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Cornel MC, van der Meij KRM, van El CG, Rigter T, Henneman L. Genetic Screening-Emerging Issues. Genes (Basel) 2024; 15:581. [PMID: 38790210 PMCID: PMC11121342 DOI: 10.3390/genes15050581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 04/25/2024] [Accepted: 04/30/2024] [Indexed: 05/26/2024] Open
Abstract
In many countries, some form of genetic screening is offered to all or part of the population, either in the form of well-organized screening programs or in a less formalized way. Screening can be offered at different phases of life, such as preconception, prenatal, neonatal and later in life. Screening should only be offered if the advantages outweigh the disadvantages. Technical innovations in testing and treatment are driving changes in the field of prenatal and neonatal screening, where many jurisdictions have organized population-based screening programs. As a result, a greater number and wider range of conditions are being added to the programs, which can benefit couples' reproductive autonomy (preconception and prenatal screening) and improve early diagnosis to prevent irreversible health damage in children (neonatal screening) and in adults (cancer and cascade screening). While many developments in screening are technology-driven, citizens may also express a demand for innovation in screening, as was the case with non-invasive prenatal testing. Relatively new emerging issues for genetic screening, especially if testing is performed using DNA sequencing, relate to organization, data storage and interpretation, benefit-harm ratio and distributive justice, information provision and follow-up, all connected to acceptability in current healthcare systems.
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Affiliation(s)
- Martina C. Cornel
- Section Community Genetics, Department of Human Genetics, Amsterdam UMC, Vrije Universiteit Amsterdam, 1007 MB Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, 1100 DD Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Research Institute, 1100 DD Amsterdam, The Netherlands
| | - Karuna R. M. van der Meij
- Section Community Genetics, Department of Human Genetics, Amsterdam UMC, Vrije Universiteit Amsterdam, 1007 MB Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Research Institute, 1100 DD Amsterdam, The Netherlands
| | - Carla G. van El
- Section Community Genetics, Department of Human Genetics, Amsterdam UMC, Vrije Universiteit Amsterdam, 1007 MB Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, 1100 DD Amsterdam, The Netherlands
| | - Tessel Rigter
- Section Community Genetics, Department of Human Genetics, Amsterdam UMC, Vrije Universiteit Amsterdam, 1007 MB Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, 1100 DD Amsterdam, The Netherlands
| | - Lidewij Henneman
- Section Community Genetics, Department of Human Genetics, Amsterdam UMC, Vrije Universiteit Amsterdam, 1007 MB Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, 1100 DD Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Research Institute, 1100 DD Amsterdam, The Netherlands
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2
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Woodward ER, Lalloo F, Forde C, Pugh S, Burghel GJ, Schlecht H, Harkness EF, Howell A, Howell SJ, Gandhi A, Evans DG. Germline testing of BRCA1, BRCA2, PALB2 and CHEK2 c.1100delC in 1514 triple negative familial and isolated breast cancers from a single centre, with extended testing of ATM, RAD51C and RAD51D in over 400. J Med Genet 2024; 61:385-391. [PMID: 38123987 DOI: 10.1136/jmg-2023-109671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 11/14/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND The identification of germline pathogenic gene variants (PGVs) in triple negative breast cancer (TNBC) is important to inform further primary cancer risk reduction and TNBC treatment strategies. We therefore investigated the contribution of breast cancer associated PGVs to familial and isolated invasive TNBC. METHODS Outcomes of germline BRCA1, BRCA2 and CHEK2_c.1100delC testing were recorded in 1514 women (743-isolated, 771-familial), and for PALB2 in 846 women (541-isolated, 305-familial), with TNBC and smaller numbers for additional genes. Breast cancer free controls were identified from Predicting Risk Of Cancer At Screening and BRIDGES (Breast cancer RIsk after Diagnostic GEne Sequencing) studies. RESULTS BRCA1_PGVs were detected in 52 isolated (7.0%) and 195 (25.3%) familial cases (isolated-OR=58.9, 95% CI: 16.6 to 247.0), BRCA2_PGVs in 21 (2.8%) isolated and 67 (8.7%) familial cases (isolated-OR=5.0, 95% CI: 2.3 to 11.2), PALB2_PGVs in 9 (1.7%) isolated and 12 (3.9%) familial cases (isolated-OR=8.8, 95% CI: 2.5 to 30.4) and CHEK2_c.1100delC in 0 isolated and 3 (0.45%) familial cases (isolated-OR=0.0, 95% CI: 0.00 to 2.11). BRCA1_PGV detection rate was >10% for all familial TNBC age groups and significantly higher for younger diagnoses (familial: <50 years, n=165/538 (30.7%); ≥50 years, n=30/233 (12.9%); p<0.0001). Women with a G3_TNBC were more likely to have a BRCA1_PGV as compared with a BRCA2 or PALB2_PGV (p<0.0001). 0/743 isolated TNBC had the CHEK2_c.1100delC PGV and 0/305 any ATM_PGV, but 2/240 (0.83%) had a RAD51D_PGV. CONCLUSION PGVs in BRCA1 are associated with G3_TNBCs. Familial TNBCs and isolated TNBCs <30 years have a >10% likelihood of a PGV in BRCA1. BRCA1_PGVs are associated with younger age of familial TNBC. There was no evidence for any increased risk of TNBC with CHEK2 or ATM PGVs.
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Affiliation(s)
- Emma R Woodward
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
- Division of Evolution, Infection and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
- Manchester Breast Centre, The Christie NHS Foundation Trust, Manchester, UK
| | - Fiona Lalloo
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Claire Forde
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Sarah Pugh
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - George J Burghel
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Helene Schlecht
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Elaine F Harkness
- Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Anthony Howell
- Manchester Breast Centre, The Christie NHS Foundation Trust, Manchester, UK
- Prevent Breast Cancer Unit, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, UK
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Sacha J Howell
- Manchester Breast Centre, The Christie NHS Foundation Trust, Manchester, UK
- Prevent Breast Cancer Unit, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, UK
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Ashu Gandhi
- Prevent Breast Cancer Unit, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, UK
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - D Gareth Evans
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
- Division of Evolution, Infection and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
- Manchester Breast Centre, The Christie NHS Foundation Trust, Manchester, UK
- Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
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Zirpoli GR, Pfeiffer RM, Bertrand KA, Huo D, Lunetta KL, Palmer JR. Addition of polygenic risk score to a risk calculator for prediction of breast cancer in US Black women. Breast Cancer Res 2024; 26:2. [PMID: 38167144 PMCID: PMC10763003 DOI: 10.1186/s13058-023-01748-8] [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: 08/22/2023] [Accepted: 11/30/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Previous work in European ancestry populations has shown that adding a polygenic risk score (PRS) to breast cancer risk prediction models based on epidemiologic factors results in better discriminatory performance as measured by the AUC (area under the curve). Following publication of the first PRS to perform well in women of African ancestry (AA-PRS), we conducted an external validation of the AA-PRS and then evaluated the addition of the AA-PRS to a risk calculator for incident breast cancer in Black women based on epidemiologic factors (BWHS model). METHODS Data from the Black Women's Health Study, an ongoing prospective cohort study of 59,000 US Black women followed by biennial questionnaire since 1995, were used to calculate AUCs and 95% confidence intervals (CIs) for discriminatory accuracy of the BWHS model, the AA-PRS alone, and a new model that combined them. Analyses were based on data from 922 women with invasive breast cancer and 1844 age-matched controls. RESULTS AUCs were 0.577 (95% CI 0.556-0.598) for the BWHS model and 0.584 (95% CI 0.563-0.605) for the AA-PRS. For a model that combined estimates from the questionnaire-based BWHS model with the PRS, the AUC increased to 0.623 (95% CI 0.603-0.644). CONCLUSIONS This combined model represents a step forward for personalized breast cancer preventive care for US Black women, as its performance metrics are similar to those from models in other populations. Use of this new model may mitigate exacerbation of breast cancer disparities if and when it becomes feasible to include a PRS in routine health care decision-making.
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Affiliation(s)
- Gary R Zirpoli
- Slone Epidemiology Center at Boston University, Boston, MA, USA
| | - Ruth M Pfeiffer
- Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
- Division of Cancer Epidemiology and Biostatistics, National Cancer Institute, Bethesda, USA.
| | - Kimberly A Bertrand
- Slone Epidemiology Center at Boston University, Boston, MA, USA
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Dezheng Huo
- Department of Public Health Sciences, The University of Chicago, Chicago, IL, USA
- Center for Clinical Cancer Genetics & Global Health, The University of Chicago, Chicago, IL, USA
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Julie R Palmer
- Slone Epidemiology Center at Boston University, Boston, MA, USA.
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
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Mbuya-Bienge C, Pashayan N, Kazemali CD, Lapointe J, Simard J, Nabi H. A Systematic Review and Critical Assessment of Breast Cancer Risk Prediction Tools Incorporating a Polygenic Risk Score for the General Population. Cancers (Basel) 2023; 15:5380. [PMID: 38001640 PMCID: PMC10670420 DOI: 10.3390/cancers15225380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/26/2023] [Accepted: 11/03/2023] [Indexed: 11/26/2023] Open
Abstract
Single nucleotide polymorphisms (SNPs) in the form of a polygenic risk score (PRS) have emerged as a promising factor that could improve the predictive performance of breast cancer (BC) risk prediction tools. This study aims to appraise and critically assess the current evidence on these tools. Studies were identified using Medline, EMBASE and the Cochrane Library up to November 2022 and were included if they described the development and/ or validation of a BC risk prediction model using a PRS for women of the general population and if they reported a measure of predictive performance. We identified 37 articles, of which 29 combined genetic and non-genetic risk factors using seven different risk prediction tools. Most models (55.0%) were developed on populations from European ancestry and performed better than those developed on populations from other ancestry groups. Regardless of the number of SNPs in each PRS, models combining a PRS with genetic and non-genetic risk factors generally had better discriminatory accuracy (AUC from 0.52 to 0.77) than those using a PRS alone (AUC from 0.48 to 0.68). The overall risk of bias was considered low in most studies. BC risk prediction tools combining a PRS with genetic and non-genetic risk factors provided better discriminative accuracy than either used alone. Further studies are needed to cross-compare their clinical utility and readiness for implementation in public health practices.
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Affiliation(s)
- Cynthia Mbuya-Bienge
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada; (C.M.-B.); (C.D.K.)
- Oncology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1S 4L8, Canada;
| | - Nora Pashayan
- Department of Applied Health Research, University College London, London WC1E 6BT, UK;
| | - Cornelia D. Kazemali
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada; (C.M.-B.); (C.D.K.)
- Oncology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1S 4L8, Canada;
| | - Julie Lapointe
- Oncology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1S 4L8, Canada;
| | - Jacques Simard
- Endocrinology and Nephology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1V 4G2, Canada;
- Department of Molecular Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada
| | - Hermann Nabi
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada; (C.M.-B.); (C.D.K.)
- Oncology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1S 4L8, Canada;
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Woof VG, McWilliams L, Howell A, Evans DG, French DP. How do women at increased risk of breast cancer make sense of their risk? An interpretative phenomenological analysis. Br J Health Psychol 2023; 28:1169-1184. [PMID: 37395149 PMCID: PMC10947456 DOI: 10.1111/bjhp.12678] [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: 03/20/2023] [Revised: 06/08/2023] [Accepted: 06/16/2023] [Indexed: 07/04/2023]
Abstract
OBJECTIVES Offering breast cancer risk prediction for all women of screening age is being considered globally. For women who have received a clinically derived estimate, risk appraisals are often inaccurate. This study aimed to gain an in-depth understanding of women's lived experiences of receiving an increased breast cancer risk. DESIGN One-to-one semi-structured telephone interviews. METHODS Eight women informed that they were at a 10-year above-average (moderate) or high risk in a breast cancer risk study (BC-Predict) were interviewed about their views on breast cancer, personal breast cancer risk and risk prevention. Interviews lasted between 40 and 70 min. Data were analysed using Interpretative Phenomenological Analysis. RESULTS Four themes were generated: (i) encounters with breast cancer and perceived personal significance, where the nature of women's lived experiences of others with breast cancer impacted their views on the significance of the disease, (ii) 'It's random really': difficulty in seeking causal attributions, where women encountered contradictions and confusion in attributing causes to breast cancer, (iii) believing versus identifying with a clinically-derived breast cancer risk, where personal risk appraisals and expectations influenced women's ability to internalize their clinically derived risk and pursue preventative action and (iv) perceived utility of breast cancer risk notification, where women reflected on the usefulness of knowing their risk. CONCLUSIONS Providing (numerical) risk estimates appear to have little impact on stable yet internally contradictory beliefs about breast cancer risk. Given this, discussions with healthcare professionals are needed to help women form more accurate appraisals and make informed decisions.
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Affiliation(s)
| | | | - Anthony Howell
- University of ManchesterManchesterUK
- The Nightingale Centre, Wythenshawe HospitalManchester University NHS Foundation TrustManchesterUK
| | - D. Gareth Evans
- University of ManchesterManchesterUK
- The Nightingale Centre, Wythenshawe HospitalManchester University NHS Foundation TrustManchesterUK
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Evans DG, Burghel GJ, Schlecht H, Harkness EF, Gandhi A, Howell SJ, Howell A, Forde C, Lalloo F, Newman WG, Smith MJ, Woodward ER. Detection of pathogenic variants in breast cancer susceptibility genes in bilateral breast cancer. J Med Genet 2023; 60:974-979. [PMID: 37055167 DOI: 10.1136/jmg-2023-109196] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 03/22/2023] [Indexed: 04/15/2023]
Abstract
PURPOSE To investigate the frequency of germline pathogenic variants (PVs) in women with bilateral breast cancer. METHODS We undertook BRCA1/2 and CHEK2 c.1100delC molecular analysis in 764 samples and a multigene panel in 156. Detection rates were assessed by age at first primary, Manchester Score, and breast pathology. Oestrogen receptor (ER) status of the contralateral versus first breast cancer was compared on 1081 patients with breast cancer with BRCA1/BRCA2 PVs. RESULTS 764 women with bilateral breast cancer have undergone testing of BRCA1/2 and CHEK2; 407 were also tested for PALB2 and 177 for ATM. Detection rates were BRCA1 11.6%, BRCA2 14.0%, CHEK2 2.4%, PALB2 1.0%, ATM 1.1% and, for a subset of mainly very early onset tumours, TP53 4.6% (9 of 195). The highest PV detection rates were for triple negative cancers for BRCA1 (26.4%), grade 3 ER+HER2 for BRCA2 (27.9%) and HER2+ for CHEK2 (8.9%). ER status of the first primary in BRCA1 and BRCA2 PV heterozygotes was strongly predictive of the ER status of the second contralateral tumour since ~90% of second tumours were ER- in BRCA1 heterozygotes, and 50% were ER- in BRCA2 heterozygotes if the first was ER-. CONCLUSION We have shown a high rate of detection of BRCA1 and BRCA2 PVs in triple negative and grade 3 ER+HER2- first primary diagnoses, respectively. High rates of HER2+ were associated with CHEK2 PVs, and women ≤30 years were associated with TP53 PVs. First primary ER status in BRCA1/2 strongly predicts the second tumour will be the same ER status even if unusual for PVs in that gene.
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Affiliation(s)
- D Gareth Evans
- Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
- Genomic Medicine, Manchester Academic Health Science Centre, Manchester, UK
| | - George J Burghel
- Genomic Diagnostic Laboratory, Manchester University NHS Foundation Trust, Manchester, UK
| | - Helene Schlecht
- North West Genomic Laboratory Hub, Central Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | | | - Ashu Gandhi
- Prevent Breast Cancer Centre, Wythenshawe Hospital Manchester Universities Foundation Trust, Manchester, UK
| | - Sacha J Howell
- Genomic Medicine, Wythenshawe Hospital Manchester Universities Foundation Trust, Wythenshawe, UK
- Genomic Medicine, The Christie NHS Foundation Trust, Manchester, UK
| | - Anthony Howell
- Genomic Medicine, Prevent Breast Cancer Centre, Manchester, UK
| | - Claire Forde
- Clinical Genetics Service, Manchester Centre for Genomic Medicine, Central Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Fiona Lalloo
- Clinical Genetics Service, Manchester Centre for Genomic Medicine, Central Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - William G Newman
- Genetics, Central Manchester University foundation Trust, Manchester, UK
| | | | - Emma Roisin Woodward
- Manchester Centre for Genomic Medicine, Central Manchester NHS Foundation Trust, Manchester, UK
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Ho PJ, Lim EH, Hartman M, Wong FY, Li J. Breast cancer risk stratification using genetic and non-genetic risk assessment tools for 246,142 women in the UK Biobank. Genet Med 2023; 25:100917. [PMID: 37334786 DOI: 10.1016/j.gim.2023.100917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 06/08/2023] [Accepted: 06/09/2023] [Indexed: 06/20/2023] Open
Abstract
PURPOSE The benefit of using individual risk prediction tools to identify high-risk individuals for breast cancer (BC) screening is uncertain, despite the personalized approach of risk-based screening. METHODS We studied the overlap of predicted high-risk individuals among 246,142 women enrolled in the UK Biobank. Risk predictors assessed include the Gail model (Gail), BC family history (FH, binary), BC polygenic risk score (PRS), and presence of loss-of-function (LoF) variants in BC predisposition genes. Youden J-index was used to select optimal thresholds for defining high-risk. RESULTS In total, 147,399 were considered at high risk for developing BC within the next 2 years by at least 1 of the 4 risk prediction tools examined (Gail2-year > 0.5%: 47%, PRS2-yea r > 0.7%: 30%, FH: 6%, and LoF: 1%); 92,851 (38%) were flagged by only 1 risk predictor. The overlap between individuals flagged as high-risk because of genetic (PRS) and Gail model risk factors was 30%. The best-performing combinatorial model comprises a union of high-risk women identified by PRS, FH, and, LoF (AUC2-year [95% CI]: 62.2 [60.8 to 63.6]). Assigning individual weights to each risk prediction tool increased discriminatory ability. CONCLUSION Risk-based BC screening may require a multipronged approach that includes PRS, predisposition genes, FH, and other recognized risk factors.
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Affiliation(s)
- Peh Joo Ho
- Laboratory of Women's Health and Genetics, Genome Institute of Singapore, A∗STAR Research Entities, Singapore; Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Elaine H Lim
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore, Singapore
| | - Mikael Hartman
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Saw Swee Hock School of Public Health, National University of Singapore, Singapore; Department of Surgery, University Surgical Cluster, National University Hospital, Singapore, Singapore
| | - Fuh Yong Wong
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore, Singapore
| | - Jingmei Li
- Laboratory of Women's Health and Genetics, Genome Institute of Singapore, A∗STAR Research Entities, Singapore; Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
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Chen S, Tamimi RM, Colditz GA, Jiang S. Association and Prediction Utilizing Craniocaudal and Mediolateral Oblique View Digital Mammography and Long-Term Breast Cancer Risk. Cancer Prev Res (Phila) 2023; 16:531-537. [PMID: 37428020 PMCID: PMC10472097 DOI: 10.1158/1940-6207.capr-22-0499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 04/19/2023] [Accepted: 06/30/2023] [Indexed: 07/11/2023]
Abstract
Mammographic percentage of volumetric density is an important risk factor for breast cancer. Epidemiology studies historically used film images often limited to craniocaudal (CC) views to estimate area-based breast density. More recent studies using digital mammography images typically use the averaged density between craniocaudal (CC) and mediolateral oblique (MLO) view mammography for 5- and 10-year risk prediction. The performance in using either and both mammogram views has not been well-investigated. We use 3,804 full-field digital mammograms from the Joanne Knight Breast Health Cohort (294 incident cases and 657 controls), to quantity the association between volumetric percentage of density extracted from either and both mammography views and to assess the 5 and 10-year breast cancer risk prediction performance. Our results show that the association between percent volumetric density from CC, MLO, and the average between the two, retain essentially the same association with breast cancer risk. The 5- and 10-year risk prediction also shows similar prediction accuracy. Thus, one view is sufficient to assess association and predict future risk of breast cancer over a 5 or 10-year interval. PREVENTION RELEVANCE Expanding use of digital mammography and repeated screening provides opportunities for risk assessment. To use these images for risk estimates and guide risk management in real time requires efficient processing. Evaluating the contribution of different views to prediction performance can guide future applications for risk management in routine care.
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Affiliation(s)
- Simin Chen
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, Missouri
| | - Rulla M. Tamimi
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York
| | - Graham A. Colditz
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, Missouri
- Alvin J. Siteman Cancer Center, Barnes-Jewish Hospital and Washington University School of Medicine, St. Louis, Missouri
| | - Shu Jiang
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, Missouri
- Alvin J. Siteman Cancer Center, Barnes-Jewish Hospital and Washington University School of Medicine, St. Louis, Missouri
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Akdeniz BC, Mattingsdal M, Dominguez-Valentin M, Frei O, Shadrin A, Puustusmaa M, Saar R, Sõber S, Møller P, Andreassen OA, Padrik P, Hovig E. A Breast Cancer Polygenic Risk Score Is Feasible for Risk Stratification in the Norwegian Population. Cancers (Basel) 2023; 15:4124. [PMID: 37627152 PMCID: PMC10452897 DOI: 10.3390/cancers15164124] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 08/11/2023] [Accepted: 08/13/2023] [Indexed: 08/27/2023] Open
Abstract
BACKGROUND Statistical associations of numerous single nucleotide polymorphisms with breast cancer (BC) have been identified in genome-wide association studies (GWAS). Recent evidence suggests that a Polygenic Risk Score (PRS) can be a useful risk stratification instrument for a BC screening strategy, and a PRS test has been developed for clinical use. The performance of the PRS is yet unknown in the Norwegian population. AIM To evaluate the performance of PRS models for BC in a Norwegian dataset. METHODS We investigated a sample of 1053 BC cases and 7094 controls from different regions of Norway. PRS values were calculated using four PRS models, and their performance was evaluated by the area under the curve (AUC) and the odds ratio (OR). The effect of the PRS on the age of onset of BC was determined by a Cox regression model, and the lifetime absolute risk of developing BC was calculated using the iCare tool. RESULTS The best performing PRS model included 3820 SNPs, which yielded an AUC = 0.625 and an OR = 1.567 per one standard deviation increase. The PRS values of the samples correlate with an increased risk of BC, with a hazard ratio of 1.494 per one standard deviation increase (95% confidence interval of 1.406-1.588). The individuals in the highest decile of the PRS have at least twice the risk of developing BC compared to the individuals with a median PRS. The results in this study with Norwegian samples are coherent with the findings in the study conducted using Estonian and UK Biobank samples. CONCLUSION The previously validated PRS models have a similar observed accuracy in the Norwegian data as in the UK and Estonian populations. A PRS provides a meaningful association with the age of onset of BC and lifetime risk. Therefore, as suggested in Estonia, a PRS may also be integrated into the screening strategy for BC in Norway.
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Affiliation(s)
- Bayram Cevdet Akdeniz
- Center for Bioinformatics, Department of Informatics, University of Oslo, 0313 Oslo, Norway (E.H.)
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, University of Oslo, 4956 Oslo, Norway (O.A.A.)
| | - Morten Mattingsdal
- Center for Bioinformatics, Department of Informatics, University of Oslo, 0313 Oslo, Norway (E.H.)
- Department of Medical Research, Vestre Viken Hospital Trust, Bærum Hospital, 1346 Gjettum, Norway
| | - Mev Dominguez-Valentin
- Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, 0424 Oslo, Norway (P.M.)
| | - Oleksandr Frei
- Center for Bioinformatics, Department of Informatics, University of Oslo, 0313 Oslo, Norway (E.H.)
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, University of Oslo, 4956 Oslo, Norway (O.A.A.)
| | - Alexey Shadrin
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, University of Oslo, 4956 Oslo, Norway (O.A.A.)
| | | | - Regina Saar
- OÜ Antegenes, 50603 Tartu, Estonia; (M.P.); (R.S.)
| | - Siim Sõber
- OÜ Antegenes, 50603 Tartu, Estonia; (M.P.); (R.S.)
| | - Pål Møller
- Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, 0424 Oslo, Norway (P.M.)
| | - Ole A. Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, University of Oslo, 4956 Oslo, Norway (O.A.A.)
| | | | - Eivind Hovig
- Center for Bioinformatics, Department of Informatics, University of Oslo, 0313 Oslo, Norway (E.H.)
- Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, 0424 Oslo, Norway (P.M.)
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Evans DG, Sithambaram S, van Veen EM, Burghel GJ, Schlecht H, Harkness EF, Byers H, Ellingford JM, Gandhi A, Howell SJ, Howell A, Forde C, Lalloo F, Newman WG, Smith MJ, Woodward ER. Differential involvement of germline pathogenic variants in breast cancer genes between DCIS and low-grade invasive cancers. J Med Genet 2023; 60:740-746. [PMID: 36442995 DOI: 10.1136/jmg-2022-108790] [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: 06/28/2022] [Accepted: 11/14/2022] [Indexed: 11/29/2022]
Abstract
PURPOSE To investigate frequency of germline pathogenic variants (PVs) in women with ductal carcinoma in situ (DCIS) and grade 1 invasive breast cancer (G1BC). METHODS We undertook BRCA1/2 analysis in 311 women with DCIS and 392 with G1BC and extended panel testing (non-BRCA1/2) in 176/311 with DCIS and 156/392 with G1BC. We investigated PV detection by age at diagnosis, Manchester Score (MS), DCIS grade and receptor status. RESULTS 30/311 (9.6%) with DCIS and 16/392 with G1BC (4.1%) had a BRCA1/2 PV (p=0.003), and 24/176-(13.6%) and 7/156-(4.5%), respectively, a non-BRCA1/2 PV (p=0.004). Increasing MS was associated with increased likelihood of BRCA1/2 PV in both DCIS and G1BC, although the 10% threshold was not predictive for G1GB. 13/32 (40.6%) DCIS and 0/17 with G1BC <40 years had a non-BRCA1/2 PV (p<0.001). 0/16 DCIS G1 had a PV. For G2 and G3 DCIS, PV rates were 10/98 (BRCA1/2) and 9/90 (non-BRCA1/2), and 8/47 (BRCA1/2) and 8/45 (non-BRCA1/2), respectively. 6/9 BRCA1 and 3/26 BRCA2-associated DCIS were oestrogen receptor negative-(p=0.003). G1BC population testing showed no increased PV rate (OR=1.16, 95% CI 0.28 to 4.80). CONCLUSION DCIS is more likely to be associated with both BRCA1/2 and non-BRCA1/2 PVs than G1BC. Extended panel testing ought to be offered in young-onset DCIS where PV detection rates are highest.
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Affiliation(s)
- D Gareth Evans
- Division of Evolution and Genomic Science, The University of Manchester School of Health Sciences, Manchester, UK
| | - Siva Sithambaram
- Manchester Univerities Hospital NHS Foundation Trust, Manchester, UK
| | - Elke Maria van Veen
- Division of Evolution and Genomic Sciences, The University of Manchester, Manchester, UK
| | | | - Helene Schlecht
- North West Genomic Laboratory Hub, Central Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Elaine F Harkness
- Division of Evolution and Genomic Sciences, The University of Manchester, Manchester, UK
| | - Helen Byers
- Genomic Medicine, The University of Manchester School of Health Sciences, Manchester, UK
| | - Jamie M Ellingford
- Institute of Human Development, The University of Manchester School of Health Sciences, Manchester, UK
| | - Ashu Gandhi
- Prevent Breast Cancer Centre, Wythenshawe Hospital Manchester Universities Foundation Trust, Manchester, UK
| | - Sacha J Howell
- Manchester Univerities Hospital NHS Foundation Trust, Manchester, UK
- Department of Medical Oncology, The Christie NHS Foundation Trust, Manchester, UK
| | - Anthony Howell
- Manchester Foundation Trust, Prevent Breast Cancer Centre, Manchester, UK
| | - Claire Forde
- Clinical Genetics Service, Central Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Fiona Lalloo
- Clinical Genetics Service, Manchester Centre for Genomic Medicine, Central Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - William G Newman
- Genetics, The University of Manchester School of Health Sciences, Manchester, UK
| | - Miriam Jane Smith
- Genetic Medicine, The University of Manchester School of Health Sciences, Manchester, UK
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11
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Gareth Evans D, McWilliams L, Astley S, Brentnall AR, Cuzick J, Dobrashian R, Duffy SW, Gorman LS, Harkness EF, Harrison F, Harvie M, Jerrison A, Machin M, Maxwell AJ, Howell SJ, Wright SJ, Payne K, Qureshi N, Ruane H, Southworth J, Fox L, Bowers S, Hutchinson G, Thorpe E, Ulph F, Woof V, Howell A, French DP. Quantifying the effects of risk-stratified breast cancer screening when delivered in real time as routine practice versus usual screening: the BC-Predict non-randomised controlled study (NCT04359420). Br J Cancer 2023; 128:2063-2071. [PMID: 37005486 PMCID: PMC10066938 DOI: 10.1038/s41416-023-02250-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 02/28/2023] [Accepted: 03/20/2023] [Indexed: 04/04/2023] Open
Abstract
BACKGROUND Risk stratification as a routine part of the NHS Breast Screening Programme (NHSBSP) could provide a better balance of benefits and harms. We developed BC-Predict, to offer women when invited to the NHSBSP, which collects standard risk factor information; mammographic density; and in a sub-sample, a Polygenic Risk Score (PRS). METHODS Risk prediction was estimated primarily from self-reported questionnaires and mammographic density using the Tyrer-Cuzick risk model. Women eligible for NHSBSP were recruited. BC-Predict produced risk feedback letters, inviting women at high risk (≥8% 10-year) or moderate risk (≥5-<8% 10-year) to have appointments to discuss prevention and additional screening. RESULTS Overall uptake of BC-Predict in screening attendees was 16.9% with 2472 consenting to the study; 76.8% of those received risk feedback within the 8-week timeframe. Recruitment was 63.2% with an onsite recruiter and paper questionnaire compared to <10% with BC-Predict only (P < 0.0001). Risk appointment attendance was highest for those at high risk (40.6%); 77.5% of those opted for preventive medication. DISCUSSION We have shown that a real-time offer of breast cancer risk information (including both mammographic density and PRS) is feasible and can be delivered in reasonable time, although uptake requires personal contact. Preventive medication uptake in women newly identified at high risk is high and could improve the cost-effectiveness of risk stratification. TRIAL REGISTRATION Retrospectively registered with clinicaltrials.gov (NCT04359420).
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Affiliation(s)
- D Gareth Evans
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England.
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England.
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, 555 Wilmslow Road, Manchester, M20 4GJ, England.
- Genomic Medicine, Division of Evolution and Genomic Sciences, The University of Manchester, St Mary's Hospital, Manchester University NHS Foundation Trust, Oxford Road, Manchester, M13 9WL, England.
| | - Lorna McWilliams
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- Manchester Centre of Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, University of Manchester, Coupland Street, Manchester, M13 9PL, England
| | - Susan Astley
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Manchester, England
| | - Adam R Brentnall
- Centre for Prevention, Detection and Diagnosis, Wolfson Institute of Population Health, Queen Mary University of London, London, England
| | - Jack Cuzick
- Centre for Prevention, Detection and Diagnosis, Wolfson Institute of Population Health, Queen Mary University of London, London, England
| | - Richard Dobrashian
- East Lancashire Hospitals NHS Trust, Royal Blackburn Hospital, Haslingden Road, Lancashire, BB2 3HH, Manchester, England
| | - Stephen W Duffy
- Centre for Prevention, Detection and Diagnosis, Wolfson Institute of Population Health, Queen Mary University of London, London, England
| | - Louise S Gorman
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
- Manchester Centre of Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, University of Manchester, Coupland Street, Manchester, M13 9PL, England
- NIHR Greater Manchester Patient Safety Translational Research Centre, University of Manchester, Manchester, M13 9PL, England
| | - Elaine F Harkness
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, 555 Wilmslow Road, Manchester, M20 4GJ, England
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Manchester, England
| | | | - Michelle Harvie
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, 555 Wilmslow Road, Manchester, M20 4GJ, England
| | - Andrew Jerrison
- Research IT, IT Services, University of Manchester, Manchester, M13 9PL, England
| | - Matthew Machin
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Manchester, England
| | - Anthony J Maxwell
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, 555 Wilmslow Road, Manchester, M20 4GJ, England
| | - Sacha J Howell
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, 555 Wilmslow Road, Manchester, M20 4GJ, England
- Department of Medical Oncology, The Christie NHS Foundation Trust, Wilmslow Road, Manchester, M20 4BX, England
| | - Stuart J Wright
- Manchester Centre for Health Economics, Division of Population Health, Health Services Research & Primary Care, School of Health Sciences, University of Manchester, Manchester, M13 9PL, England
| | - Katherine Payne
- Manchester Centre for Health Economics, Division of Population Health, Health Services Research & Primary Care, School of Health Sciences, University of Manchester, Manchester, M13 9PL, England
| | - Nadeem Qureshi
- Primary Care Stratified Medicine research group, Centre for Academic Primary Care, University of Nottingham, University Park, Nottingham, NG7 2RD, England
| | - Helen Ruane
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
| | - Jake Southworth
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
| | - Lynne Fox
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
| | - Sarah Bowers
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
| | - Gillian Hutchinson
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
| | - Emma Thorpe
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
| | - Fiona Ulph
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- Manchester Centre of Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, University of Manchester, Coupland Street, Manchester, M13 9PL, England
| | - Victoria Woof
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- Manchester Centre of Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, University of Manchester, Coupland Street, Manchester, M13 9PL, England
| | - Anthony Howell
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, 555 Wilmslow Road, Manchester, M20 4GJ, England
- Department of Medical Oncology, The Christie NHS Foundation Trust, Wilmslow Road, Manchester, M20 4BX, England
| | - David P French
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England
- Manchester Centre of Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, University of Manchester, Coupland Street, Manchester, M13 9PL, England
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12
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Ayoub A, Lapointe J, Nabi H, Pashayan N. Risk-Stratified Breast Cancer Screening Incorporating a Polygenic Risk Score: A Survey of UK General Practitioners’ Knowledge and Attitudes. Genes (Basel) 2023; 14:genes14030732. [PMID: 36981003 PMCID: PMC10048009 DOI: 10.3390/genes14030732] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 02/10/2023] [Accepted: 03/13/2023] [Indexed: 03/19/2023] Open
Abstract
A polygenic risk score (PRS) quantifies the aggregated effects of common genetic variants in an individual. A ‘personalised breast cancer risk assessment’ combines PRS with other genetic and nongenetic risk factors to offer risk-stratified screening and interventions. Large-scale studies are evaluating the clinical utility and feasibility of implementing risk-stratified screening; however, General Practitioners’ (GPs) views remain largely unknown. This study aimed to explore GPs’: (i) knowledge of risk-stratified screening; (ii) attitudes towards risk-stratified screening; and (iii) preferences for continuing professional development. A cross-sectional online survey of UK GPs was conducted between July–August 2022. The survey was distributed by the Royal College of General Practitioners and via other mailing lists and social media. In total, 109 GPs completed the survey; 49% were not familiar with the concept of PRS. Regarding risk-stratified screening pathways, 75% agreed with earlier and more frequent screening for women at high risk, 43% neither agreed nor disagreed with later and less screening for women at lower-than-average risk, and 55% disagreed with completely removing screening for women at much lower risk. In total, 81% felt positive about the potential impact of risk-stratified screening towards patients and 62% felt positive about the potential impact on their practice. GPs selected training of healthcare professionals as the priority for future risk-stratified screening implementation, preferring online formats for learning. The results suggest limited knowledge of PRS and risk-stratified screening amongst GPs. Training—preferably using online learning formats—was identified as the top priority for future implementation. GPs felt positive about the potential impact of risk-stratified screening; however, there was hesitance and disagreement towards a low-risk screening pathway.
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Affiliation(s)
- Aya Ayoub
- National Heart and Lung Institute, Imperial College London, London SW3 6LY, UK
- Correspondence:
| | - Julie Lapointe
- Oncology Division, CHU de Québec-Université Laval Research Center, Québec City, QC G1R 3S3, Canada
| | - Hermann Nabi
- Oncology Division, CHU de Québec-Université Laval Research Center, Québec City, QC G1R 3S3, Canada
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Québec City, QC G1V 0A6, Canada
| | - Nora Pashayan
- Department of Applied Health Research, University College London (UCL), London WC1E 7HB, UK
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Roberts E, Howell S, Evans DG. Polygenic risk scores and breast cancer risk prediction. Breast 2023; 67:71-77. [PMID: 36646003 PMCID: PMC9982311 DOI: 10.1016/j.breast.2023.01.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 01/09/2023] [Indexed: 01/11/2023] Open
Abstract
Polygenic Risk Scores (PRS) are a major component of accurate breast cancer risk prediction and have the potential to improve screening and prevention strategies. PRS combine the risk from Single nucleotide polymorphisms (SNPs) associated with breast cancer in Genome Wide Association Studies (GWAS) and explain over 30% of breast cancer heritability. When incorporated into risk models, the more personalised risk assessment derived from PRS, help identify women at higher risk of breast cancer development and enables the implementation of stratified screening and prevention approaches. This review describes the role of PRS in breast cancer risk prediction including the development of PRS and their clinical application. We have also examined the role of PRS within more well-established risk prediction models which incorporate known classic risk factors and discuss the interaction of PRS with these factors and their capacity to predict breast cancer subtypes. Before PRS can be implemented on a population-wide scale, there are several challenges that must be addressed. Perhaps the most pressing of these is the use of PRS in women of non-White European origin, where PRS have been shown to have attenuated risk prediction both in discrimination and calibration. We discuss progress in developing and applying PRS in non-white European populations. PRS represent a significant advance in breast cancer risk prediction and their further development will undoubtedly enhance personalisation.
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Affiliation(s)
- Eleanor Roberts
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Sacha Howell
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK; Nightingale/Prevent Breast Cancer Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, UK; Manchester Breast Centre, Manchester Cancer Research Centre, The Christie Hospital, Manchester, UK
| | - D Gareth Evans
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, UK; Division of Evolution, Infection and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK; Nightingale/Prevent Breast Cancer Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, UK; Manchester Breast Centre, Manchester Cancer Research Centre, The Christie Hospital, Manchester, UK.
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14
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Wright SJ, Eden M, Ruane H, Byers H, Evans DG, Harvie M, Howell SJ, Howell A, French D, Payne K. Estimating the Cost of 3 Risk Prediction Strategies for Potential Use in the United Kingdom National Breast Screening Program. MDM Policy Pract 2023; 8:23814683231171363. [PMID: 37152662 PMCID: PMC10161319 DOI: 10.1177/23814683231171363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 03/29/2023] [Indexed: 05/09/2023] Open
Abstract
Background Economic evaluations have suggested that risk-stratified breast cancer screening may be cost-effective but have used assumptions to estimate the cost of risk prediction. The aim of this study was to identify and quantify the resource use and associated costs required to introduce a breast cancer risk-stratification approach into the English national breast screening program. Methods A micro-costing study, conducted alongside a cohort-based prospective trial (BC-PREDICT), identified the resource use and cost per individual (£; 2021 price year) of providing a risk-stratification strategy at a woman's first mammography. Costs were calculated for 3 risk-stratification approaches: Tyrer-Cuzick survey, Tyrer-Cuzick with Volpara breast-density measurement, and Tyrer-Cuzick with Volpara breast-density measurement and testing for 142 single nucleotide polymorphisms (SNP). Costs were determined for the intervention as implemented in the trial and in the health service. Results The cost of providing the risk-stratification strategy was calculated to be £16.45 for the Tyrer-Cuzick survey approach, £21.82 for the Tyrer-Cuzick with Volpara breast-density measurement, and £102.22 for the Tyrer-Cuzick with Volpara breast-density measurement and SNP testing. Limitations This study did not use formal expert elicitation methods to synthesize estimates. Conclusion The costs of risk prediction using a survey and breast density measurement were low, but adding SNP testing substantially increases costs. Implementation issues present in the trial may also significantly increase the cost of risk prediction. Implications This is the first study to robustly estimate the cost of risk-stratification for breast cancer screening. The cost of risk prediction using questionnaires and automated breast density measurement was low, but full economic evaluations including accurate costs are required to provide evidence of the cost-effectiveness of risk-stratified breast cancer screening. Highlights Economic evaluations have suggested that risk-stratified breast cancer screening may be a cost-effective use of resources in the United Kingdom.Current estimates of the cost of risk stratification are based on pragmatic assumptions.This study provides estimates of the cost of risk stratification using 3 strategies and when these strategies are implemented perfectly and imperfectly in the health system.The cost of risk stratification is relatively low unless single nucleotide polymorphisms are included in the strategy.
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Affiliation(s)
- Stuart J. Wright
- Manchester Centre for Health Economics, Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, The University of Manchester, Manchester, UK
| | - Martin Eden
- Manchester Centre for Health Economics, Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, The University of Manchester, Manchester, UK
| | - Helen Ruane
- The Prevent Breast Cancer Research Unit, The Nightingale Centre, Manchester University NHS Foundation Trust, Manchester, UK
| | - Helen Byers
- Division of Evolution and Genomic Science, The University of Manchester, Manchester, UK
- Manchester Centre of Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, UK
| | - D. Gareth Evans
- The Prevent Breast Cancer Research Unit, The Nightingale Centre, Manchester University NHS Foundation Trust, Manchester, UK
- Manchester Centre of Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, UK
- Division of Evolution and Genomic Science, The University of Manchester, Manchester, UK
- Manchester Academic Health Science Centre, Health Innovation Manchester, Manchester, UK
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, Manchester, UK
- NIHR Manchester Biomedical Research Centre, The University of Manchester and Manchester University NHS foundation trust
| | - Michelle Harvie
- The Prevent Breast Cancer Research Unit, The Nightingale Centre, Manchester University NHS Foundation Trust, Manchester, UK
- Manchester Academic Health Science Centre, Health Innovation Manchester, Manchester, UK
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, Manchester, UK
- NIHR Manchester Biomedical Research Centre, The University of Manchester and Manchester University NHS foundation trust
| | - Sacha J. Howell
- The Prevent Breast Cancer Research Unit, The Nightingale Centre, Manchester University NHS Foundation Trust, Manchester, UK
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, Manchester, UK
- NIHR Manchester Biomedical Research Centre, The University of Manchester and Manchester University NHS foundation trust
- The Christie NHS Foundation Trust, Manchester, UK
| | - Anthony Howell
- The Prevent Breast Cancer Research Unit, The Nightingale Centre, Manchester University NHS Foundation Trust, Manchester, UK
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, Manchester, UK
- NIHR Manchester Biomedical Research Centre, The University of Manchester and Manchester University NHS foundation trust
- The Christie NHS Foundation Trust, Manchester, UK
| | - David French
- NIHR Manchester Biomedical Research Centre, The University of Manchester and Manchester University NHS foundation trust
- Manchester Centre for Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Katherine Payne
- Manchester Centre for Health Economics, Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, The University of Manchester, Manchester, UK
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Taylor G, McWilliams L, Woof VG, Evans DG, French DP. What are the views of three key stakeholder groups on extending the breast screening interval for low-risk women? A secondary qualitative analysis. Health Expect 2022; 25:3287-3296. [PMID: 36305519 PMCID: PMC9700144 DOI: 10.1111/hex.13637] [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: 07/22/2022] [Revised: 10/14/2022] [Accepted: 10/16/2022] [Indexed: 11/29/2022] Open
Abstract
INTRODUCTION There is increasing interest in risk-stratified breast screening, whereby the prevention and early detection offers vary by a woman's estimated risk of breast cancer. To date, more focus has been directed towards high-risk screening pathways rather than considering women at lower risk, who may be eligible for extended screening intervals. This secondary data analysis aimed to compare the views of three key stakeholder groups on how extending screening intervals for low-risk women should be implemented and communicated as part of a national breast screening programme. METHODS Secondary data analysis of three qualitative studies exploring the views of distinct stakeholder groups was conducted. Interviews took place with 23 low-risk women (identified from the BC-Predict study) and 17 national screening figures, who were involved in policy-making and implementation. In addition, three focus groups and two interviews were conducted with 26 healthcare professionals. A multiperspective thematic analysis was conducted to identify similarities and differences between stakeholders. FINDINGS Three themes were produced: Questionable assumptions about negative consequences, highlighting how other stakeholders lack trust in how women are likely to understand extended screening intervals; Preserving the integrity of the programme, centring on decision-making and maintaining a positive reputation of breast screening and Negotiating a communication pathway highlighting communication expectations and public campaign importance. CONCLUSIONS A risk-stratified screening programme should consider how best to engage women assessed as having a low risk of breast cancer to ensure mutual trust, balance the practicality of change whilst ensuring acceptability, and carefully develop multilevel inclusive communication strategies. PATIENT AND PUBLIC CONTRIBUTION The research within this paper involved patient/public contributors throughout including study design and materials input.
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Affiliation(s)
- Grace Taylor
- School of Health Sciences, Manchester Centre of Health Psychology, Division of Psychology and Mental HealthUniversity of ManchesterManchesterUK
| | - Lorna McWilliams
- School of Health Sciences, Manchester Centre of Health Psychology, Division of Psychology and Mental HealthUniversity of ManchesterManchesterUK
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science CentreCentral Manchester University Hospitals NHS Foundation TrustManchesterUK
| | - Victoria G. Woof
- School of Health Sciences, Manchester Centre of Health Psychology, Division of Psychology and Mental HealthUniversity of ManchesterManchesterUK
| | - D. Gareth Evans
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science CentreCentral Manchester University Hospitals NHS Foundation TrustManchesterUK
- The Nightingale and Prevent Breast Cancer CentreManchester University NHS Foundation TrustManchesterUK
- Manchester Breast Centre, Manchester Cancer Research CentreUniversity of ManchesterManchesterUK
- Genomic Medicine, Division of Evolution and Genomic Sciences, St Mary's Hospital, Manchester University NHS Foundation TrustThe University of ManchesterManchesterUK
| | - David P. French
- School of Health Sciences, Manchester Centre of Health Psychology, Division of Psychology and Mental HealthUniversity of ManchesterManchesterUK
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science CentreCentral Manchester University Hospitals NHS Foundation TrustManchesterUK
- Manchester Breast Centre, Manchester Cancer Research CentreUniversity of ManchesterManchesterUK
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McWilliams L, Evans DG, Payne K, Harrison F, Howell A, Howell SJ, French DP. Implementing Risk-Stratified Breast Screening in England: An Agenda Setting Meeting. Cancers (Basel) 2022; 14:cancers14194636. [PMID: 36230559 PMCID: PMC9563640 DOI: 10.3390/cancers14194636] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 09/20/2022] [Accepted: 09/21/2022] [Indexed: 11/16/2022] Open
Abstract
It is now possible to accurately assess breast cancer risk at routine NHS Breast Screening Programme (NHSBSP) appointments, provide risk feedback and offer risk management strategies to women at higher risk. These strategies include National Institute for Health and Care Excellence (NICE) approved additional breast screening and risk-reducing medication. However, the NHSBSP invites nearly all women three-yearly, regardless of risk. In March 2022, a one-day agenda setting meeting took place in Manchester to discuss the feasibility and desirability of implementation of risk-stratified screening in the NHSBSP. Fifty-eight individuals participated (38 face-to-face, 20 virtual) with relevant expertise from academic, clinical and/or policy-making perspectives. Key findings were presented from the PROCAS2 NIHR programme grant regarding feasibility of risk-stratified screening in the NHSBSP. Participants discussed key uncertainties in seven groups, followed by a plenary session. Discussions were audio-recorded and thematically analysed to produce descriptive themes. Five themes were developed: (i) risk and health economic modelling; (ii) health inequalities and communication with women; (iii); extending screening intervals for low-risk women; (iv) integration with existing NHSBSP; and (v) potential new service models. Most attendees expected some form of risk-stratified breast screening to be implemented in England and collectively identified key issues to be resolved to facilitate this.
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Affiliation(s)
- Lorna McWilliams
- Manchester Centre for Health Psychology, Division of Psychology & Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Oxford Road, Manchester M13 9PL, UK
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester M13 9WU, UK
- Correspondence:
| | - D. Gareth Evans
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester M13 9WU, UK
- Genomic Medicine, Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, St Mary’s Hospital, Manchester University NHS Foundation Trust, Oxford Road, Manchester M13 9WL, UK
- Nightingale & Prevent Breast Cancer Research Unit, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Southmoor Road, Wythenshawe, Manchester M23 9LT, UK
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, 55 Wilmslow Road, Manchester M20 4GJ, UK
| | - Katherine Payne
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester M13 9WU, UK
- Manchester Centre for Health Economics, School of Health Sciences, Faculty of Biology Medicine and Health, University of Manchester, Oxford Road, Manchester M13 9PL, UK
| | | | - Anthony Howell
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester M13 9WU, UK
- Nightingale & Prevent Breast Cancer Research Unit, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Southmoor Road, Wythenshawe, Manchester M23 9LT, UK
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, 55 Wilmslow Road, Manchester M20 4GJ, UK
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine & Health, University of Manchester, Oxford Road, Manchester M13 9PL, UK
| | - Sacha J. Howell
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester M13 9WU, UK
- Nightingale & Prevent Breast Cancer Research Unit, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Southmoor Road, Wythenshawe, Manchester M23 9LT, UK
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, 55 Wilmslow Road, Manchester M20 4GJ, UK
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine & Health, University of Manchester, Oxford Road, Manchester M13 9PL, UK
| | - David P. French
- Manchester Centre for Health Psychology, Division of Psychology & Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Oxford Road, Manchester M13 9PL, UK
- NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester M13 9WU, UK
- Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, 55 Wilmslow Road, Manchester M20 4GJ, UK
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Polygenic risk scores: improving the prediction of future disease or added complexity? Br J Gen Pract 2022; 72:396-398. [PMID: 35902257 PMCID: PMC9343049 DOI: 10.3399/bjgp22x720437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
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