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

Research output: Contribution to journalArticlepeer-review


  • Tim Carver
  • Andrew Lee
  • Alex P. Cunningham
  • Stephanie Archer
  • Chantal Babb de Villiers
  • Rod Ruston
  • Fiona M. Walter
  • Marc Tischkowitz
  • Douglas F. Easton
  • Antonis C. Antoniou


Background: The CanRisk Tool ( 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.


Original languageEnglish
JournalCancer Epidemiology, Biomarkers & Prevention
Publication statusPublished - 18 Dec 2020

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