's natural immune response on the cell populations. After combining the operational matrices with the Lagrange multipliers technique we obtain an optimization method for solving the F-BCCM whose convergence is investigated. Several examples show that a few number of basis functions lead to the satisfactory results. In fact, numerical experiments not only confirm the accuracy but also the practicability and computational efficiency of the devised technique.
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Affiliation(s)
- H Hassani
- Department of Mathematics, Anand International College of Engineering, Jaipur, 302012, India
| | - J A Tenreiro Machado
- Polytechnic of Porto, Dept. of Electrical Engineering, Institute of Engineering, R. Dr. António Bernardino de Almeida, Porto, 431 4249-015, Portugal
| | - Z Avazzadeh
- Department of Applied Mathematics, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, Jiangsu, China.
| | - E Safari
- Department of Immunology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - S Mehrabi
- Department of Internal Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
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19
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Simonetto C, Wollschläger D, Kundrát P, Ulanowski A, Becker J, Castelletti N, Güthlin D, Shemiakina E, Eidemüller M. Estimating long-term health risks after breast cancer radiotherapy: merging evidence from low and high doses. RADIATION AND ENVIRONMENTAL BIOPHYSICS 2021; 60:459-474. [PMID: 34275005 PMCID: PMC8310522 DOI: 10.1007/s00411-021-00924-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 07/05/2021] [Indexed: 05/03/2023]
Abstract
In breast cancer radiotherapy, substantial radiation exposure of organs other than the treated breast cannot be avoided, potentially inducing second primary cancer or heart disease. While distant organs and large parts of nearby ones receive doses in the mGy-Gy range, small parts of the heart, lung and bone marrow often receive doses as high as 50 Gy. Contemporary treatment planning allows for considerable flexibility in the distribution of this exposure. To optimise treatment with regards to long-term health risks, evidence-based risk estimates are required for the entire broad range of exposures. Here, we thus propose an approach that combines data from medical and epidemiological studies with different exposure conditions. Approximating cancer induction as a local process, we estimate organ cancer risks by integrating organ-specific dose-response relationships over the organ dose distributions. For highly exposed organ parts, specific high-dose risk models based on studies with medical exposure are applied. For organs or their parts receiving relatively low doses, established dose-response models based on radiation-epidemiological data are used. Joining the models in the intermediate dose range leads to a combined, in general non-linear, dose response supported by data over the whole relevant dose range. For heart diseases, a linear model consistent with high- and low-dose studies is presented. The resulting estimates of long-term health risks are largely compatible with rate ratios observed in randomised breast cancer radiotherapy trials. The risk models have been implemented in a software tool PASSOS that estimates long-term risks for individual breast cancer patients.
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Affiliation(s)
- Cristoforo Simonetto
- Institute of Radiation Medicine, Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | - Daniel Wollschläger
- Institute of Medical Biostatistics, Epidemiology and Informatics, University Medical Center Mainz, Obere Zahlbacher Str. 69, 55131, Mainz, Germany
| | - Pavel Kundrát
- Institute of Radiation Medicine, Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Department of Radiation Dosimetry, Nuclear Physics Institute of the Czech Academy of Sciences, Na Truhlářce 39/64, 180 00, Prague 8, Czech Republic
| | - Alexander Ulanowski
- Institute of Radiation Medicine, Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- IAEA Environment Laboratories, International Atomic Energy Agency, 2444, Seibersdorf, Austria
| | - Janine Becker
- Institute of Radiation Medicine, Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | - Noemi Castelletti
- Institute of Radiation Medicine, Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, 80802, Munich, Germany
| | - Denise Güthlin
- Institute of Radiation Medicine, Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Department of Radiation Protection and Health, Federal Office for Radiation Protection, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | - Elena Shemiakina
- Institute of Radiation Medicine, Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | - Markus Eidemüller
- Institute of Radiation Medicine, Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany.
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20
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Knoppers BM, Bernier A, Granados Moreno P, Pashayan N. Of Screening, Stratification, and Scores. J Pers Med 2021; 11:736. [PMID: 34442379 PMCID: PMC8398020 DOI: 10.3390/jpm11080736] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Accepted: 07/24/2021] [Indexed: 12/16/2022] Open
Abstract
Technological innovations including risk-stratification algorithms and large databases of longitudinal population health data and genetic data are allowing us to develop a deeper understanding how individual behaviors, characteristics, and genetics are related to health risk. The clinical implementation of risk-stratified screening programmes that utilise risk scores to allocate patients into tiers of health risk is foreseeable in the future. Legal and ethical challenges associated with risk-stratified cancer care must, however, be addressed. Obtaining access to the rich health data that are required to perform risk-stratification, ensuring equitable access to risk-stratified care, ensuring that algorithms that perform risk-scoring are representative of human genetic diversity, and determining the appropriate follow-up to be provided to stratification participants to alert them to changes in their risk score are among the principal ethical and legal challenges. Accounting for the great burden that regulatory requirements could impose on access to risk-scoring technologies is another critical consideration.
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Affiliation(s)
- Bartha M. Knoppers
- Centre of Genomics and Policy, Faculty of Medicine, McGill University, 740 Avenue Dr. Penfield, Suite 5200, Montreal, QC H3A 0G1, Canada; (A.B.); (P.G.M.)
| | - Alexander Bernier
- Centre of Genomics and Policy, Faculty of Medicine, McGill University, 740 Avenue Dr. Penfield, Suite 5200, Montreal, QC H3A 0G1, Canada; (A.B.); (P.G.M.)
| | - Palmira Granados Moreno
- Centre of Genomics and Policy, Faculty of Medicine, McGill University, 740 Avenue Dr. Penfield, Suite 5200, Montreal, QC H3A 0G1, Canada; (A.B.); (P.G.M.)
| | - Nora Pashayan
- Department of Applied Health Research, University College London, 1-19 Torrington Place, London WC1E 7HB, UK;
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21
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Kurian AW, Hughes E, Simmons T, Bernhisel R, Probst B, Meek S, Caswell-Jin JL, John EM, Lanchbury JS, Slavin TP, Wagner S, Gutin A, Rohan TE, Shadyab AH, Manson JE, Lane D, Chlebowski RT, Stefanick ML. Performance of the IBIS/Tyrer-Cuzick model of breast cancer risk by race and ethnicity in the Women's Health Initiative. Cancer 2021; 127:3742-3750. [PMID: 34228814 DOI: 10.1002/cncr.33767] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 05/28/2021] [Accepted: 06/05/2021] [Indexed: 12/20/2022]
Abstract
BACKGROUND The IBIS/Tyrer-Cuzick model is used clinically to guide breast cancer screening and prevention, but was developed primarily in non-Hispanic White women. Little is known about its long-term performance in a racially/ethnically diverse population. METHODS The Women's Health Initiative study enrolled postmenopausal women from 1993-1998. Women were included who were aged <80 years at enrollment with no prior breast cancer or mastectomy and with data required for IBIS/Tyrer-Cuzick calculation (weight; height; ages at menarche, first birth, and menopause; menopausal hormone therapy use; and family history of breast or ovarian cancer). Calibration was assessed by the ratio of observed breast cancer cases to the number expected by the IBIS/Tyrer-Cuzick model (O/E; calculated as the sum of cumulative hazards). Differential discrimination was tested for by self-reported race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, Asian or Pacific Islander, and American Indian or Alaskan Native) using Cox regression. Exploratory analyses, including simulation of a protective single-nucleotide polymorphism (SNP), rs140068132 at 6q25, were performed. RESULTS During follow-up (median 18.9 years, maximum 23.4 years), 6783 breast cancer cases occurred among 90,967 women. IBIS/Tyrer-Cuzick was well calibrated overall (O/E ratio = 0.95; 95% CI, 0.93-0.97) and in most racial/ethnic groups, but overestimated risk for Hispanic women (O/E ratio = 0.75; 95% CI, 0.62-0.90). Discrimination did not differ by race/ethnicity. Exploratory simulation of the protective SNP suggested improved IBIS/Tyrer-Cuzick calibration for Hispanic women (O/E ratio = 0.80; 95% CI, 0.66-0.96). CONCLUSIONS The IBIS/Tyrer-Cuzick model is well calibrated for several racial/ethnic groups over 2 decades of follow-up. Studies that incorporate genetic and other risk factors, particularly among Hispanic women, are essential to improve breast cancer-risk prediction.
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Affiliation(s)
- Allison W Kurian
- Department of Medicine, Stanford University School of Medicine, Stanford, California.,Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, California
| | | | | | | | | | | | | | - Esther M John
- Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, California
| | | | | | | | | | - Thomas E Rohan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York
| | - Aladdin H Shadyab
- Department of Family Medicine and Public Health, Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, California
| | - JoAnn E Manson
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Dorothy Lane
- Department of Family, Population and Preventive Medicine, Renaissance School of Medicine, Stony Brook University, Stony Brook, New York
| | - Rowan T Chlebowski
- Department of Medicine, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, California
| | - Marcia L Stefanick
- Department of Medicine, Stanford University School of Medicine, Stanford, California
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22
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Jahan N, Jones C, Rahman RL. Endocrine prevention of breast cancer. Mol Cell Endocrinol 2021; 530:111284. [PMID: 33882282 DOI: 10.1016/j.mce.2021.111284] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 04/04/2021] [Accepted: 04/12/2021] [Indexed: 01/01/2023]
Abstract
Breast cancer (BC) is the most common non-cutaneous malignancy among women worldwide and is a significant cause of morbidity, mortality, and national health care expenditure. Unfortunately, with few exceptions like alcohol consumption, obesity, and physical activity, most BC risk factors are unmodifiable. Antiestrogen endocrine therapy, commonly known as BC chemoprevention, is an effective method of BC prevention. In multiple randomized trials, two selective estrogen receptor modulators - tamoxifen and raloxifene, and two aromatase inhibitors - exemestane and anastrozole have reduced BC incidence by 50%-65% in high-risk women. An estimated 15% of the US women between 35 and 79 years of age may qualify as high risk for BC, yet a small percentage of these women will ever have a formal BC risk assessment or a discussion of endocrine prevention options. The etiology of underutilization of endocrine prevention of BC is multifactorial - infrequent use of BC risk assessment tools in the primary care settings, insufficient knowledge of BC risk assessment tools and antiestrogen agents among primary care providers, concerns of side effects, inadequate time for counseling during primary care visit, and lack of predictive biomarkers may play significant roles. Many small studies incorporating risk assessment tools and decision-making aids showed minimal success in enhancing endocrine prevention. One critical factor for underutilization of endocrine prevention is low uptake of endocrine prevention by high-risk women even when appropriately recommended. Furthermore, adherence to BC endocrine prevention is unsatisfactorily low. Despite the current infrequent usage, endocrine prevention has the potential to reduce the public health burden of BC significantly. Innovative approaches like finding new agents, alternative dosing and schedule of currently available agents, transdermal medication delivery, increased public and professional awareness, and policymakers' commitments may bring the desired changes.
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Affiliation(s)
- Nusrat Jahan
- Division of Hematology-Oncology, Department of Internal Medicine, Texas Tech University Health Sciences Center, 3601 4th St, Lubbock, Tx, 79430, USA.
| | - Catherine Jones
- Division of Hematology-Oncology, Department of Internal Medicine, Texas Tech University Health Sciences Center, 3601 4th St, Lubbock, Tx, 79430, USA
| | - Rakhshanda Layeequr Rahman
- Department of Surgery, Texas Tech University Health Sciences Center, 3601 4th St, Lubbock, Tx, 79430, USA
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23
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Moskowitz CS, Ronckers CM, Chou JF, Smith SA, Friedman DN, Barnea D, Kok JL, de Vries S, Wolden SL, Henderson TO, van der Pal HJH, Kremer LCM, Neglia JP, Turcotte LM, Howell RM, Arnold MA, Schaapveld M, Aleman B, Janus C, Versluys B, Leisenring W, Sklar CA, Begg CB, Pike MC, Armstrong GT, Robison LL, van Leeuwen FE, Oeffinger KC. Development and Validation of a Breast Cancer Risk Prediction Model for Childhood Cancer Survivors Treated With Chest Radiation: A Report From the Childhood Cancer Survivor Study and the Dutch Hodgkin Late Effects and LATER Cohorts. J Clin Oncol 2021; 39:3012-3021. [PMID: 34048292 DOI: 10.1200/jco.20.02244] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
PURPOSE Women treated with chest radiation for childhood cancer have one of the highest risks of breast cancer. Models producing personalized breast cancer risk estimates applicable to this population do not exist. We sought to develop and validate a breast cancer risk prediction model for childhood cancer survivors treated with chest radiation incorporating treatment-related factors, family history, and reproductive factors. METHODS Analyses were based on multinational cohorts of female 5-year survivors of cancer diagnosed younger than age 21 years and treated with chest radiation. Model derivation was based on 1,120 participants in the Childhood Cancer Survivor Study diagnosed between 1970 and 1986, with median attained age 42 years (range 20-64) and 242 with breast cancer. Model validation included 1,027 participants from three cohorts, with median age 32 years (range 20-66) and 105 with breast cancer. RESULTS The model included current age, chest radiation field, whether chest radiation was delivered within 1 year of menarche, anthracycline exposure, age at menopause, and history of a first-degree relative with breast cancer. Ten-year risk estimates ranged from 2% to 23% for 30-year-old women (area under the curve, 0.63; 95% CI, 0.50 to 0.73) and from 5% to 34% for 40-year-old women (area under the curve, 0.67; 95% CI, 0.54 to 0.84). The highest risks were among premenopausal women older than age 40 years treated with mantle field radiation within a year of menarche who had a first-degree relative with breast cancer. It showed good calibration with an expected-to-observed ratio of the number of breast cancers of 0.92 (95% CI, 0.74 to 1.16). CONCLUSION Breast cancer risk varies among childhood cancer survivors treated with chest radiation. Accurate risk prediction may aid in refining surveillance, counseling, and preventive strategies in this population.
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Affiliation(s)
| | - Cécile M Ronckers
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.,Brandenburg Medical School Theodor Fontane, Neuruppin, Germany
| | - Joanne F Chou
- Memorial Sloan Kettering Cancer Center, New York, NY
| | - Susan A Smith
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Dana Barnea
- Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Judith L Kok
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
| | | | | | - Tara O Henderson
- University of Chicago Medicine Comer Children's Hospital, Chicago, IL
| | | | | | - Joseph P Neglia
- University of Minnesota Masonic Cancer Center, Minneapolis, MN
| | | | | | | | | | - Berthe Aleman
- Netherlands Cancer Institute, Amsterdam, the Netherlands
| | | | - Birgitta Versluys
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
| | | | | | - Colin B Begg
- Memorial Sloan Kettering Cancer Center, New York, NY
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24
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Beard C, Monohan K, Cicciarelli L, James PA. Mainstream genetic testing for breast cancer patients: early experiences from the Parkville Familial Cancer Centre. Eur J Hum Genet 2021; 29:872-880. [PMID: 33723355 PMCID: PMC8111023 DOI: 10.1038/s41431-021-00848-3] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 02/15/2021] [Accepted: 02/19/2021] [Indexed: 01/31/2023] Open
Abstract
The demand for genetic testing of hereditary breast cancer genes such as BRCA1 and BRCA2 has continued to increase with the lowering costs of testing, raised awareness in the general public, and implications for breast cancer treatment when a patient is identified as having a germline pathogenic variant. Historically within Australia, patients affected by high genetic risk breast cancers have been referred to a familial cancer centre (FCC) for assessment and testing, resulting in wait times for an appointment for pre- and post-test genetic counselling and an increased demand on the public-funded FCC. To improve patient access and pace of genetic testing, as well as refocus FCC resources, a mainstream clinical genetic testing program was rolled out in September 2017 through the Parkville FCC (PFCC) in Australia at 10 hospital sites. This program enables specialist doctors of eligible patients affected by breast cancer to arrange genetic testing directly at an oncology/surgical appointment and follow up the results as part of the patients' routine clinical care. In this model, the specialist doctor is responsible for any treatment implications of the genetic test result, and the PFCC is responsible for result interpretation, future cancer risk, family cascade testing and segregation testing where warranted. To date the program has had successful uptake, a notable pathogenic variant detection rate, reduced the burden on the PFCC enabling a reallocation of resources and has streamlined the process of genetic testing for eligible patients. Investigation into the patient and clinician experiences of the mainstream program is required.
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Affiliation(s)
- Catherine Beard
- Parkville Familial Cancer Centre, Peter MacCallum Cancer Centre and The Royal Melbourne Hospital, Parkville, VIC, Australia.
- Department of Medicine, University of Melbourne, The Royal Melbourne Hospital, Parkville, VIC, Australia.
| | - Katrina Monohan
- Parkville Familial Cancer Centre, Peter MacCallum Cancer Centre and The Royal Melbourne Hospital, Parkville, VIC, Australia
| | - Linda Cicciarelli
- Parkville Familial Cancer Centre, Peter MacCallum Cancer Centre and The Royal Melbourne Hospital, Parkville, VIC, Australia
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
| | - Paul A James
- Parkville Familial Cancer Centre, Peter MacCallum Cancer Centre and The Royal Melbourne Hospital, Parkville, VIC, Australia
- Department of Medicine, University of Melbourne, The Royal Melbourne Hospital, Parkville, VIC, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia
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25
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Tone AA, McCuaig JM, Ricker N, Boghosian T, Romagnuolo T, Stickle N, Virtanen C, Zhang T, Kim RH, Ferguson SE, May T, Laframboise S, Armel S, Demsky R, Volenik A, Stuart-McEwan T, Shaw P, Oza A, Kamel-Reid S, Stockley T, Bernardini MQ. The Prevent Ovarian Cancer Program (POCP): Identification of women at risk for ovarian cancer using complementary recruitment approaches. Gynecol Oncol 2021; 162:97-106. [PMID: 33858678 DOI: 10.1016/j.ygyno.2021.04.011] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Accepted: 04/09/2021] [Indexed: 11/17/2022]
Abstract
BACKGROUND Up to 20% of high-grade serous ovarian carcinomas (HGSOC) are hereditary; however, historical uptake of genetic testing is low. We used a unique combination of approaches to identify women in Ontario, Canada, with a first-degree relative (FDR) who died from HGSOC without prior genetic testing, and offer them multi-gene panel testing. METHODS From May 2015-Sept 2019, genetic counseling and testing was provided to eligible participants. Two recruitment strategies were employed, including self-identification in response to an outreach campaign and direct targeting of FDRs of deceased HGSOC patients treated at our institution. The rate of pathogenic variants (PV) in established/potential ovarian cancer risk genes and the benefits/challenges of each approach were assessed. RESULTS A total of 564 women enrolled in response to our outreach campaign (n = 473) or direct recruitment (n = 91). Mean age at consent was 52 years and 96% did not meet provincial testing criteria. Genetic results were provided to 528 individuals from 458 families. The rate of PVs in ovarian cancer risk genes was highest when FDRs were diagnosed with HGSOC <60 years (9.4% vs. 3.9% ≥ 60y, p = 0.0160). Participants in the outreach vs. direct recruitment cohort had a similar rate of PVs; however, uptake of genetic testing (97% vs. 89%; p = 0.0036) and study completion (95% vs. 87%; p = 0.0062) rates were higher in the former. Eleven participants with pathogenic variants have completed risk-reducing gynecologic surgery, with one stage I HGSOC and two breast cancers identified. CONCLUSION Overall PV rates in this large cohort were lower than expected; however, we provide evidence that genetic testing criteria in Ontario should include individuals with a deceased FDR diagnosed with HGSOC <60 years of age.
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Affiliation(s)
- Alicia A Tone
- Gynecologic Oncology, The University Health Network, Toronto, Canada; Ovarian Cancer Canada, Toronto, Canada
| | - Jeanna M McCuaig
- Gynecologic Oncology, The University Health Network, Toronto, Canada; Familial Cancer Clinic, The University Health Network, Toronto, Canada; Department of Molecular Genetics, University of Toronto, Toronto, Canada
| | - Nicole Ricker
- Gynecologic Oncology, The University Health Network, Toronto, Canada
| | - Talin Boghosian
- Gynecologic Oncology, The University Health Network, Toronto, Canada
| | - Tina Romagnuolo
- Gynecologic Oncology, The University Health Network, Toronto, Canada
| | - Natalie Stickle
- Bioinformatics and HPC Core, The University Health Network, Toronto, Canada
| | - Carl Virtanen
- Bioinformatics and HPC Core, The University Health Network, Toronto, Canada
| | - Tong Zhang
- Advanced Molecular Diagnostics Laboratory, The University Health Network, Toronto, Canada
| | - Raymond H Kim
- Familial Cancer Clinic, The University Health Network, Toronto, Canada; Department of Medicine, University of Toronto, Toronto, Canada; Medical Oncology, The University Health Network, Toronto, Canada
| | - Sarah E Ferguson
- Gynecologic Oncology, The University Health Network, Toronto, Canada; Department of Obstetrics and Gynecology, University of Toronto, Toronto, Canada
| | - Taymaa May
- Gynecologic Oncology, The University Health Network, Toronto, Canada
| | | | - Susan Armel
- Familial Cancer Clinic, The University Health Network, Toronto, Canada; Department of Molecular Genetics, University of Toronto, Toronto, Canada
| | - Rochelle Demsky
- Familial Cancer Clinic, The University Health Network, Toronto, Canada; Department of Molecular Genetics, University of Toronto, Toronto, Canada
| | - Alexandra Volenik
- Familial Cancer Clinic, The University Health Network, Toronto, Canada; Department of Molecular Genetics, University of Toronto, Toronto, Canada
| | | | - Patricia Shaw
- Gynecologic Pathology, The University Health Network, Toronto, Canada
| | - Amit Oza
- Medical Oncology, The University Health Network, Toronto, Canada
| | - Suzanne Kamel-Reid
- Advanced Molecular Diagnostics Laboratory, The University Health Network, Toronto, Canada; Clinical Laboratory Genetics, The University Health Network, Toronto, Canada
| | - Tracy Stockley
- Advanced Molecular Diagnostics Laboratory, The University Health Network, Toronto, Canada; Clinical Laboratory Genetics, The University Health Network, Toronto, Canada
| | - Marcus Q Bernardini
- Gynecologic Oncology, The University Health Network, Toronto, Canada; Department of Obstetrics and Gynecology, University of Toronto, Toronto, Canada.
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26
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Kim G, Bahl M. Assessing Risk of Breast Cancer: A Review of Risk Prediction Models. JOURNAL OF BREAST IMAGING 2021; 3:144-155. [PMID: 33778488 DOI: 10.1093/jbi/wbab001] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Indexed: 12/17/2022]
Abstract
Accurate and individualized breast cancer risk assessment can be used to guide personalized screening and prevention recommendations. Existing risk prediction models use genetic and nongenetic risk factors to provide an estimate of a woman's breast cancer risk and/or the likelihood that she has a BRCA1 or BRCA2 mutation. Each model is best suited for specific clinical scenarios and may have limited applicability in certain types of patients. For example, the Breast Cancer Risk Assessment Tool, which identifies women who would benefit from chemoprevention, is readily accessible and user-friendly but cannot be used in women under 35 years of age or those with prior breast cancer or lobular carcinoma in situ. Emerging research on deep learning-based artificial intelligence (AI) models suggests that mammographic images contain risk indicators that could be used to strengthen existing risk prediction models. This article reviews breast cancer risk factors, describes the appropriate use, strengths, and limitations of each risk prediction model, and discusses the emerging role of AI for risk assessment.
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Affiliation(s)
- Geunwon Kim
- Beth Israel Deaconess Medical Center, Department of Radiology, Boston, MA, USA
| | - Manisha Bahl
- Massachusetts General Hospital, Department of Radiology, Boston, MA, USA
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27
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Aleshin-Guendel S, Lange J, Goodman P, Weiss NS, Etzioni R. A Latent Disease Model to Reduce Detection Bias in Cancer Risk Prediction Studies. Eval Health Prof 2021; 44:42-49. [PMID: 33506704 PMCID: PMC8279086 DOI: 10.1177/0163278720984203] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
In studies of cancer risk, detection bias arises when risk factors are associated with screening patterns, affecting the likelihood and timing of diagnosis. To eliminate detection bias in a screened cohort, we propose modeling the latent onset of cancer and estimating the association between risk factors and onset rather than diagnosis. We apply this framework to estimate the increase in prostate cancer risk associated with black race and family history using data from the SELECT prostate cancer prevention trial, in which men were screened and biopsied according to community practices. A positive family history was associated with a hazard ratio (HR) of prostate cancer onset of 1.8, lower than the corresponding HR of prostate cancer diagnosis (HR = 2.2). This result comports with a finding that men in SELECT with a family history were more likely to be biopsied following a positive PSA test than men with no family history. For black race, the HRs for onset and diagnosis were similar, consistent with similar patterns of screening and biopsy by race. If individual screening and diagnosis histories are available, latent disease modeling can be used to decouple risk of disease from risk of disease diagnosis and reduce detection bias.
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Affiliation(s)
| | - Jane Lange
- Fred Hutchinson Cancer Research Center, Seattle, WA
| | | | - Noel S Weiss
- Fred Hutchinson Cancer Research Center, Seattle, WA
- University of Washington, Department of Epidemiology
| | - Ruth Etzioni
- University of Washington, Department of Biostatistics, Seattle, WA
- Fred Hutchinson Cancer Research Center, Seattle, WA
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28
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Carver T, Hartley S, Lee A, Cunningham AP, Archer S, Babb de Villiers C, Roberts J, Ruston R, Walter FM, Tischkowitz M, Easton DF, Antoniou AC. CanRisk Tool-A Web Interface for the Prediction of Breast and Ovarian Cancer Risk and the Likelihood of Carrying Genetic Pathogenic Variants. Cancer Epidemiol Biomarkers Prev 2021; 30:469-473. [PMID: 33335023 PMCID: PMC7611188 DOI: 10.1158/1055-9965.epi-20-1319] [Citation(s) in RCA: 108] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 10/08/2020] [Accepted: 12/14/2020] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND The CanRisk Tool (https://canrisk.org) is the next-generation web interface for the latest version of the BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) state-of-the-art risk model and a forthcoming ovarian cancer risk model. METHODS The tool captures information on family history, rare pathogenic variants in cancer susceptibility genes, polygenic risk scores, lifestyle/hormonal/clinical features, and imaging risk factors to predict breast and ovarian cancer risks and estimate the probabilities of carrying pathogenic variants in certain genes. It was implemented using modern web frameworks, technologies, and web services to make it extensible and increase accessibility to researchers and third-party applications. The design of the graphical user interface was informed by feedback from health care professionals and a formal evaluation. RESULTS This freely accessible tool was designed to be user friendly for clinicians and to boost acceptability in clinical settings. The tool incorporates a novel graphical pedigree builder to facilitate collection of the family history data required by risk calculations. CONCLUSIONS The CanRisk Tool provides health care professionals and researchers with a user-friendly interface to carry out multifactorial breast and ovarian cancer risk predictions. It is the first freely accessible cancer risk prediction program to carry the CE marking. IMPACT There have been over 3,100 account registrations, and 98,000 breast and ovarian cancer risk calculations have been run within the first 9 months of the CanRisk Tool launch.
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Affiliation(s)
- Tim Carver
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.
| | - Simon Hartley
- Centre for Computational Biology, University of Birmingham, Birmingham, United Kingdom
| | - Andrew Lee
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Alex P Cunningham
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Stephanie Archer
- Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Chantal Babb de Villiers
- Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Jonathan Roberts
- East Anglian Medical Genetics Service, Cambridge Biomedical Campus, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Rod Ruston
- Priory Analysts, Milton Keynes, United Kingdom
| | - Fiona M Walter
- Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- Centre for Cancer Research and Department of General Practice, University of Melbourne, Melbourne, Victoria, Australia
| | - Marc Tischkowitz
- East Anglian Medical Genetics Service, Cambridge Biomedical Campus, Addenbrooke's Hospital, Cambridge, United Kingdom
- Academic Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, United Kingdom
| | - Antonis C Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
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29
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Eidemüller M, Holmberg E, Lundell M, Karlsson P. Evidence for Increased Susceptibility to Breast Cancer From Exposure to Ionizing Radiation Due to a Familial History of Breast Cancer: Results From the Swedish Hemangioma Cohort. Am J Epidemiol 2021; 190:76-84. [PMID: 32735015 PMCID: PMC7784527 DOI: 10.1093/aje/kwaa163] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Revised: 07/09/2020] [Accepted: 07/09/2020] [Indexed: 12/12/2022] Open
Abstract
Women with a history of breast cancer among family members are at increased risk for breast cancer. However, it is unknown whether a familial breast cancer history (FBCH) also increases individual susceptibility to breast cancer from radiation exposure. In this cohort study, 17,200 female Swedish hemangioma patients with 1,079 breast cancer cases diagnosed between 1958 and 2013, exposed to ionizing radiation in infancy, were linked to their first-degree relatives. The association between FBCH and radiation-induced breast cancer risk was assessed. Further, the relevance for breast cancer radiotherapy and mammography screening was evaluated. On average, the radiation-induced excess relative risk and excess absolute risk of breast cancer at age 50 years were 0.51 Gy-1 (95% confidence interval (CI): 0.33, 0.71) and 10.8 cases/10,000 person-years/Gy (95% CI: 7.0, 14.6), respectively. Radiation risk was higher by a factor of 2.7 (95% CI: 1.0, 4.8; P = 0.05) if 1 first-degree relative was affected by breast cancer. For whole-breast standard radiotherapy at age 40 years with a contralateral breast dose of 0.72 Gy, the 20-year radiation-related excess risk of contralateral breast cancer was estimated to increase from 0.6% for women without FBCH to 1.7% for women with FBCH. In a biennial mammography screening program at ages 40-74 years, radiation risk up to age 80 years would increase from 0.11% for women without FBCH to 0.29% for women with FBCH.
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Affiliation(s)
- Markus Eidemüller
- Correspondence to Dr. Markus Eidemüller, Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Radiation Medicine, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany (e-mail: ). † Deceased
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30
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MacInnis RJ, Knight JA, Chung WK, Milne RL, Whittemore AS, Buchsbaum R, Liao Y, Zeinomar N, Dite GS, Southey MC, Goldgar D, Giles GG, Kurian AW, Andrulis IL, John EM, Daly MB, Buys SS, Phillips KA, Hopper JL, Terry MB. Comparing 5-Year and Lifetime Risks of Breast Cancer using the Prospective Family Study Cohort. J Natl Cancer Inst 2020; 113:785-791. [PMID: 33301022 DOI: 10.1093/jnci/djaa178] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 08/06/2020] [Accepted: 10/13/2020] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Clinical guidelines often use predicted lifetime risk from birth to define criteria for making decisions regarding breast cancer screening rather than thresholds based on absolute 5-year risk from current age. METHODS We used the Prospective Family Cohort Study of 14 657 women without breast cancer at baseline in which, during a median follow-up of 10 years, 482 women were diagnosed with invasive breast cancer. We examined the performances of the International Breast Cancer Intervention Study (IBIS) and Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk models when using the alternative thresholds by comparing predictions based on 5-year risk with those based on lifetime risk from birth and remaining lifetime risk. All statistical tests were 2-sided. RESULTS Using IBIS, the areas under the receiver-operating characteristic curves were 0.66 (95% confidence interval = 0.63 to 0.68) and 0.56 (95% confidence interval = 0.54 to 0.59) for 5-year and lifetime risks, respectively (Pdiff < .001). For equivalent sensitivities, the 5-year incidence almost always had higher specificities than lifetime risk from birth. For women aged 20-39 years, 5-year risk performed better than lifetime risk from birth. For women aged 40 years or older, receiver-operating characteristic curves were similar for 5-year and lifetime IBIS risk from birth. Classifications based on remaining lifetime risk were inferior to 5-year risk estimates. Results were similar using BOADICEA. CONCLUSIONS Our analysis shows that risk stratification using clinical models will likely be more accurate when based on predicted 5-year risk compared with risks based on predicted lifetime and remaining lifetime, particularly for women aged 20-39 years.
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Affiliation(s)
- Robert J MacInnis
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.,Centre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, Victoria, Australia
| | - Julia A Knight
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Wendy K Chung
- Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA.,Departments of Pediatrics and Medicine, Columbia University, New York, NY, USA
| | - Roger L Milne
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.,Centre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, Victoria, Australia.,Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Alice S Whittemore
- Department of Health Research and Policy and of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Richard Buchsbaum
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Yuyan Liao
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Nur Zeinomar
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Gillian S Dite
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, Victoria, Australia
| | - Melissa C Southey
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.,Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.,Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Parkville, Victoria, Australia
| | - David Goldgar
- Department of Dermatology and Huntsman Cancer Institute, University of Utah Health, Salt Lake City, UT, USA
| | - Graham G Giles
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.,Centre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, Victoria, Australia.,Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Allison W Kurian
- Department of Medicine and Epidemiology and Population Health, Stanford University, Stanford, CA, USA
| | | | - Irene L Andrulis
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada.,Department of Molecular Genetics and Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Esther M John
- Department of Epidemiology & Population Health and Medicine and Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Mary B Daly
- Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, PA, USA
| | - Saundra S Buys
- Department of Medicine and Huntsman Cancer Institute, University of Utah Health, Salt Lake City, UT, USA
| | - Kelly-Anne Phillips
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, Victoria, Australia.,Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Victoria, Australia.,Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, Victoria, Australia
| | - Mary Beth Terry
- Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA.,Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
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Polygenic risk scores for genetic counseling in psychiatry: Lessons learned from other fields of medicine. Neurosci Biobehav Rev 2020; 121:119-127. [PMID: 33301779 DOI: 10.1016/j.neubiorev.2020.11.021] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 11/17/2020] [Accepted: 11/27/2020] [Indexed: 12/16/2022]
Abstract
Polygenic risk scores (PRS) may aid in the identification of individuals at-risk for psychiatric disorders, treatment optimization, and increase in prognostic accuracy. PRS may also add significant value to genetic counseling. Thus far, integration of PRSs in genetic counseling sessions remains problematic because of uncertainties in risk prediction and other concerns. Here, we review the current utility of PRSs in the context of clinical psychiatry. By comprehensively appraising the literature in other fields of medicine including breast cancer, Alzheimer's Disease, and cardiovascular disease, we outline several lessons learned that could be applied to future studies and may thus benefit the incorporation of PRS in psychiatric genetic counseling. These include integrating PRS with environmental factors (e.g. lifestyle), setting up large-scale studies, and applying reproducible methods allowing for cross-validation between cohorts. We conclude that psychiatry may benefit from experiences in these fields. PRS may in future have a role in genetic counseling in clinical psychiatric practice, by advancing prevention strategies and treatment decision-making, thus promoting quality of life for (potentially) affected individuals.
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Screening Strategy Modification Based on Personalized Breast Cancer Risk Stratification and its Implementation in the National Guidelines - Pilot Study. Zdr Varst 2020; 59:211-218. [PMID: 33133277 PMCID: PMC7583429 DOI: 10.2478/sjph-2020-0027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 08/31/2020] [Indexed: 12/24/2022] Open
Abstract
Background One of the most consistent models for estimating personalized breast cancer (BC) risk is the Tyrer-Cuzick algorithm that is incorporated into the International Breast Cancer Intervention Study (IBIS) software. Our main objective was to provide criteria for the classification of the Slovenian population, which has BC incidence below the European average, into risk groups, and to evaluate the integration of the criteria in Slovenian guidelines. Our main focus was on women age <50 with higher BC risk, since no organized BC screening is available for these women. Methods Slovenian age-specific BC risks were incorporated into IBIS software and threshold values of risk categories were determined. Risk categories were assigned according to the individual’s ten-year risk for women aged 40 and older, and lifetime risk for women between 20 and 39. To test the software, we compared screening strategies with the use vs. no use of IBIS. Results Of the 197 women included in the study IBIS assigned 75.1% to the BC risk group, and the rest to the moderately increased risk. Without IBIS 80 women were offered mammographic and 33 ultrasound screening. In contrast, 28 instead of 80 would have been offered mammographic screening and there would have been no referrals for ultrasound if IBIS had been used. Conclusions The Slovenian IBIS has been developed, tested and suggested for personalized breast cancer risk assessment. The implementation of the software with the consideration of Slovenian risk thresholds enables a more accurate and nationally unified assessment.
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Macdonald C, Saunders CM, Keogh LA, Hunter M, Mazza D, McLachlan SA, Jones SC, Nesci S, Friedlander ML, Hopper JL, Emery JD, Hickey M, Milne RL, Phillips KA. Breast Cancer Chemoprevention: Use and Views of Australian Women and Their Clinicians. Cancer Prev Res (Phila) 2020; 14:131-144. [PMID: 33115784 DOI: 10.1158/1940-6207.capr-20-0369] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 08/27/2020] [Accepted: 10/15/2020] [Indexed: 11/16/2022]
Abstract
Guidelines endorse the use of chemoprevention for breast cancer risk reduction. This study examined the barriers and facilitators to chemoprevention use for Australian women at increased risk of breast cancer, and their clinicians. Surveys, based on the Theoretical Domains Framework, were mailed to 1,113 women at ≥16% lifetime risk of breast cancer who were enrolled in the Kathleen Cuningham Foundation Consortium for Research into Familial Breast Cancer cohort study (kConFab), and their 524 treating clinicians. Seven hundred twenty-five women (65%) and 221 (42%) clinicians responded. Only 10 (1.4%) kConFab women had ever taken chemoprevention. Three hundred seventy-eight (52%) kConFab women, two (3%) breast surgeons, and 51 (35%) family physicians were not aware of chemoprevention. For women, the strongest barriers to chemoprevention were side effects (31%) and inadequate information (23%), which operate in the Theoretical Domains Framework domains of "beliefs about consequences" and "knowledge," respectively. Strongest facilitators related to tamoxifen's long-term efficacy (35%, "knowledge," "beliefs about consequences," and "goals" domains), staying healthy for family (13%, "social role" and "goals" domains), and abnormal breast biopsy (13%, "environmental context" domain). The strongest barrier for family physicians was insufficient knowledge (45%, "knowledge" domain) and for breast surgeons was medication side effects (40%, "beliefs about consequences" domain). The strongest facilitators for both clinician groups related to clear guidelines, strong family history, and better tools to select patients ("environmental context and resources" domain). Clinician knowledge and resources, and beliefs about the side-effect consequences of chemoprevention, are key domains that could be targeted to potentially enhance uptake. PREVENTION RELEVANCE: Despite its efficacy in reducing breast cancer incidence, chemoprevention is underutilised. This survey study of Australian women and their clinicians used behavioural change theory to identify modifiable barriers to chemoprevention uptake, and to suggest interventions such as policy change, educational resources and public campaigns, that may increase awareness and use.See related Spotlight by Vogel, p. 1.
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Affiliation(s)
- Courtney Macdonald
- Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, VIC, Australia
| | | | - Louise A Keogh
- Centre for Health Equity, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia
| | - Morgan Hunter
- Centre for Biostatistics and Clinical Trials, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Danielle Mazza
- Department of General Practice, Monash University, Melbourne, Australia
| | - Sue-Anne McLachlan
- Department of Medicine, St Vincent's Hospital, University of Melbourne, Melbourne, Australia.,Department of Medical Oncology, St Vincent's Hospital, Fitzroy, Melbourne, Australia
| | - Sandra C Jones
- ACU Engagement, Australian Catholic University, Melbourne, Australia
| | - Stephanie Nesci
- Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Michael L Friedlander
- Prince of Wales Clinical School University of New South Wales, Sydney, Australia.,Department of Medical Oncology, Prince of Wales Hospital, Randwick, NSW, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia
| | - Jon D Emery
- Department of General Practice and Centre for Cancer Research, University of Melbourne, Victorian Comprehensive Cancer Centre, Melbourne, Australia.,School of Primary, Aboriginal and Rural Health Care, University of Western Australia, Perth, Australia
| | - Martha Hickey
- Department of Obstetrics and Gynaecology, University of Melbourne and the Royal Women's Hospital, Melbourne, Australia
| | - Roger L Milne
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.,Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia.,Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Melbourne, Australia
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Barnes DR, Rookus MA, McGuffog L, Leslie G, Mooij TM, Dennis J, Mavaddat N, Adlard J, Ahmed M, Aittomäki K, Andrieu N, Andrulis IL, Arnold N, Arun BK, Azzollini J, Balmaña J, Barkardottir RB, Barrowdale D, Benitez J, Berthet P, Białkowska K, Blanco AM, Blok MJ, Bonanni B, Boonen SE, Borg Å, Bozsik A, Bradbury AR, Brennan P, Brewer C, Brunet J, Buys SS, Caldés T, Caligo MA, Campbell I, Christensen LL, Chung WK, Claes KBM, Colas C, Collonge-Rame MA, Cook J, Daly MB, Davidson R, de la Hoya M, de Putter R, Delnatte C, Devilee P, Diez O, Ding YC, Domchek SM, Dorfling CM, Dumont M, Eeles R, Ejlertsen B, Engel C, Evans DG, Faivre L, Foretova L, Fostira F, Friedlander M, Friedman E, Frost D, Ganz PA, Garber J, Gehrig A, Gerdes AM, Gesta P, Giraud S, Glendon G, Godwin AK, Goldgar DE, González-Neira A, Greene MH, Gschwantler-Kaulich D, Hahnen E, Hamann U, Hanson H, Hentschel J, Hogervorst FBL, Hooning MJ, Horvath J, Hu C, Hulick PJ, Imyanitov EN, Isaacs C, Izatt L, Izquierdo A, Jakubowska A, James PA, Janavicius R, John EM, Joseph V, Karlan BY, Kast K, Koudijs M, Kruse TA, Kwong A, Laitman Y, Lasset C, Lazaro C, Lester J, Lesueur F, Liljegren A, Loud JT, Lubiński J, Mai PL, Manoukian S, Mari V, Mebirouk N, Meijers-Heijboer HEJ, Meindl A, Mensenkamp AR, Miller A, Montagna M, Mouret-Fourme E, Mukherjee S, Mulligan AM, Nathanson KL, Neuhausen SL, Nevanlinna H, Niederacher D, Nielsen FC, Nikitina-Zake L, Noguès C, Olah E, Olopade OI, Ong KR, O'Shaughnessy-Kirwan A, Osorio A, Ott CE, Papi L, Park SK, Parsons MT, Pedersen IS, Peissel B, Peixoto A, Peterlongo P, Pfeiler G, Phillips KA, Prajzendanc K, Pujana MA, Radice P, Ramser J, Ramus SJ, Rantala J, Rennert G, Risch HA, Robson M, Rønlund K, Salani R, Schuster H, Senter L, Shah PD, Sharma P, Side LE, Singer CF, Slavin TP, Soucy P, Southey MC, Spurdle AB, Steinemann D, Steinsnyder Z, Stoppa-Lyonnet D, Sutter C, Tan YY, Teixeira MR, Teo SH, Thull DL, Tischkowitz M, Tognazzo S, Toland AE, Trainer AH, Tung N, van Engelen K, van Rensburg EJ, Vega A, Vierstraete J, Wagner G, Walker L, Wang-Gohrke S, Wappenschmidt B, Weitzel JN, Yadav S, Yang X, Yannoukakos D, Zimbalatti D, Offit K, Thomassen M, Couch FJ, Schmutzler RK, Simard J, Easton DF, Chenevix-Trench G, Antoniou AC. Polygenic risk scores and breast and epithelial ovarian cancer risks for carriers of BRCA1 and BRCA2 pathogenic variants. Genet Med 2020; 22:1653-1666. [PMID: 32665703 PMCID: PMC7521995 DOI: 10.1038/s41436-020-0862-x] [Citation(s) in RCA: 72] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Revised: 05/28/2020] [Accepted: 05/29/2020] [Indexed: 11/21/2022] Open
Abstract
PURPOSE We assessed the associations between population-based polygenic risk scores (PRS) for breast (BC) or epithelial ovarian cancer (EOC) with cancer risks for BRCA1 and BRCA2 pathogenic variant carriers. METHODS Retrospective cohort data on 18,935 BRCA1 and 12,339 BRCA2 female pathogenic variant carriers of European ancestry were available. Three versions of a 313 single-nucleotide polymorphism (SNP) BC PRS were evaluated based on whether they predict overall, estrogen receptor (ER)-negative, or ER-positive BC, and two PRS for overall or high-grade serous EOC. Associations were validated in a prospective cohort. RESULTS The ER-negative PRS showed the strongest association with BC risk for BRCA1 carriers (hazard ratio [HR] per standard deviation = 1.29 [95% CI 1.25-1.33], P = 3×10-72). For BRCA2, the strongest association was with overall BC PRS (HR = 1.31 [95% CI 1.27-1.36], P = 7×10-50). HR estimates decreased significantly with age and there was evidence for differences in associations by predicted variant effects on protein expression. The HR estimates were smaller than general population estimates. The high-grade serous PRS yielded the strongest associations with EOC risk for BRCA1 (HR = 1.32 [95% CI 1.25-1.40], P = 3×10-22) and BRCA2 (HR = 1.44 [95% CI 1.30-1.60], P = 4×10-12) carriers. The associations in the prospective cohort were similar. CONCLUSION Population-based PRS are strongly associated with BC and EOC risks for BRCA1/2 carriers and predict substantial absolute risk differences for women at PRS distribution extremes.
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Affiliation(s)
- Daniel R Barnes
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
| | - Matti A Rookus
- The Netherlands Cancer Institute, Department of Epidemiology (PSOE), Amsterdam, The Netherlands
| | - Lesley McGuffog
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Goska Leslie
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Thea M Mooij
- The Netherlands Cancer Institute, Department of Epidemiology (PSOE), Amsterdam, The Netherlands
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Nasim Mavaddat
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Julian Adlard
- Chapel Allerton Hospital, Yorkshire Regional Genetics Service, Leeds, UK
| | - Munaza Ahmed
- Great Ormond Street Hospital for Children NHS Trust, North East Thames Regional Genetics Service, London, UK
| | - Kristiina Aittomäki
- University of Helsinki, Department of Clinical Genetics, Helsinki University Hospital, Helsinki, Finland
| | - Nadine Andrieu
- Inserm U900, Genetic Epidemiology of Cancer team, Paris, France
- Institut Curie, Paris, France
- Mines ParisTech, Fontainebleau, France
- Department of Life & Health Sciences, PSL University, Paris, France
| | - Irene L Andrulis
- Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Fred A. Litwin Center for Cancer Genetics, Toronto, ON, Canada
- University of Toronto, Department of Molecular Genetics, Toronto, ON, Canada
| | - Norbert Arnold
- University Hospital of Schleswig-Holstein, Campus Kiel, Christian-Albrechts University Kiel, Department of Gynaecology and Obstetrics, Kiel, Germany
- University Hospital of Schleswig-Holstein, Campus Kiel, Christian-Albrechts University Kiel, Institute of Clinical Molecular Biology, Kiel, Germany
| | - Banu K Arun
- University of Texas MD Anderson Cancer Center, Department of Breast Medical Oncology, Houston, TX, USA
| | - Jacopo Azzollini
- Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Unit of Medical Genetics, Department of Medical Oncology and Hematology, Milan, Italy
| | - Judith Balmaña
- Vall d'Hebron Institute of Oncology, High Risk and Cancer Prevention Group, Barcelona, Spain
- University Hospital of Vall d'Hebron, Department of Medical Oncology, Barcelona, Spain
| | - Rosa B Barkardottir
- Landspitali University Hospital, Department of Pathology, Reykjavik, Iceland
- University of Iceland, BMC (Biomedical Centre), Faculty of Medicine, Reykjavik, Iceland
| | - Daniel Barrowdale
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Javier Benitez
- Centro de Investigación en Red de Enfermedades Raras (CIBERER), Madrid, Spain
- Spanish National Cancer Research Centre (CNIO), Human Cancer Genetics Programme, Madrid, Spain
| | - Pascaline Berthet
- Centre François Baclesse, Département de Biopathologie, Caen, France
| | - Katarzyna Białkowska
- Pomeranian Medical University, Department of Genetics and Pathology, Szczecin, Poland
| | - Amie M Blanco
- University of California San Francisco, Cancer Genetics and Prevention Program, San Francisco, CA, USA
| | - Marinus J Blok
- Maastricht University Medical Center, Department of Clinical Genetics, Maastricht, The Netherlands
| | - Bernardo Bonanni
- IEO, European Institute of Oncology IRCCS, Division of Cancer Prevention and Genetics, Milan, Italy
| | - Susanne E Boonen
- Zealand University Hospital, Clinical Genetic Unit, Department of Paediatrics, Roskilde, Denmark
| | - Åke Borg
- Lund University, Division of Oncology and Pathology, Department of Clinical Sciences Lund, Lund, Sweden
| | - Aniko Bozsik
- National Institute of Oncology, Department of Molecular Genetics, Budapest, Hungary
| | - Angela R Bradbury
- Perelman School of Medicine at the University of Pennsylvania, Department of Medicine, Abramson Cancer Center, Philadelphia, PA, USA
| | - Paul Brennan
- Institute of Genetic Medicine, International Centre for Life, Northern Genetic Service, Newcastle upon Tyne, UK
| | - Carole Brewer
- Royal Devon & Exeter Hospital, Department of Clinical Genetics, Exeter, UK
| | - Joan Brunet
- ONCOBELL-IDIBELL-IDIBGI-IGTP, Catalan Institute of Oncology, CIBERONC, Hereditary Cancer Program, Barcelona, Spain
| | - Saundra S Buys
- Huntsman Cancer Institute, Department of Medicine, Salt Lake City, UT, USA
| | - Trinidad Caldés
- CIBERONC, Hospital Clinico San Carlos, IdISSC (Instituto de Investigación Sanitaria del Hospital Clínico San Carlos), Molecular Oncology Laboratory, Madrid, Spain
| | - Maria A Caligo
- University Hospital, SOD Genetica Molecolare, Pisa, Italy
| | - Ian Campbell
- Peter MacCallum Cancer Center, Melbourne, VIC, Australia
- The University of Melbourne, Sir Peter MacCallum Department of Oncology, Melbourne, VIC, Australia
| | | | - Wendy K Chung
- Columbia University, Departments of Pediatrics and Medicine, New York, NY, USA
| | | | | | | | - Jackie Cook
- Sheffield Children's Hospital, Sheffield Clinical Genetics Service, Sheffield, UK
| | - Mary B Daly
- Fox Chase Cancer Center, Department of Clinical Genetics, Philadelphia, PA, USA
| | - Rosemarie Davidson
- Queen Elizabeth University Hospitals, Department of Clinical Genetics, Glasgow, UK
| | - Miguel de la Hoya
- CIBERONC, Hospital Clinico San Carlos, IdISSC (Instituto de Investigación Sanitaria del Hospital Clínico San Carlos), Molecular Oncology Laboratory, Madrid, Spain
| | - Robin de Putter
- Ghent University, Centre for Medical Genetics, Ghent, Belgium
| | | | - Peter Devilee
- Leiden University Medical Center, Department of Pathology, Leiden, The Netherlands
- Leiden University Medical Center, Department of Human Genetics, Leiden, The Netherlands
| | - Orland Diez
- Vall dHebron Institute of Oncology (VHIO), Oncogenetics Group, Barcelona, Spain
- University Hospital Vall dHebron, Clinical and Molecular Genetics Area, Barcelona, Spain
| | - Yuan Chun Ding
- Beckman Research Institute of City of Hope, Department of Population Sciences, Duarte, CA, USA
| | - Susan M Domchek
- University of Pennsylvania, Basser Center for BRCA, Abramson Cancer Center, Philadelphia, PA, USA
| | | | - Martine Dumont
- Centre Hospitalier Universitaire de Québec - Université Laval Research Center, Genomics Center,, Québec City, QC, Canada
| | - Ros Eeles
- The Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Oncogenetics Team, London, UK
| | - Bent Ejlertsen
- Rigshospitalet, Copenhagen University Hospital, Department of Oncology, Copenhagen, Denmark
| | - Christoph Engel
- University of Leipzig, Institute for Medical Informatics, Statistics and Epidemiology, Leipzig, Germany
| | - D Gareth Evans
- The University of Manchester, Manchester Academic Health Science Centre, Manchester Universities Foundation Trust, St. Mary's Hospital, Genomic Medicine, Division of Evolution and Genomic Sciences, Manchester, UK
- Manchester Academic Health Science Centre, Manchester Universities Foundation Trust, St. Mary's Hospital, Genomic Medicine, North West Genomics hub, Manchester, UK
| | - Laurence Faivre
- Centre Georges-François Leclerc, Unité d'oncogénétique, Centre de Lutte Contre le Cancer, Dijon, France
- DHU Dijon, Centre de Génétique, Dijon, France
| | - Lenka Foretova
- Masaryk Memorial Cancer Institute, Department of Cancer Epidemiology and Genetics, Brno, Czech Republic
| | - Florentia Fostira
- National Centre for Scientific Research 'Demokritos', Molecular Diagnostics Laboratory, INRASTES, Athens, Greece
| | - Michael Friedlander
- NHMRC Clinical Trials, ANZ GOTG Coordinating Centre, Camperdown, NSW, Australia
| | - Eitan Friedman
- Chaim Sheba Medical Center, The Susanne Levy Gertner Oncogenetics Unit, Ramat Gan, Israel
- Tel Aviv University, Sackler Faculty of Medicine, Ramat Aviv, Israel
| | - Debra Frost
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Patricia A Ganz
- Jonsson Comprehensive Cancer Centre, UCLA, Schools of Medicine and Public Health, Division of Cancer Prevention & Control Research, Los Angeles, CA, USA
| | - Judy Garber
- Dana-Farber Cancer Institute, Cancer Risk and Prevention Clinic, Boston, MA, USA
| | - Andrea Gehrig
- University Würzburg, Department of Human Genetics, Würzburg, Germany
| | - Anne-Marie Gerdes
- Rigshospitalet, Copenhagen University Hospital, Department of Clinical Genetics, Copenhagen, Denmark
| | - Paul Gesta
- CH Niort, Service Régional Oncogénétique Poitou-Charentes, Niort, France
| | - Sophie Giraud
- Hospices Civils de Lyon, Department of Genetics, Bron, France
| | - Gord Glendon
- Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Fred A. Litwin Center for Cancer Genetics, Toronto, ON, Canada
| | - Andrew K Godwin
- University of Kansas Medical Center, Department of Pathology and Laboratory Medicine, Kansas City, KS, USA
| | - David E Goldgar
- Huntsman Cancer Institute, University of Utah School of Medicine, Department of Dermatology, Salt Lake City, UT, USA
| | - Anna González-Neira
- Spanish National Cancer Research Centre (CNIO), Human Cancer Genetics Programme, Madrid, Spain
| | - Mark H Greene
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | | | - Eric Hahnen
- Faculty of Medicine and University Hospital Cologne, University of Cologne, Center for Familial Breast and Ovarian Cancer, Cologne, Germany
- Faculty of Medicine and University Hospital Cologne, University of Cologne, Center for Integrated Oncology (CIO), Cologne, Germany
| | - Ute Hamann
- German Cancer Research Center (DKFZ), Molecular Genetics of Breast Cancer, Heidelberg, Germany
| | - Helen Hanson
- St George's NHS Foundation Trust, Southwest Thames Regional Genetics Service, London, UK
| | - Julia Hentschel
- University Hospital Leipzig, Institute of Human Genetics, Leipzig, Germany
| | - Frans B L Hogervorst
- The Netherlands Cancer Institute - Antoni van Leeuwenhoek hospital, Family Cancer Clinic, Amsterdam, The Netherlands
| | - Maartje J Hooning
- Erasmus MC Cancer Institute, Department of Medical Oncology, Family Cancer Clinic, Rotterdam, The Netherlands
| | - Judit Horvath
- University of Münster, Institute of Human Genetics, Münster, Germany
| | - Chunling Hu
- Mayo Clinic, Department of Laboratory Medicine and Pathology, Rochester, MN, USA
| | - Peter J Hulick
- NorthShore University HealthSystem, Center for Medical Genetics, Evanston, IL, USA
- The University of Chicago Pritzker School of Medicine, Chicago, IL, USA
| | | | - Claudine Isaacs
- Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA
| | - Louise Izatt
- Guy's and St Thomas' NHS Foundation Trust, Clinical Genetics, London, UK
| | - Angel Izquierdo
- ONCOBELL-IDIBELL-IDIBGI-IGTP, Catalan Institute of Oncology, CIBERONC, Hereditary Cancer Program, Barcelona, Spain
| | - Anna Jakubowska
- Pomeranian Medical University, Department of Genetics and Pathology, Szczecin, Poland
- Pomeranian Medical University, Independent Laboratory of Molecular Biology and Genetic Diagnostics, Szczecin, Poland
| | - Paul A James
- The University of Melbourne, Sir Peter MacCallum Department of Oncology, Melbourne, VIC, Australia
- Peter MacCallum Cancer Center, Parkville Familial Cancer Centre, Melbourne, VIC, Australia
| | - Ramunas Janavicius
- Vilnius University Hospital Santariskiu Clinics, Hematology, Oncology and Transfusion Medicine Center, Department of Molecular and Regenerative Medicine, Vilnius, Lithuania
- State Research Institute Centre for Innovative Medicine, Vilnius, Lithuania
| | - Esther M John
- Stanford Cancer Institute, Stanford University School of Medicine, Department of Medicine, Division of Oncology, Stanford, CA, USA
| | - Vijai Joseph
- Memorial Sloan-Kettering Cancer Center, Clinical Genetics Research Lab, Department of Cancer Biology and Genetics, New York, NY, USA
| | - Beth Y Karlan
- University of California at Los Angeles, David Geffen School of Medicine, Department of Obstetrics and Gynecology, Los Angeles, CA, USA
- Cedars-Sinai Medical Center, Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute, Los Angeles, CA, USA
| | - Karin Kast
- Department of Gynecology and Obstetrics, Medical Faculty and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Marco Koudijs
- University Medical Center Utrecht, Department of Medical Genetics, Utrecht, The Netherlands
| | - Torben A Kruse
- Odense University Hospital, Department of Clinical Genetics, Odense, Denmark
| | - Ava Kwong
- Cancer Genetics Centre, Hong Kong Hereditary Breast Cancer Family Registry, Happy Valley, Hong Kong
- The University of Hong Kong, Department of Surgery, Pok Fu Lam, Hong Kong
- Hong Kong Sanatorium and Hospital, Department of Surgery, Happy Valley, Hong Kong
| | - Yael Laitman
- Chaim Sheba Medical Center, The Susanne Levy Gertner Oncogenetics Unit, Ramat Gan, Israel
| | - Christine Lasset
- Centre Léon Bérard, Unité de Prévention et d'Epidémiologie Génétique, Lyon, France
- Lyon University, UMR CNRS 5558, Lyon, France
| | - Conxi Lazaro
- ONCOBELL-IDIBELL-IDIBGI-IGTP, Catalan Institute of Oncology, CIBERONC, Hereditary Cancer Program, Barcelona, Spain
| | - Jenny Lester
- University of California at Los Angeles, David Geffen School of Medicine, Department of Obstetrics and Gynecology, Los Angeles, CA, USA
- Cedars-Sinai Medical Center, Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute, Los Angeles, CA, USA
| | - Fabienne Lesueur
- Inserm U900, Genetic Epidemiology of Cancer team, Paris, France
- Institut Curie, Paris, France
- Mines ParisTech, Fontainebleau, France
- Department of Life & Health Sciences, PSL University, Paris, France
| | | | - Jennifer T Loud
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Jan Lubiński
- Pomeranian Medical University, Department of Genetics and Pathology, Szczecin, Poland
| | - Phuong L Mai
- Magee-Womens Hospital, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Siranoush Manoukian
- Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Unit of Medical Genetics, Department of Medical Oncology and Hematology, Milan, Italy
| | - Véronique Mari
- Centre Antoine Lacassagne, Département d'Hématologie-Oncologie Médicale, Nice, France
| | - Noura Mebirouk
- Inserm U900, Genetic Epidemiology of Cancer team, Paris, France
- Institut Curie, Paris, France
- Mines ParisTech, Fontainebleau, France
- Department of Life & Health Sciences, PSL University, Paris, France
| | | | - Alfons Meindl
- University of Munich, Campus Großhadern, Department of Gynecology and Obstetrics, Munich, Germany
| | - Arjen R Mensenkamp
- Radboud University Medical Center, Department of Human Genetics, Nijmegen, The Netherlands
| | - Austin Miller
- Roswell Park Cancer Institute, NRG Oncology, Statistics and Data Management Center, Buffalo, NY, USA
| | - Marco Montagna
- Veneto Institute of Oncology IOV - IRCCS, Immunology and Molecular Oncology Unit, Padua, Italy
| | | | - Semanti Mukherjee
- Memorial Sloan-Kettering Cancer Center, Clinical Genetics Service, Department of Medicine, New York, NY, USA
| | - Anna Marie Mulligan
- University of Toronto, Department of Laboratory Medicine and Pathobiology, Toronto, ON, Canada
- University Health Network, Laboratory Medicine Program, Toronto, ON, Canada
| | - Katherine L Nathanson
- University of Pennsylvania, Basser Center for BRCA, Abramson Cancer Center, Philadelphia, PA, USA
| | - Susan L Neuhausen
- Beckman Research Institute of City of Hope, Department of Population Sciences, Duarte, CA, USA
| | - Heli Nevanlinna
- University of Helsinki, Department of Obstetrics and Gynecology, Helsinki University Hospital, Helsinki, Finland
| | - Dieter Niederacher
- University Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, Department of Gynecology and Obstetrics, Düsseldorf, Germany
| | - Finn Cilius Nielsen
- Rigshospitalet, Copenhagen University Hospital, Center for Genomic Medicine, Copenhagen, Denmark
| | | | - Catherine Noguès
- Oncogénétique Clinique and Aix Marseille Univ, INSERM, IRD, SESSTIM, Institut Paoli-Calmettes, Département d'Anticipation et de Suivi des Cancers, Marseille, France
| | - Edith Olah
- National Institute of Oncology, Department of Molecular Genetics, Budapest, Hungary
| | | | - Kai-Ren Ong
- Birmingham Women's Hospital Healthcare NHS Trust, West Midlands Regional Genetics Service, Birmingham, UK
| | - Aoife O'Shaughnessy-Kirwan
- Cambridge University Hospitals NHS Foundation Trust, East Anglian Medical Genetics Service, Cambridge, UK
| | - Ana Osorio
- Centro de Investigación en Red de Enfermedades Raras (CIBERER), Madrid, Spain
- Spanish National Cancer Research Centre (CNIO), Human Cancer Genetics Programme, Madrid, Spain
| | - Claus-Eric Ott
- Campus Virchov Klinikum, Charite, Institute of Human Genetics, Berlin, Germany
| | - Laura Papi
- University of Florence, Department of Experimental and Clinical Biomedical Sciences 'Mario Serio', Medical Genetics Unit, Florence, Italy
| | - Sue K Park
- Seoul National University College of Medicine, Department of Preventive Medicine, Seoul, Korea
- Seoul National University Graduate School, Department of Biomedical Sciences, Seoul, Korea
- Seoul National University, Cancer Research Institute, Seoul, Korea
| | - Michael T Parsons
- QIMR Berghofer Medical Research Institute, Department of Genetics and Computational Biology, Brisbane, QLD, Australia
| | - Inge Sokilde Pedersen
- Aalborg University Hospital, Molecular Diagnostics, Aalborg, Denmark
- Aalborg University Hospital, Clinical Cancer Research Center, Aalborg, Denmark
- Aalborg University, Department of Clinical Medicine, Aalborg, Denmark
| | - Bernard Peissel
- Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Unit of Medical Genetics, Department of Medical Oncology and Hematology, Milan, Italy
| | - Ana Peixoto
- Portuguese Oncology Institute, Department of Genetics, Porto, Portugal
| | - Paolo Peterlongo
- IFOM - the FIRC Institute of Molecular Oncology, Genome Diagnostics Program, Milan, Italy
| | - Georg Pfeiler
- Medical University of Vienna, Dept of OB/GYN and Comprehensive Cancer Center, Vienna, Austria
| | - Kelly-Anne Phillips
- Peter MacCallum Cancer Center, Melbourne, VIC, Australia
- The University of Melbourne, Sir Peter MacCallum Department of Oncology, Melbourne, VIC, Australia
- The University of Melbourne, Department of Medicine, St Vincent's Hospital, Fitzroy, VIC, Australia
- The University of Melbourne, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, Melbourne, VIC, Australia
| | - Karolina Prajzendanc
- Pomeranian Medical University, Department of Genetics and Pathology, Szczecin, Poland
| | - Miquel Angel Pujana
- IDIBELL (Bellvitge Biomedical Research Institute), Catalan Institute of Oncology, ProCURE, Barcelona, Spain
| | - Paolo Radice
- Fondazione IRCCS Istituto Nazionale dei Tumori (INT), Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Research, Milan, Italy
| | - Juliane Ramser
- Klinikum rechts der Isar der Technischen Universität München, Department of Gynaecology and Obstetrics, Munich, Germany
| | - Susan J Ramus
- University of NSW Sydney, School of Women's and Children's Health, Faculty of Medicine, Sydney, NSW, Australia
- The Kinghorn Cancer Centre, Garvan Institute of Medical Research, Sydney, NSW, Australia
- University of NSW Sydney, Adult Cancer Program, Lowy Cancer Research Centre, Sydney, NSW, Australia
| | | | - Gad Rennert
- Carmel Medical Center and Technion Faculty of Medicine, Clalit National Cancer Control Center, Haifa, Israel
| | - Harvey A Risch
- Yale School of Medicine, Chronic Disease Epidemiology, New Haven, CT, USA
| | - Mark Robson
- Memorial Sloan-Kettering Cancer Center, Clinical Genetics Service, Department of Medicine, New York, NY, USA
| | - Karina Rønlund
- Region of Southern Denmark, Vejle Hospital, Department of Clinical Genetics, Vejle, Denmark
| | - Ritu Salani
- Wexner Medical Center, The Ohio State University, Department of Gynecology and Obstetrics, Columbus, OH, USA
| | - Hélène Schuster
- Unité d'Oncogénétique Centre de Lutte contre le Cancer Paul Strauss, Strasbourg, France
- Institut de Cancérologie Strasbourg Europe, ICANS, Strasbourg, France
- Université de Strasbourg, Laboratoire d'ImmunoRhumatologie Moléculaire, Plateforme GENOMAX, INSERM UMR_S 1109, LabEx TRANSPLANTEX, Fédération de Médecine Translationnelle de Strasbourg (FMTS), Faculté de Médecine, Strasbourg, France
| | - Leigha Senter
- The Ohio State University, Clinical Cancer Genetics Program, Division of Human Genetics, Department of Internal Medicine, The Comprehensive Cancer Center, Columbus, OH, USA
| | - Payal D Shah
- Perelman School of Medicine at the University of Pennsylvania, Department of Medicine, Abramson Cancer Center, Philadelphia, PA, USA
| | - Priyanka Sharma
- University of Kansas Medical Center, Department of Internal Medicine, Division of Medical Oncology, Westwood, KS, USA
| | | | - Christian F Singer
- Medical University of Vienna, Dept of OB/GYN and Comprehensive Cancer Center, Vienna, Austria
| | | | - Penny Soucy
- Centre Hospitalier Universitaire de Québec - Université Laval Research Center, Genomics Center,, Québec City, QC, Canada
| | - Melissa C Southey
- Monash University, Precision Medicine, School of Clinical Sciences at Monash Health, Clayton, VIC, Australia
- The University of Melbourne, Department of Clinical Pathology, Melbourne, VIC, Australia
- Cancer Council Victoria, Cancer Epidemiology Division, Melbourne, VIC, Australia
| | - Amanda B Spurdle
- QIMR Berghofer Medical Research Institute, Department of Genetics and Computational Biology, Brisbane, QLD, Australia
| | - Doris Steinemann
- Hannover Medical School, Institute of Human Genetics, Hannover, Germany
| | - Zoe Steinsnyder
- Memorial Sloan-Kettering Cancer Center, Clinical Genetics Service, Department of Medicine, New York, NY, USA
| | - Dominique Stoppa-Lyonnet
- Institut Curie, Service de Génétique, Paris, France
- INSERM U830, Department of Tumour Biology, Paris, France
- Université Paris Descartes, Paris, France
| | - Christian Sutter
- University Hospital Heidelberg, Institute of Human Genetics, Heidelberg, Germany
| | - Yen Yen Tan
- Medical University of Vienna, Dept of OB/GYN, Vienna, Austria
| | - Manuel R Teixeira
- Portuguese Oncology Institute, Department of Genetics, Porto, Portugal
- University of Porto, Biomedical Sciences Institute (ICBAS), Porto, Portugal
| | - Soo Hwang Teo
- Cancer Research Malaysia, Breast Cancer Research Programme, Subang Jaya, Selangor, Malaysia
- University of Malaya, Department of Surgery, Faculty of Medicine, Kuala Lumpur, Malaysia
| | - Darcy L Thull
- Magee-Womens Hospital, University of Pittsburgh School of Medicine, Department of Medicine, Pittsburgh, PA, USA
| | - Marc Tischkowitz
- McGill University, Program in Cancer Genetics, Departments of Human Genetics and Oncology, Montréal, QC, Canada
- University of Cambridge, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge, UK
| | - Silvia Tognazzo
- Veneto Institute of Oncology IOV - IRCCS, Immunology and Molecular Oncology Unit, Padua, Italy
| | - Amanda E Toland
- The Ohio State University, Department of Cancer Biology and Genetics, Columbus, OH, USA
| | - Alison H Trainer
- Peter MacCallum Cancer Center, Parkville Familial Cancer Centre, Melbourne, VIC, Australia
- University Of Melbourne, Department of Medicine, Melbourne, VIC, Australia
| | - Nadine Tung
- Beth Israel Deaconess Medical Center, Department of Medical Oncology, Boston, MA, USA
| | - Klaartje van Engelen
- Amsterdam UMC, location VUmc, Department of Clinical Genetics, Amsterdam, The Netherlands
| | | | - Ana Vega
- Centro de Investigación en Red de Enfermedades Raras (CIBERER), Madrid, Spain
- Fundación Pública Galega de Medicina Xenómica, Santiago de Compostela, Spain
- Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago, SERGAS, Santiago de Compostela, Spain
| | | | - Gabriel Wagner
- Medical University of Vienna, Dept of OB/GYN and Comprehensive Cancer Center, Vienna, Austria
| | - Lisa Walker
- Oxford University Hospitals, Oxford Centre for Genomic Medicine, Oxford, UK
| | - Shan Wang-Gohrke
- University Hospital Ulm, Department of Gynaecology and Obstetrics, Ulm, Germany
| | - Barbara Wappenschmidt
- Faculty of Medicine and University Hospital Cologne, University of Cologne, Center for Familial Breast and Ovarian Cancer, Cologne, Germany
- Faculty of Medicine and University Hospital Cologne, University of Cologne, Center for Integrated Oncology (CIO), Cologne, Germany
| | | | | | - Xin Yang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Drakoulis Yannoukakos
- National Centre for Scientific Research 'Demokritos', Molecular Diagnostics Laboratory, INRASTES, Athens, Greece
| | - Dario Zimbalatti
- Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Unit of Medical Genetics, Department of Medical Oncology and Hematology, Milan, Italy
| | - Kenneth Offit
- Memorial Sloan-Kettering Cancer Center, Clinical Genetics Research Lab, Department of Cancer Biology and Genetics, New York, NY, USA
- Memorial Sloan-Kettering Cancer Center, Clinical Genetics Service, Department of Medicine, New York, NY, USA
| | - Mads Thomassen
- Odense University Hospital, Department of Clinical Genetics, Odense, Denmark
| | - Fergus J Couch
- Mayo Clinic, Department of Laboratory Medicine and Pathology, Rochester, MN, USA
| | - Rita K Schmutzler
- Faculty of Medicine and University Hospital Cologne, University of Cologne, Center for Familial Breast and Ovarian Cancer, Cologne, Germany
- Faculty of Medicine and University Hospital Cologne, University of Cologne, Center for Integrated Oncology (CIO), Cologne, Germany
- Faculty of Medicine and University Hospital Cologne, University of Cologne, Center for Molecular Medicine Cologne (CMMC), Cologne, Germany
| | - Jacques Simard
- Centre Hospitalier Universitaire de Québec - Université Laval Research Center, Genomics Center,, Québec City, QC, Canada
| | - 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
| | - Georgia Chenevix-Trench
- QIMR Berghofer Medical Research Institute, Department of Genetics and Computational Biology, Brisbane, QLD, Australia
| | - Antonis C Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
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Breast cancer screening for women at high risk: review of current guidelines from leading specialty societies. Breast Cancer 2020; 28:1195-1211. [PMID: 32959120 DOI: 10.1007/s12282-020-01157-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2020] [Accepted: 08/28/2020] [Indexed: 12/20/2022]
Abstract
The purpose of this article is to overview the existing breast cancer screening guidelines for women at high risk from world-leading specialty societies. Accumulation of evidence and development of accessible genetic testing strategies have changed the idea of breast cancer screening for high-risk women. Personalized tailor-made screening adjusted for risk factors has been conducted in accordance with guidelines. The use of imaging modalities other than mammography including contrast-enhanced MRI and other various strategies for improving screening are discussed. The present review also mentions the existing challenges in high-risk screening and the latest information based on two large-scale studies.
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Prevalence of pancreaticobiliary cancers in Irish families with pathogenic BRCA1 and BRCA2 variants. Fam Cancer 2020; 20:97-101. [PMID: 32918181 DOI: 10.1007/s10689-020-00205-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Accepted: 08/27/2020] [Indexed: 12/27/2022]
Abstract
Pathogenic variants (PVs) in the BRCA1 and BRCA2 genes are associated with an increased lifetime risk of pancreatic ductal adenocarcinoma (PDAC), and more recently have been associated with increased risk of biliary tract cancers (BTC). This study assessed the prevalence, age and gender distribution of PDAC/BTC cases in families known to carry a BRCA1/2 PV compared to those of the Irish population. A review of all families referred to a national genetics clinic from 09/11/1997 to 01/06/2018 was performed. The BOADICEA algorithm was used to estimate the probability that an untested relative of a known BRCA1/2 PV carrier with PDAC was a carrier. We reviewed 3252 family pedigrees, 1193 contained a proband who underwent testing for BRCA1/2 based on Manchester score ≥ 15. Among 128 BRCA2 PV-positive families, 27 (21%) contained a 1st/2nd/3rd-degree relative with PDAC, while of 116 BRCA1 PV-positive families, 11 (9%) contained a 1st/2nd/3rd-degree relative with PDAC. Within these 38 families, 25 patients with PDAC had ≥ 50% likelihood of being a BRCA1/2 PV carrier. This cohort had a median age at diagnosis of 55 years (range 33-75), with a mean (55 years) lower than 8364 patients with PDAC identified through the National Cancer Registry of Ireland (71 years, p < 0.0001). Six BRCA2 positive (5%) and 2 BRCA1 positive pedigrees (2%) included an individual with BTC; median age at diagnosis was 65 years (range 33-99). PDAC and BTC are prevalent in Irish families harbouring a BRCA2 PV and are associated with early-onset malignancy. This supports current guidelines recommending universal germline testing for PDAC patients.
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Agata S, Tognazzo S, Alducci E, Matricardi L, Moserle L, Barana D, Montagna M. Segregation analysis of the BRCA2 c.9227G>T variant in multiple families suggests a pathogenic role in breast and ovarian cancer predisposition. Sci Rep 2020; 10:13987. [PMID: 32814805 PMCID: PMC7438490 DOI: 10.1038/s41598-020-70729-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 07/20/2020] [Indexed: 11/09/2022] Open
Abstract
Classification of variants in the BRCA1 and BRCA2 genes has a major impact on the clinical management of subjects at high risk for breast and ovarian cancer. The identification of a pathogenic variant allows for early detection/prevention strategies in healthy carriers as well as targeted treatments in patients affected by BRCA-associated tumors. The BRCA2 c.9227G>T p.(Gly3076Val) variant recurs in families from Northeast Italy and is rarely reported in international databases. This variant substitutes the evolutionary invariant glycine 3076 with a valine in the DNA binding domain of the BRCA2 protein, thus suggesting a high probability of pathogenicity. We analysed clinical and genealogic data of carriers from 15 breast/ovarian cancer families in whom no other pathogenic variants were detected. The variant was shown to co-segregate with breast and ovarian cancer in the most informative families. Combined segregation data led to a likelihood ratio of 81,527:1 of pathogenicity vs. neutrality. We conclude that c.9227G>T is a BRCA2 pathogenic variant that recurs in Northeast Italy. It can now be safely used for the predictive testing of healthy family members to guide preventive surgery and/or early tumor detection strategies, as well as for PARP inhibitors treatments in patients with BRCA2-associated tumors.
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Affiliation(s)
- Simona Agata
- Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, Padua, Italy
| | - Silvia Tognazzo
- Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, Padua, Italy
| | - Elisa Alducci
- Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, Padua, Italy
| | - Laura Matricardi
- Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, Padua, Italy
| | - Lidia Moserle
- Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, Padua, Italy
| | - Daniela Barana
- Oncology Unit, Local Health and Social Care Unit ULSS8 Berica, Montecchio Maggiore, Italy
| | - Marco Montagna
- Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, Padua, Italy.
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McWilliams L, Woof VG, Donnelly LS, Howell A, Evans DG, French DP. Risk stratified breast cancer screening: UK healthcare policy decision-making stakeholders' views on a low-risk breast screening pathway. BMC Cancer 2020; 20:680. [PMID: 32698780 PMCID: PMC7374862 DOI: 10.1186/s12885-020-07158-9] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 07/09/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND There is international interest in risk-stratification of breast screening programmes to allow women at higher risk to benefit from more frequent screening and chemoprevention. Risk-stratification also identifies women at low-risk who could be screened less frequently, as the harms of breast screening may outweigh benefits for this group. The present research aimed to elicit the views of national healthcare policy decision-makers regarding implementation of less frequent screening intervals for women at low-risk. METHODS Seventeen professionals were purposively recruited to ensure relevant professional group representation directly or indirectly associated with the UK National Screening Committee and National Institute for Health and Care Excellence (NICE) clinical guidelines. Interviews were analysed using thematic analysis. RESULTS Three themes are reported: (1) producing the evidence defining low-risk, describing requirements preceding implementation; (2) the impact of risk stratification on women is complicated, focusing on gaining acceptability from women; and (3) practically implementing a low-risk pathway, where feasibility questions are highlighted. CONCLUSIONS Overall, national healthcare policy decision-makers appear to believe that risk-stratified breast screening is acceptable, in principle. It will however be essential to address key obstacles prior to implementation in national programmes.
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Affiliation(s)
- Lorna McWilliams
- Manchester Centre for Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, MAHSC, Oxford Road, Manchester, M13 9PL, UK
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Manchester University Hospitals NHS Foundation Trust, Manchester, England
| | - Victoria G Woof
- Manchester Centre for Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, MAHSC, Oxford Road, Manchester, M13 9PL, UK
| | - Louise S Donnelly
- Nightingale & Prevent Breast Cancer Research Unit, Manchester University NHS Foundation Trust, Southmoor Road, Wythenshawe, Manchester, M23 9LT, UK
- NIHR Greater Manchester Patient Safety Translational Research Centre, Centre for Mental Health and Safety, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, MAHSC, Oxford Road, Manchester, M13 9PL, UK
| | - Anthony Howell
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Manchester University Hospitals NHS Foundation Trust, Manchester, England
- Nightingale & Prevent Breast Cancer Research Unit, Manchester University NHS Foundation Trust, Southmoor Road, Wythenshawe, Manchester, M23 9LT, UK
| | - D Gareth Evans
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Manchester University Hospitals NHS Foundation Trust, Manchester, England
- Nightingale & Prevent Breast Cancer Research Unit, Manchester University NHS Foundation Trust, Southmoor Road, Wythenshawe, Manchester, M23 9LT, UK
- Department of Genomic Medicine, Division of Evolution and Genomic Science, Manchester Academic Health Science Centre, University of Manchester, Manchester University NHS Foundation Trust, Oxford Road, Manchester, M13 9WL, UK
| | - David P French
- Manchester Centre for Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, MAHSC, Oxford Road, Manchester, M13 9PL, UK.
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Manchester University Hospitals NHS Foundation Trust, Manchester, England.
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Gill G, Beard C, Storey K, Taylor S, Sexton A. "It wasn't just for me": Motivations and implications of genetic testing for women at a low risk of hereditary breast and ovarian cancer syndrome. Psychooncology 2020; 29:1303-1311. [PMID: 32497346 DOI: 10.1002/pon.5436] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Revised: 04/29/2020] [Accepted: 05/26/2020] [Indexed: 12/22/2022]
Abstract
OBJECTIVE Genetic testing for hereditary breast and ovarian cancer (HBOC) due to pathogenic variants in BRCA1 or BRCA2 is why most women present to familial cancer centers. Despite being assessed as low risk for HBOC, many women proceed with genetic testing. This study explored the genetic testing experiences of unaffected women at low risk of HBOC to clarify what motivates these women to have testing, and what are the implications of the results. METHODS A qualitative approach was taken. Participants included women who had genetic testing for HBOC from 2016-2018 at the Parkville Familial Cancer Centre in Melbourne, Australia. In-depth, semi-structured interviews were conducted, and thematic analysis was undertaken on transcripts; transcripts were coded, codes were organized into a hierarchical system of categories/subcategories, and key themes were identified. RESULTS Analysis of 19 transcripts identified five themes: family underpinned all motivators for HBOC genetic testing; health professionals were influential throughout the process; participants were planning for a positive result; results influenced screening-anxiety and frequency; and negative results gave participants relief in many different ways. The three participants with positive results reported feeling shocked at the results and empowered giving this information to family members. CONCLUSIONS Women at low HBOC risk may be motivated to seek genetic testing, and access to this is increasingly offered through non-genetic health professionals. Professionals can support clients through genetic testing by recognizing familial experiences, providing accurate information, addressing risk perceptions, and understanding cancer anxiety felt by many women.
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Affiliation(s)
- Gulvir Gill
- Parkville Familial Cancer Centre and Genomic Medicine Department, Peter MacCallum Cancer Centre and the Royal Melbourne Hospital, Parkville, Victoria, Australia.,Department of Paediatrics, The University of Melbourne, Parkville, Victoria, Australia
| | - Catherine Beard
- Parkville Familial Cancer Centre and Genomic Medicine Department, Peter MacCallum Cancer Centre and the Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Kirsty Storey
- Parkville Familial Cancer Centre and Genomic Medicine Department, Peter MacCallum Cancer Centre and the Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Shelby Taylor
- Parkville Familial Cancer Centre and Genomic Medicine Department, Peter MacCallum Cancer Centre and the Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Adrienne Sexton
- Parkville Familial Cancer Centre and Genomic Medicine Department, Peter MacCallum Cancer Centre and the Royal Melbourne Hospital, Parkville, Victoria, Australia.,Department of Medicine, The University of Melbourne, Parkville, Victoria, Australia
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Harkness EF, Astley SM, Evans D. Risk-based breast cancer screening strategies in women. Best Pract Res Clin Obstet Gynaecol 2020; 65:3-17. [DOI: 10.1016/j.bpobgyn.2019.11.005] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 10/14/2019] [Accepted: 11/10/2019] [Indexed: 10/25/2022]
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Weidner A, Liggin M, Zuniga B, Tezak A, Wiesner G, Pal T. Breast cancer screening implications of risk modeling among female relatives of ATM and CHEK2 carriers. Cancer 2020; 126:1651-1655. [PMID: 31967672 PMCID: PMC7103510 DOI: 10.1002/cncr.32715] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2019] [Revised: 12/18/2019] [Accepted: 12/18/2019] [Indexed: 01/05/2023]
Abstract
BACKGROUND With the increasing use of multigene panel tests, pathogenic and likely pathogenic (P/LP) variants are identified more frequently in the moderate-penetrance breast cancer genes ATM and CHEK2. Lifetime breast cancer risk among women with P/LP variants in these genes generally exceeds 20%, meeting the threshold at which high-risk breast cancer screening through breast magnetic resonance imaging (MRI) is recommended. METHODS Among a registry-based sample of 56 ATM and 69 CHEK2 carriers, the authors sought to determine the percentage of relatives in whom a P/LP variant would impact breast cancer surveillance. Lifetime breast cancer risks for unaffected, female first-degree and second-degree relatives were estimated using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA). RESULTS Among first-degree relatives of ATM and CHEK2 carriers, only 22.6% and 14.9%, respectively, were found to have lifetime breast cancer risks of ≥20% based on family cancer history alone; however, when including the proband's P/LP variant in the model, these percentages increased significantly to 56.6% and 55.3%, respectively (P < .0001 and P < .0001, respectively). Similar increases in lifetime breast cancer risks were found among second-degree relatives. CONCLUSIONS The results of the current study suggest that the majority of female first-degree and second-degree relatives of ATM and CHEK2 carriers do not qualify for breast MRI based on family cancer history alone. Therefore, testing for these genes, as well as awareness of positive moderate-penetrance breast cancer gene results in the family, may impact MRI eligibility. These findings highlight the potential usefulness of and need for breast cancer risk models that incorporate moderate-penetrance gene positivity to inform screening recommendations among at-risk family members.
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Affiliation(s)
- Anne Weidner
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center
| | - Mariel Liggin
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center
- Tennessee State University
| | - Brenda Zuniga
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center
| | - Ann Tezak
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center
| | - Georgia Wiesner
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center
- Vandertilt-Ingram Cancer Center
| | - Tuya Pal
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center
- Vandertilt-Ingram Cancer Center
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Van Marcke C, Helaers R, De Leener A, Merhi A, Schoonjans CA, Ambroise J, Galant C, Delrée P, Rothé F, Bar I, Khoury E, Brouillard P, Canon JL, Vuylsteke P, Machiels JP, Berlière M, Limaye N, Vikkula M, Duhoux FP. Tumor sequencing is useful to refine the analysis of germline variants in unexplained high-risk breast cancer families. Breast Cancer Res 2020; 22:36. [PMID: 32295625 PMCID: PMC7161277 DOI: 10.1186/s13058-020-01273-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Accepted: 03/31/2020] [Indexed: 02/06/2023] Open
Abstract
Background Multigene panels are routinely used to assess for predisposing germline mutations in families at high breast cancer risk. The number of variants of unknown significance thereby identified increases with the number of sequenced genes. We aimed to determine whether tumor sequencing can help refine the analysis of germline variants based on second somatic genetic events in the same gene. Methods Whole-exome sequencing (WES) was performed on whole blood DNA from 70 unrelated breast cancer patients referred for genetic testing and without a BRCA1, BRCA2, TP53, or CHEK2 mutation. Rare variants were retained in a list of 735 genes. WES was performed on matched tumor DNA to identify somatic second hits (copy number alterations (CNAs) or mutations) in the same genes. Distinct methods (among which immunohistochemistry, mutational signatures, homologous recombination deficiency, and tumor mutation burden analyses) were used to further study the role of the variants in tumor development, as appropriate. Results Sixty-eight patients (97%) carried at least one germline variant (4.7 ± 2.0 variants per patient). Of the 329 variants, 55 (17%) presented a second hit in paired tumor tissue. Of these, 53 were CNAs, resulting in tumor enrichment (28 variants) or depletion (25 variants) of the germline variant. Eleven patients received variant disclosure, with clinical measures for five of them. Seven variants in breast cancer-predisposing genes were considered not implicated in oncogenesis. One patient presented significant tumor enrichment of a germline variant in the oncogene ERBB2, in vitro expression of which caused downstream signaling pathway activation. Conclusion Tumor sequencing is a powerful approach to refine variant interpretation in cancer-predisposing genes in high-risk breast cancer patients. In this series, the strategy provided clinically relevant information for 11 out of 70 patients (16%), adapted to the considered gene and the familial clinical phenotype.
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Affiliation(s)
- Cédric Van Marcke
- Department of Medical Oncology, Institut Roi Albert II, Cliniques universitaires Saint-Luc and Institut de Recherche Expérimentale et Clinique, UCLouvain, Brussels, Belgium.,Human Molecular Genetics, de Duve Institute, UCLouvain, Brussels, Belgium
| | - Raphaël Helaers
- Human Molecular Genetics, de Duve Institute, UCLouvain, Brussels, Belgium
| | - Anne De Leener
- Center for Human Genetics, Cliniques universitaires Saint-Luc, Brussels, Belgium.,Breast Clinic, Institut Roi Albert II, Cliniques universitaires Saint-Luc, Avenue Hippocrate 10, 1200, Brussels, Belgium
| | - Ahmad Merhi
- Laboratory of Translational Oncology and IPG BioBank, Institute of Pathology and Genetics, Gosselies, Belgium
| | | | - Jérôme Ambroise
- Center for Applied Molecular Technologies, Institut de Recherche Expérimentale et Clinique, UCLouvain, Brussels, Belgium
| | - Christine Galant
- Breast Clinic, Institut Roi Albert II, Cliniques universitaires Saint-Luc, Avenue Hippocrate 10, 1200, Brussels, Belgium.,Department of Pathology, Cliniques universitaires Saint-Luc, Brussels, Belgium
| | - Paul Delrée
- Department of Pathology, Institute of Pathology and Genetics, Gosselies, Belgium
| | - Françoise Rothé
- Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - Isabelle Bar
- Laboratory of Translational Oncology and IPG BioBank, Institute of Pathology and Genetics, Gosselies, Belgium
| | - Elsa Khoury
- Genetics of Autoimmune Diseases and Cancer, de Duve Institute, UCLouvain, Brussels, Belgium
| | - Pascal Brouillard
- Human Molecular Genetics, de Duve Institute, UCLouvain, Brussels, Belgium
| | - Jean-Luc Canon
- Department of Oncology-Hematology, Grand Hôpital de Charleroi, Charleroi, Belgium
| | - Peter Vuylsteke
- Department of Medical Oncology, UCLouvain, CHU UCL Namur, site Sainte-Elisabeth, Namur, Belgium
| | - Jean-Pascal Machiels
- Department of Medical Oncology, Institut Roi Albert II, Cliniques universitaires Saint-Luc and Institut de Recherche Expérimentale et Clinique, UCLouvain, Brussels, Belgium
| | - Martine Berlière
- Breast Clinic, Institut Roi Albert II, Cliniques universitaires Saint-Luc, Avenue Hippocrate 10, 1200, Brussels, Belgium
| | - Nisha Limaye
- Genetics of Autoimmune Diseases and Cancer, de Duve Institute, UCLouvain, Brussels, Belgium
| | - Miikka Vikkula
- Human Molecular Genetics, de Duve Institute, UCLouvain, Brussels, Belgium
| | - François P Duhoux
- Department of Medical Oncology, Institut Roi Albert II, Cliniques universitaires Saint-Luc and Institut de Recherche Expérimentale et Clinique, UCLouvain, Brussels, Belgium. .,Center for Human Genetics, Cliniques universitaires Saint-Luc, Brussels, Belgium. .,Breast Clinic, Institut Roi Albert II, Cliniques universitaires Saint-Luc, Avenue Hippocrate 10, 1200, Brussels, Belgium.
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Terkelsen T, Christensen LL, Fenton DC, Jensen UB, Sunde L, Thomassen M, Skytte AB. Population frequencies of pathogenic alleles of BRCA1 and BRCA2: analysis of 173 Danish breast cancer pedigrees using the BOADICEA model. Fam Cancer 2020; 18:381-388. [PMID: 31435815 DOI: 10.1007/s10689-019-00141-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
The Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) calculates the probability that a woman carries a pathogenic variant in BRCA1 or BRCA2 based on her pedigree and the population frequencies of pathogenic alleles of BRCA1 (0.0006394) and BRCA2 (0.00102) in the United Kingdom (UK). BOADICEA allows the clinician to define the population frequencies of pathogenic alleles of BRCA1 and BRCA2 for other populations but only includes preset values for the Ashkenazy Jewish and Icelandic populations. Among 173 early-onset breast cancer pedigrees in Denmark, BOADICEA discriminated well between carriers and non-carriers of pathogenic variants (area under the receiver operating characteristics curve: 0.81; 95% CI 0.74-0.86) but underestimated the frequency of carriers of pathogenic variants in BRCA1 or BRCA2 as measured by the observed-to-expected ratio (O/E 1.83; 95% CI 1.18-2.84). This reflects findings from older studies of BOADICEA in UK, German, Italian, and Chinese populations, all accounting for the different calibration for different carrier probabilities. To improve the performance of BOADICEA for non-UK populations, we developed a method to derive population frequencies of pathogenic alleles of BRCA1 and BRCA2. Compared to the UK population frequencies, we estimated the Danish population frequencies of pathogenic alleles to be higher for BRCA1 (0.0015; 95% CI 0.00064-0.0034) and lower for BRCA2 (0.00052; 95% CI 0.00018-0.0017) after adjusting for the different calibration of BOADICEA for different carrier probabilities. Incorporating additional population frequencies into BOADICEA could improve its performance for non-UK populations.
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Affiliation(s)
- Thorkild Terkelsen
- Department of Clinical Genetics, Aarhus University Hospital, Brendstrupgaardsvej 21C, 8200, Aarhus N, Denmark.
| | | | | | - Uffe Birk Jensen
- Department of Clinical Genetics, Aarhus University Hospital, Brendstrupgaardsvej 21C, 8200, Aarhus N, Denmark
| | - Lone Sunde
- Department of Clinical Genetics, Aarhus University Hospital, Brendstrupgaardsvej 21C, 8200, Aarhus N, Denmark
| | - Mads Thomassen
- Department of Clinical Genetics, Odense University Hospital, Odense, Denmark
| | - Anne-Bine Skytte
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark
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iCARE: An R package to build, validate and apply absolute risk models. PLoS One 2020; 15:e0228198. [PMID: 32023287 PMCID: PMC7001949 DOI: 10.1371/journal.pone.0228198] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Accepted: 01/09/2020] [Indexed: 01/07/2023] Open
Abstract
This report describes an R package, called the Individualized Coherent Absolute Risk Estimator (iCARE) tool, that allows researchers to build and evaluate models for absolute risk and apply them to estimate an individual's risk of developing disease during a specified time interval based on a set of user defined input parameters. An attractive feature of the software is that it gives users flexibility to update models rapidly based on new knowledge on risk factors and tailor models to different populations by specifying three input arguments: a model for relative risk, an age-specific disease incidence rate and the distribution of risk factors for the population of interest. The tool can handle missing information on risk factors for individuals for whom risks are to be predicted using a coherent approach where all estimates are derived from a single model after appropriate model averaging. The software allows single nucleotide polymorphisms (SNPs) to be incorporated into the model using published odds ratios and allele frequencies. The validation component of the software implements the methods for evaluation of model calibration, discrimination and risk-stratification based on independent validation datasets. We provide an illustration of the utility of iCARE for building, validating and applying absolute risk models using breast cancer as an example.
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45
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Terkelsen T, Rønning H, Skytte AB. Impact of genetic counseling on the uptake of contralateral prophylactic mastectomy among younger women with breast cancer. Acta Oncol 2020; 59:60-65. [PMID: 31379231 DOI: 10.1080/0284186x.2019.1648860] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Background: Preoperative genetic testing affects the surgical decision-making among women with breast cancer. To avoid breast-conserving surgery and to offer the possibility of mastectomy with immediate reconstruction in high-risk patients, genetic testing for pathogenic variants in BRCA1 or BRCA2 and a pedigree-based familial breast cancer risk assessment was offered to younger women with breast cancer in Denmark. We evaluated the impact of the risk stratification through genetic counseling on the uptake of contralateral prophylactic mastectomy (CPM).Material and methods: The prospective cohort study included all women with unilateral breast cancer before the age of 45 who participated in a genetic counseling program during their primary diagnostics in the Central Denmark Region (2013-2018). Each patient was followed from the time of the genetic test result to the end of follow-up to estimate the long-term uptake of CPM as a competing risk-adjusted cumulative incidence. We compared the uptake of CPM between the various genetic risk categories, ages of onset, and family histories in a multivariable Cox proportional hazards regression model, reporting hazard ratios (HR) with two-sided 95% confidence intervals (CIs).Results: 156 females, aged 21-44, learned their genetic test result within a median of 92 days [interquartile range (IQR): 75-114]. The maximal follow-up was 3.8 years (median 1.8; IQR: 0.49-2.5), after which 33% (95% CI: 24-42%) of the patients had undergone CPM. The uptake of CPM was inversely associated with the age of onset (HR 0.92; 95% CI: 0.86-0.98) and significantly higher among BRCA carriers (HR 2.9; 95% CI: 1.3-6.8) and patients from the high risk of breast cancer families (HR 5.6; 95% CI: 1.9-16) compared to the lower genetic risk categories.Conclusion: The risk stratification obtained through genetic counseling had a considerable impact on the surgical decision-making among younger women with breast cancer at long-term follow-up.
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Affiliation(s)
- Thorkild Terkelsen
- Department of Clinical Genetics, Aarhus University Hospital, Aarhus, Denmark
| | - Hanne Rønning
- Plastic and Breast Surgery, Aarhus University Hospital, Aarhus, Denmark
| | - Anne-Bine Skytte
- Department of Clinical Genetics, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark
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Jiang Y, Weinberg CR, Sandler DP, Zhao S. Use of detailed family history data to improve risk prediction,with application to breast cancer screening. PLoS One 2019; 14:e0226407. [PMID: 31846476 PMCID: PMC6917296 DOI: 10.1371/journal.pone.0226407] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Accepted: 11/26/2019] [Indexed: 01/26/2023] Open
Abstract
Background As breast cancer represents a major morbidity and mortality burden in the U.S., with about one in eight women developing invasive breast cancer over her lifetime, accurate low-cost screening is an important public health issue. First-degree family history, often simplified as a dichotomous or three-level categorical variable (0/1/>1) based on number of affected relatives, is an important risk factor for many conditions. However, detailed family structure information such as the total number of first-degree relatives, and for each, their current or death age, and age at diagnosis are also important for risk prediction. Methods We develop a family history score under a Bayesian framework, based on first-degree family structure. We tested performance of the proposed score using data from a large prospective cohort study of women with a first-degree breast cancer family history. We used likelihood ratio tests to evaluate whether the proposed score added additional information to a Cox model with known breast cancer risk factors and the three-level family history variable. We also compared prediction performance through Receiver Operating Characteristic (ROC) curves and goodness-of-fit testing. Results Our proposed Bayesian family history score improved fit compared to the commonly used three-level family history score, both without and with adjustment for other risk factors (likelihood ratio tests p = 0.003 without adjustment for other risk factors, and p = 0.007 and 0.009 under adjustment with two candidate sets of risk factors). AUCs of ROC curves for the two models were similar, though in all cases were higher after addition of the BFHS. Conclusions Capturing detailed family history data through the proposed family history score can improve risk assessment and prediction. Such approaches could enable better-targeted personalized screening schedules and prevention strategies.
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Affiliation(s)
- Yue Jiang
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, United States of America
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Clarice R. Weinberg
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, United States of America
| | - Dale P. Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, United States of America
| | - Shanshan Zhao
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, United States of America
- * E-mail:
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Zhang Z, Bien J, Mori M, Jindal S, Bergan R. A way forward for cancer prevention therapy: personalized risk assessment. Oncotarget 2019; 10:6898-6912. [PMID: 31839883 PMCID: PMC6901339 DOI: 10.18632/oncotarget.27365] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Accepted: 11/19/2019] [Indexed: 12/17/2022] Open
Abstract
Cancer is characterized by genetic and molecular aberrations whose number and complexity increase dramatically as cells progress along the spectrum of carcinogenesis. The pharmacologic application of agents in the context of a lower burden of dysregulated cellular processes constitutes an efficient strategy to enhance therapeutic efficacy, and underlies the rationale for using cancer prevention agents in high-risk populations. A longstanding barrier to implementing this strategy is that the risk in the general population is low for any given cancer, many people would have to be treated in order to benefit a few. Therefore, identifying and treating high-risk individuals will improve the risk: benefit ratio. Currently, risk is defined by considering a relatively low number of factors. A strategy that considers multiple factors has the ability to define a much-higher-risk cohort than the general population. This article will review the rationale for evaluating multiple risk factors so as to identify individuals at highest risk. It will use breast and lung cancer as examples, will describe currently available risk assessment tools, and will discuss ongoing efforts to expand the impact of this approach. The high potential of this strategy to provide a way forward for developing cancer prevention therapy will be highlighted.
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Affiliation(s)
- Zhenzhen Zhang
- Division of Hematology/Oncology, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
| | - Jeffrey Bien
- Division of Oncology, Stanford University, Palo Alto, California, USA
| | - Motomi Mori
- Biostatistics Shared Resource, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA.,OHSU-PSU School of Public Health, Oregon Health & Science University, Portland, Oregon, USA
| | - Sonali Jindal
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, Oregon, USA
| | - Raymond Bergan
- Division of Hematology/Oncology, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
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Thorat MA, Balasubramanian R. Breast cancer prevention in high-risk women. Best Pract Res Clin Obstet Gynaecol 2019; 65:18-31. [PMID: 31862315 DOI: 10.1016/j.bpobgyn.2019.11.006] [Citation(s) in RCA: 85] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 11/10/2019] [Accepted: 11/11/2019] [Indexed: 12/24/2022]
Abstract
Women at high risk of developing breast cancer are a heterogeneous group of women including those with and without high-risk germline mutation/s. Prevention in these women requires a personalised and multidisciplinary approach. Preventive therapy with selective oestrogen receptor modulators (SERMs) like tamoxifen and aromatase inhibitors (AIs) substantially reduces breast cancer risk well beyond the active treatment period. The importance of benign breast disease as a marker of increased breast cancer risk remains underappreciated, and although the benefit of preventive therapy may be greater in such women, preventive therapy remains underutilised in these and other high-risk women. Bilateral Risk-Reducing Mastectomy (BRRM) reduces the risk of developing breast cancer by 90% in high-risk women such as carriers of BRCA mutations. It also improves breast cancer-specific survival in BRCA1 carriers. Bilateral risk-reducing salpingo-oophorectomy may also reduce risk in premenopausal BRCA2 carriers. Further research to improve risk models, to identify surrogate biomarkers of preventive therapy benefit and to develop newer preventive agents is needed.
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Affiliation(s)
- Mangesh A Thorat
- Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London, United Kingdom; School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences & Medicine, King's College London, United Kingdom; Breast Services, Guy's Hospital, Great Maze Pond, London, SE1 9RT, United Kingdom.
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Livon D, Moretta J, Noguès C. [What attitude to women at high risk of breast cancer?]. Presse Med 2019; 48:1092-1100. [PMID: 31706893 DOI: 10.1016/j.lpm.2019.07.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Revised: 05/27/2019] [Accepted: 07/04/2019] [Indexed: 11/17/2022] Open
Abstract
In France, breast cancer is the most common cancer among women and the leading cause of cancer deaths. Identifying women with a "high" or "very high" breast cancer risk, according the terminology of the Haute Autorité de Santé 2014 guidelines, is essential to offer them special cares in term of screening and prevention. Women genetically predisposed have a very high risk of breast cancer. During the oncogenetic specialist consultation, familial and personal history of cancer is taken into account to evaluate the risk of hereditary Breast/Ovarian syndrome and thus the need of a genetic screening. In 2017, a list of 13 genes involved in hereditary ovarian or breast cancer has been established in France (Genetic and Cancer Group - Unicancer). Women carrying a BRCA1, BRCA2, PALB2, TP53, CDH1, PTEN mutation have a higher risk of breast cancer and are considered as "high risk". Therefore, medical breast surveillance similar to carriers of BRCA1/BRCA2 mutation is recommended for these patients (INCa guidelines 2017). However a mutation in one of those genes is only identified in approximatively 10 % of the screened families. The oncogenetic specialist's assessment distinguishes families in which women remain at a "high" risk of breast cancer (HAS 2014 for screening) from those where women have a "very high" risk (INCa guidelines 2017 for screening and prevention).
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Affiliation(s)
- Doriane Livon
- Institut Paoli-Calmettes, oncogénétique clinique, département d'anticipation et de suivi du cancer, 232, boulevard Sainte-Marguerite, 13009 Marseille, France.
| | - Jessica Moretta
- Institut Paoli-Calmettes, oncogénétique clinique, département d'anticipation et de suivi du cancer, 232, boulevard Sainte-Marguerite, 13009 Marseille, France
| | - Catherine Noguès
- Institut Paoli-Calmettes, oncogénétique clinique, département d'anticipation et de suivi du cancer, 232, boulevard Sainte-Marguerite, 13009 Marseille, France; Aix-Marseille Université, IRD, SESSTIM, Inserm, 13007 Marseille, France
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Speiser D, Rebitschek FG, Feufel MA, Brand H, Besch L, Kendel F. Accuracy in risk understanding among BRCA1/2-mutation carriers. PATIENT EDUCATION AND COUNSELING 2019; 102:1925-1931. [PMID: 31079956 DOI: 10.1016/j.pec.2019.05.007] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Revised: 03/07/2019] [Accepted: 05/04/2019] [Indexed: 06/09/2023]
Abstract
OBJECTIVE BRCA1/2-mutation carriers are at high risk of developing cancer. Since they must weigh clinical recommendations and decide on risk-reducing measures, the correct understanding of their 10-year cancer risks is essential. This study focused on the accuracy of women's subjective estimates of developing breast and ovarian cancer within ten years as prerequisite to reduce unnecessary prevention. METHODS 59 and 52 BRCA1/2-mutation carriers provided their individual risks of developing breast or ovarian cancer in the next 10 years, along with self-reported sociodemographic and psychosocial variables. Women's risk estimates were compared with their objective cancer risks that had been communicated before. RESULTS 22.6% of counselees under- and 53.2% of the counselees overestimated their 10-year risk of developing breast cancer. As for ovarian cancer, 5.6% under- whereas 51.9% overestimated their risk. Neither demographic factors such as education, parenthood and age, nor a prior diagnosis of breast cancer or prophylactic surgery accounted for these variations in risk accuracy. CONCLUSION Currently, risk communication during genetic counseling does not guarantee accurate risk estimation in BRCA-mutation carriers. PRACTICE IMPLICATIONS Counselors must be prepared to prevent overestimation. Counselees' risk estimates need to be assessed and corrected to enable informed decision-making and reduce risks of unnecessary preventive efforts.
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Affiliation(s)
- Dorothee Speiser
- Department of Gynecology with Breast Center, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany.
| | - Felix G Rebitschek
- Harding Center for Risk Literacy, Max Planck Institute for Human Development, Berlin, Lentzeallee 94, 14195 Berlin, Germany.
| | - Markus A Feufel
- Harding Center for Risk Literacy, Max Planck Institute for Human Development, Berlin, Lentzeallee 94, 14195 Berlin, Germany; Division of Ergonomics, Department of Psychology and Ergonomics, Technische Universität Berlin, Marchstr. 23, 10587 Berlin, Germany.
| | - Hannah Brand
- Institute of Medical Psychology, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - Laura Besch
- Institute of Medical Psychology, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - Friederike Kendel
- Institute of Medical Psychology, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany.
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