The most recent version of BOADICEA combines genetic (e.g. There has been a growing focus on the development of multi-factorial cancer risk prediction algorithms, such as the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA ). In order to maximise opportunities to both prevent and detect cancer early, there is a need to identify people at higher risk, who may benefit from tailored screening and prevention. The other authors declare no conflicts of interest. This does not alter our adherence to PLOS ONE policies on sharing data and materials. These authors may receive royalties in the future if commercialization is realized. Fiona Walter is Director of the multi-institutional CanTest Collaborative which is funded by Cancer Research UK (C8640/A23385).Ĭompeting interests: The BOADICEA model has been licensed to Cambridge Enterprise for commercialization, with the authors D.F.E., A.C.A., A.P.C., A.L. Marc Tischkowitz acknowledges funding from the European Research Council and Cambridge NIHR Biomedical Research Centre.

Jon Emery is funded by an Australian National Health Medical Research Council practitioner fellowship. Anonymised transcripts (CanRisk Phase 1) are available from the Cancer Group at the Primary Care Unit, University of Cambridge,, for researchers who meet the criteria for access to confidential data.įunding: This work was supported by Cancer Research UK grants C12292/A20861 the European Union’s Horizon 2020 research and innovation programme under grant agreement numbers 633784 (B-CAST) and 634935 (BRIDGES) a Wellcome Trust Collaborative Award (203477/B/16/Z) and the PERSPECTIVE programme: The Government of Canada through Genome Canada and the Canadian Institutes of Health Research (grant GPH-129344). This restriction is reinforced by the University of Cambridge and additional approval by the Health Research Authority. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: Data cannot be shared publicly because of the possibility of identifying individuals based on the content of the interview transcripts. Received: DecemAccepted: FebruPublished: March 6, 2020Ĭopyright: © 2020 Archer et al.

(2020) Evaluating clinician acceptability of the prototype CanRisk tool for predicting risk of breast and ovarian cancer: A multi-methods study. Citation: Archer S, Babb de Villiers C, Scheibl F, Carver T, Hartley S, Lee A, et al.

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