CanRisk Tool-A Web Interface for the Prediction of Breast and Ovarian Cancer Risk and the Likelihood of Carrying Genetic Pathogenic Variants.


Journal

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology
ISSN: 1538-7755
Titre abrégé: Cancer Epidemiol Biomarkers Prev
Pays: United States
ID NLM: 9200608

Informations de publication

Date de publication:
03 2021
Historique:
received: 07 09 2020
revised: 08 10 2020
accepted: 14 12 2020
pubmed: 19 12 2020
medline: 3 2 2022
entrez: 18 12 2020
Statut: ppublish

Résumé

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. 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. 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. 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. 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.

Sections du résumé

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.

Identifiants

pubmed: 33335023
pii: 1055-9965.EPI-20-1319
doi: 10.1158/1055-9965.EPI-20-1319
pmc: PMC7611188
mid: EMS128678
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

469-473

Subventions

Organisme : Wellcome Trust
ID : 203477/Z/16/Z
Pays : United Kingdom
Organisme : Cancer Research UK
ID : C8640/A23385
Pays : United Kingdom
Organisme : Cancer Research UK
ID : A20861
Pays : United Kingdom
Organisme : CIHR
ID : GPH-129344
Pays : Canada
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Cancer Research UK
ID : A16563
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 203477
Pays : United Kingdom

Informations de copyright

©2020 American Association for Cancer Research.

Références

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Auteurs

Tim Carver (T)

Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom. tjc29@medschl.cam.ac.uk.

Simon Hartley (S)

Centre for Computational Biology, University of Birmingham, Birmingham, United Kingdom.

Andrew Lee (A)

Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.

Alex P Cunningham (AP)

Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.

Stephanie Archer (S)

Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.

Chantal Babb de Villiers (C)

Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.

Jonathan Roberts (J)

East Anglian Medical Genetics Service, Cambridge Biomedical Campus, Addenbrooke's Hospital, Cambridge, United Kingdom.

Rod Ruston (R)

Priory Analysts, Milton Keynes, United Kingdom.

Fiona M Walter (FM)

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 (M)

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 (DF)

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 (AC)

Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.

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Classifications MeSH