About CanRisk
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 and ovarian cancer risk prediction in unaffected women on the basis of mutation screening information for rare (high risk and moderate risk) breast and ovarian 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 in the case of breast cancer. The breast and ovarian cancer models are described in Lee et al. 2019, Lee et al 2021 and Lee et al 2022.
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
Department of Medical Genetics and National Institute for Health Research,
University of Cambridge
Development team at the Department of Public Health and Primary Care, University of Cambridge
Assistant Professor and Senior Research Associate
Research Associate
Program and Regulatory Affairs Manager
Lead Web Developer
Clinical Advisor
Alumni
Research Associate
Research Associate
Computer Programmer
Senior Software Developer/Coordinator
Acknowledgments
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
- Lee, A. J. et al. Enhancing the BOADICEA cancer risk prediction model to incorporate new data on RAD51C, RAD51D, BARD1, updates to tumour pathology and cancer incidences. J Med Genetics (2022).
- Yang, X et al. Prospective validation of the BOADICEA multifactorial breast cancer risk prediction model in a large prospective cohort study J Med Genetics (2022).
- Mavaddat, N. et al. Incorporating alternative Polygenic Risk Scores into the BOADICEA breast cancer risk prediction model. Cancer Epidemiol Biomarkers Prev (2023).
- Li, S. X. et al. Prospective Evaluation over 15 Years of Six Breast Cancer Risk Models. Cancers, 13, 5194 (2021).
- Lee, A. J. et al. A Comprehensive Epithelial Tubo-Ovarian Cancer Risk Prediction Model Incorporating Genetic and Epidemiological Risk Factors J Med Genetics (2021).
- Parichoy Pal Choudhury et al. Comparative validation of the BOADICEA and Tyrer-Cuzick breast cancer risk models incorporating classical risk factors and polygenic risk in a population-based prospective cohort of women of European ancestry. Breast Cancer Research 23, 22 (2021).
- Carver, T. et al. CanRisk Tool—A Web Interface for the Prediction of Breast and Ovarian Cancer Risk and the Likelihood of Carrying Genetic Pathogenic Variants. Cancer Epidemiol Biomarkers Prev (2020).
- Archer, S. et al. Evaluating clinician acceptability of the prototype CanRisk tool for predicting risk of breast and ovarian cancer: A multi-methods study. PLoS ONE 15, e0229999 (2020)
- Mavaddat, N. et al. Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes. The American Journal of Human Genetics 104, 21–34 (2019).
- Lee, A. et al. BOADICEA: a comprehensive breast cancer risk prediction model incorporating genetic and nongenetic risk factors. Genet Med 21, 1708–1718 (2019).
- Carver, T. et al. pedigreejs: a web-based graphical pedigree editor. Bioinformatics 34, 1069–1071 (2018).
- Lee, A. J. et al. Incorporating truncating variants in PALB2, CHEK2, and ATM into the BOADICEA breast cancer risk model. Genet. Med. 18, 1190–1198 (2016).
- Jervis, S. et al. A risk prediction algorithm for ovarian cancer incorporating BRCA1, BRCA2, common alleles and other familial effects. Journal of Medical Genetics 52, 465–475 (2015).
- Lee, A. J. et al. BOADICEA breast cancer risk prediction model: updates to cancer incidences, tumour pathology and web interface. Br. J. Cancer 110, 535–545 (2014).
- MacInnis, R. J. et al. Prospective validation of the breast cancer risk prediction model BOADICEA and a batch-mode version BOADICEACentre. British Journal of Cancer 109, 1296–1301 (2013).
- Mavaddat, N. et al. Pathology of Breast and Ovarian Cancers among BRCA1 and BRCA2 Mutation Carriers: Results from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Cancer Epidemiol Biomarkers Prev 21, 134–147 (2012).
- Cunningham, A. P., Antoniou, A. C. & Easton, D. F. Clinical software development for the Web: lessons learned from the BOADICEA project. BMC Medical Informatics and Decision Making 12, 30 (2012).
- Mavaddat, N., Rebbeck, T. R., Lakhani, S. R., Easton, D. F. & Antoniou, A. C. Incorporating tumour pathology information into breast cancer risk prediction algorithms. Breast Cancer Research 12, R28 (2010).
- Antoniou, A. C. et al. Predicting the likelihood of carrying a BRCA1 or BRCA2 mutation: validation of BOADICEA, BRCAPRO, IBIS, Myriad and the Manchester scoring system using data from UK genetics clinics. Journal of Medical Genetics 45, 425–431 (2008).
- Barcenas, C. H. et al. Assessing BRCA Carrier Probabilities in Extended Families. JCO 24, 354–360 (2006).
- Antoniou, A. C. & Easton, D. F. Risk prediction models for familial breast cancer. Future Oncol 2, 257–274 (2006).
- Antoniou, A. C. et al. BRCA1 and BRCA2 mutation predictions using the BOADICEA and BRCAPRO models and penetrance estimation in high-risk French-Canadian families. Breast Cancer Research 8, R3 (2005).
- Antoniou, A. C. et al. The BOADICEA model of genetic susceptibility to breast and ovarian cancers: updates and extensions. British Journal of Cancer 98, 1457–1466 (2008).
- Antoniou, A. C., Pharoah, P. P. D., Smith, P. & Easton, D. F. The BOADICEA model of genetic susceptibility to breast and ovarian cancer. British Journal of Cancer 91, 1580–1590 (2004).