Enhancing the BOADICEA cancer risk prediction model to incorporate new data on RAD51C, RAD51D, BARD1, updates to tumour pathology and cancer incidences.

Abstract

BackgroundBOADICEA for breast cancer and the epithelial ovarian cancer (EOC) models included in the CanRisk tool (www.canrisk.org) provide future cancer risks based on rare pathogenic variants in cancer-susceptibility genes, polygenic risk scores, breast-density, questionnaire-based risk factors and family history. Here, we extend the models to include the effects of pathogenic variants in recently established breast cancer and EOC susceptibility genes, up-to-date age-specific pathology distributions and continuous risk factors. MethodsBOADICEA was extended to further incorporate the associations of pathogenic variants in BARD1, RAD51C and RAD51D with breast cancer risk. The EOC model was extended to include the association of PALB2 pathogenic variants with EOC risk. Age-specific distributions of oestrogen-receptor-negative and triple-negative breast cancer status for pathogenic variant carriers in these genes and CHEK2 and ATM were also incorporated. A novel method to include continuous risk factors was developed, exemplified by including adult-height as continuous. ResultsBARD1, RAD51C and RAD51D explain 0.31% of the breast cancer polygenic variance. When incorporated into the multifactorial model, 34-44% of these carriers would be reclassified to the near-population and 15-22% to the high-risk categories based on the UK NICE guidelines. Including height as continuous, increased the BC relative-risk variance from 0.002 to 0.010. ConclusionsThese extensions will allow for better personalised risks for BARD1, RAD51C, RAD51D and PALB2 pathogenic variant carriers and more informed choices on screening, prevention, risk factor modification or other risk-reducing options.