The BOADICEA model of genetic susceptibility to breast and ovarian cancers: updates and extensions

Antonis C. Antoniou(University of Cambridge), Alex Cunningham(University of Cambridge), Julian Peto(Institute of Cancer Research), D. Gareth Evans(St Mary's Hospital), Fiona Lalloo(St Mary's Hospital), Steven A. Narod(University of Toronto), Harvey A. Risch(Yale University), Jórunn E. Eyfjörd(University of Iceland), John L. Hopper(The University of Melbourne), Melissa C. Southey(The University of Melbourne), Håkan Olsson(Lund University), Oskar T. Johannsson(Lund University), Åke Borg(Lund University), B Passini(Fondazione IRCCS Istituto Nazionale dei Tumori), Paolo Radice(IFOM), Siranoush Manoukian(Fondazione IRCCS Istituto Nazionale dei Tumori), Diana Eccles(Princess Anne Hospital), Nelson L.S. Tang(Chinese University of Hong Kong), Edith Oláh(National Institute of Oncology), Hoda Anton‐Culver(University of California, Irvine), Ellen Warner(University of Toronto), Jan Lubiński(International Hereditary Cancer Center), Jacek Gronwald(International Hereditary Cancer Center), Bohdan Górski(International Hereditary Cancer Center), Laufey Tryggvadóttír(University of Iceland), Kirsi Syrjäkoski(Tampere University Hospital), O-P Kallioniemi(Tampere University Hospital), Hannaleena Eerola(Helsinki University Hospital), Heli Nevanlinna(Helsinki University Hospital), Paul D.P. Pharoah(University of Cambridge), Douglas F. Easton(University of Cambridge)
British Journal of Cancer
March 18, 2008
Cited by 534Open Access
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Abstract

Multiple genetic loci confer susceptibility to breast and ovarian cancers. We have previously developed a model (BOADICEA) under which susceptibility to breast cancer is explained by mutations in BRCA1 and BRCA2, as well as by the joint multiplicative effects of many genes (polygenic component). We have now updated BOADICEA using additional family data from two UK population-based studies of breast cancer and family data from BRCA1 and BRCA2 carriers identified by 22 population-based studies of breast or ovarian cancer. The combined data set includes 2785 families (301 BRCA1 positive and 236 BRCA2 positive). Incidences were smoothed using locally weighted regression techniques to avoid large variations between adjacent intervals. A birth cohort effect on the cancer risks was implemented, whereby each individual was assumed to develop cancer according to calendar period-specific incidences. The fitted model predicts that the average breast cancer risks in carriers increase in more recent birth cohorts. For example, the average cumulative breast cancer risk to age 70 years among BRCA1 carriers is 50% for women born in 1920-1929 and 58% among women born after 1950. The model was further extended to take into account the risks of male breast, prostate and pancreatic cancer, and to allow for the risk of multiple cancers. BOADICEA can be used to predict carrier probabilities and cancer risks to individuals with any family history, and has been implemented in a user-friendly Web-based program (http://www.srl.cam.ac.uk/genepi/boadicea/boadicea_home.html).


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