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Personalised Risk Prediction in Hereditary Breast and Ovarian Cancer: A Protocol for a Multi-Centre Randomised Controlled Trial.
Archer, Stephanie; Fennell, Nichola; Colvin, Ellen; Laquindanum, Rozelle; Mills, Meredith; Dennis, Romy; Stutzin Donoso, Francisca; Gold, Rochelle; Fan, Alice; Downes, Kate; Ford, James; Antoniou, Antonis C; Kurian, Allison W; Evans, D Gareth; Tischkowitz, Marc.
Afiliación
  • Archer S; Primary Care Unit, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, Cambridge CB1 8RN, UK.
  • Fennell N; Department of Psychology, University of Cambridge, Downing Street, Cambridge CB2 3EB, UK.
  • Colvin E; Academic Department of Medical Genetics, University of Cambridge, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK.
  • Laquindanum R; Manchester Centre for Genomic Medicine, St. Marys Hospital, Oxford Road, Manchester M13 9WL, UK.
  • Mills M; Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Dennis R; Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Stutzin Donoso F; Academic Department of Medical Genetics, University of Cambridge, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK.
  • Gold R; Primary Care Unit, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, Cambridge CB1 8RN, UK.
  • Fan A; Academic Department of Medical Genetics, University of Cambridge, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK.
  • Downes K; Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Ford J; Cambridge Genomics Laboratory, Cambridge University Hospitals Foundation Trust, Hills Road, Cambridge CB2 0QQ, UK.
  • Antoniou AC; Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Kurian AW; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Evans DG; Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, Cambridge CB1 8RN, UK.
  • Tischkowitz M; Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
Cancers (Basel) ; 14(11)2022 May 31.
Article en En | MEDLINE | ID: mdl-35681696
ABSTRACT
Women who test positive for an inherited pathogenic/likely pathogenic gene variant in BRCA1, BRCA2, PALB2, CHEK2 and ATM are at an increased risk of developing certain types of cancer-specifically breast (all) and epithelial ovarian cancer (only BRCA1, BRCA2, PALB2). Women receive broad cancer risk figures that are not personalised (e.g., 44-63% lifetime risk of breast cancer for those with PALB2). Broad, non-personalised risk estimates may be problematic for women when they are considering how to manage their risk. Multifactorial-risk-prediction tools have the potential to deliver personalised risk estimates. These may be useful in the patient's decision-making process and impact uptake of risk-management options. This randomised control trial (registration number to follow), based in genetic centres in the UK and US, will randomise participants on a 11 basis to either receive conventional cancer risk estimates, as per routine clinical practice, or to receive a personalised risk estimate. This personalised risk estimate will be calculated using the CanRisk risk prediction tool, which combines the patient's genetic result, family history and polygenic risk score (PRS), along with hormonal and lifestyle factors. Women's decision-making around risk management will be monitored using questionnaires, completed at baseline (pre-appointment) and follow-up (one, three and twelve months after receiving their risk assessment). The primary outcome for this study is the type and timing of risk management options (surveillance, chemoprevention, surgery) taken up over the course of the study (i.e., 12 months). The type of risk-management options planned to be taken up in the future (i.e., beyond the end of the study) and the potential impact of personalised risk estimates on women's psychosocial health will be collected as secondary-outcome measures. This study will also assess the acceptability, feasibility and cost-effectiveness of using personalised risk estimates in clinical care.
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Clinical_trials / Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Cancers (Basel) Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Clinical_trials / Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Cancers (Basel) Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido