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dc.contributor.authorLee, Andrewen
dc.contributor.authorMavaddat, Nasimen
dc.contributor.authorWilcox, Amber Nen
dc.contributor.authorCunningham, Alexen
dc.contributor.authorCarver, Timen
dc.contributor.authorHartley, Simonen
dc.contributor.authorBabb, Chantal Louizaen
dc.contributor.authorIzquierdo, Angelen
dc.contributor.authorSimard, Jacquesen
dc.contributor.authorSchmidt, Marjanka Ken
dc.contributor.authorWalter, Fionaen
dc.contributor.authorChatterjee, Nilanjanen
dc.contributor.authorGarcia-Closas, Montserraten
dc.contributor.authorTischkowitz, Marcen
dc.contributor.authorPharoah, Paulen
dc.contributor.authorEaston, Douglasen
dc.contributor.authorAntoniou, Antonisen
dc.date.accessioned2019-01-29T00:30:14Z
dc.date.available2019-01-29T00:30:14Z
dc.date.issued2019-08en
dc.identifier.issn1098-3600
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/288440
dc.description.abstractPurpose: Breast cancer (BC) risk prediction allows systematic identification of individuals at highest and lowest risk. We extend the BOADICEA risk model to incorporate the effects of Polygenic Risk Scores (PRS) and other risk factors (RFs). Methods: BOADICEA incorporates the effects of truncating variants in BRCA1, BRCA2, PALB2, CHEK2 and ATM; a PRS based on 313 SNPs explaining 20% of BC polygenic variance; a residual polygenic component accounting for other genetic/familial effects; known lifestyle/hormonal/reproductive RFs and mammographic density, while allowing for missing information. Results: Among all factors considered, the predicted UK BC risk distribution is widest for the PRS, followed by mammographic density. The highest BC risk stratification is achieved when all genetic and lifestyle/hormonal/reproductive/anthropomorphic factors are considered jointly. With all factors, the predicted lifetime risks for women in the UK population vary from 2.8% for the 1st percentile to 30.6% for the 99th. 14.7% of women are predicted to have a lifetime risk of 17%-<30% (moderate risk according to NICE guidelines) and 1.1% a lifetime risk of 30% (high risk). Conclusions: This comprehensive model should enable high levels of BC risk stratification in the general population and women with family history, and facilitate individualised, informed decision-making on prevention therapies and screening
dc.format.mediumPrint-Electronicen
dc.languageengen
dc.publisherWolters Kluwer Health
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectHumansen
dc.subjectBreast Neoplasmsen
dc.subjectOvarian Neoplasmsen
dc.subjectGenetic Predisposition to Diseaseen
dc.subjectBRCA1 Proteinen
dc.subjectBRCA2 Proteinen
dc.subjectRisk Assessmenten
dc.subjectRisk Factorsen
dc.subjectMultifactorial Inheritanceen
dc.subjectMutationen
dc.subjectPolymorphism, Single Nucleotideen
dc.subjectFemaleen
dc.subjectGenetic Testingen
dc.subjectAtaxia Telangiectasia Mutated Proteinsen
dc.subjectCheckpoint Kinase 2en
dc.subjectFanconi Anemia Complementation Group N Proteinen
dc.titleBOADICEA: a comprehensive breast cancer risk prediction model incorporating genetic and nongenetic risk factors.en
dc.typeArticle
prism.endingPage1718
prism.issueIdentifier8en
prism.publicationDate2019en
prism.publicationNameGenetics in medicine : official journal of the American College of Medical Geneticsen
prism.startingPage1708
prism.volume21en
dc.identifier.doi10.17863/CAM.35728
dcterms.dateAccepted2018-12-03en
rioxxterms.versionofrecord10.1038/s41436-018-0406-9en
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2019-08en
dc.contributor.orcidLee, Andrew [0000-0003-0677-0252]
dc.contributor.orcidMavaddat, Nasim [0000-0003-0307-055X]
dc.contributor.orcidCunningham, Alex [0000-0002-3737-9611]
dc.contributor.orcidBabb de Villiers, Chantal [0000-0003-1334-1819]
dc.contributor.orcidWalter, Fiona [0000-0002-7191-6476]
dc.contributor.orcidTischkowitz, Marc [0000-0002-7880-0628]
dc.contributor.orcidPharoah, Paul [0000-0001-8494-732X]
dc.contributor.orcidEaston, Douglas [0000-0003-2444-3247]
dc.contributor.orcidAntoniou, Antonis [0000-0001-9223-3116]
dc.identifier.eissn1530-0366
rioxxterms.typeJournal Article/Reviewen
pubs.funder-project-idCancer Research UK (20861)
pubs.funder-project-idCancer Research UK (10119)
pubs.funder-project-idMRC (MR/P012930/1)
pubs.funder-project-idEuropean Research Council (310018)
pubs.funder-project-idWellcome Trust (203477/B/16/Z)
pubs.funder-project-idEuropean Commission Horizon 2020 (H2020) Societal Challenges (634935)
pubs.funder-project-idEuropean Commission Horizon 2020 (H2020) Societal Challenges (633784)
pubs.funder-project-idCancer Research UK (CRUK-A16563)


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Attribution-NonCommercial-NoDerivatives 4.0 International
Except where otherwise noted, this item's licence is described as Attribution-NonCommercial-NoDerivatives 4.0 International