CanRisk Tool

The CanRisk tool is a web interface to BOADICEA, the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm, risk prediction model used to calculate future breast and ovarian cancer risks in women. This is the first comprehensive model that allows for reliable breast cancer risk prediction in unaffected women on the basis of mutation screening information for rare (high risk and moderate risk) breast cancer genetic susceptibility variants, common cancer genetic susceptibility variants (using polygenic risk scores), explicit family history, personal lifestyle, hormonal and reproductive risk factors, and mammographic density. This model is described in Lee et al. 2019.

The ovarian cancer risks are calculated using a separate prediction model that is based on the BOADICEA methodology, and extensions of the ovarian cancer risk model described by Jervis et al. The model includes the effects of rare pathogenic variants BRCA1, BRCA2, RAD51D, RAD51C and BRIP1. It also can use polygenic risk scores, explicit family history, personal lifestyle/hormonal/reproductive risk factors. For details see 'What information do the breast and ovarian cancer models use to determine risks?'

This work is supported by grants through Cancer Research UK, the European Union’s Horizon 2020 and Innovation programme, Genome Canada and a Wellcome Trust Collaborative Award.

Please see more details here on the Cancer Research-UK funded CanRisk programme.

The CanRisk Tool carries the CE marking and has been created and maintained by the University of Cambridge.

How to Cite CanRisk

If you use the CanRisk tool or web-services then we ask that you cite Lee et al. (Genet Med, 2019), Carver et al. (Cancer Epidemiol Biomarkers Prev, 2020) and Archer et al. (PLoS One 2020) in any resulting work or publications. We would be grateful if you could please also acknowledge the funding that supports the running of CanRisk by including the following acknowledgement: The CanRisk tool is supported by grant PPRPGM-Nov20\100002 from Cancer Research UK.

If you use the CanRisk web-services in a third party application then we ask that you acknowledge this on the application and link to the CanRisk home page (canrisk.org). To allow us to manage resources, we also ask that you inform us of expected usage (number of calculations) and the user account that calculations will be run from.

CanRisk Team

Team Leaders

Development team at the Department of Public Health and Primary Care, University of Cambridge

Clinical Advisor

Alumni

Acknowledgments

The CanRisk team are grateful to the following for their assistance in reviewing the language translations of the tool.

Spanish:
  • Miguel de la Hoya
  • Judith Balmaña
  • Adrià López Fernández

French:
  • Penny Soucy
  • Jacques Simard
  • Antoine De Pauw

German:
  • Karin Kast
  • Anne Quante

Dutch:
  • Daoud Ait Moha
  • Lizet van der Kolk

Portuguese:
  • Rodrigo Guindalini
  • Maria Isabel Achatz

Italian:
  • Valeria Viassolo
  • Liliana Varesco

Publications