ArticleBreast cancer research : BCR2010
Incorporating tumour pathology information into breast cancer risk prediction algorithms.
Article in Breast cancer research : BCR, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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Who cites it
40 citing papers in PubMed.
- Adapting the BOADICEA breast and ovarian cancer risk models for the ethnically diverse UK population.British journal of cancer · 2025Article
- Exploring the promoter regions of cancer predisposition genes in patients with triple-negative breast cancer reveals the presence of rare germline variants.The oncologist · 2025Article
- [BRCA1 Gene's Mutations And Hereditary Breast Cancer: Genetic, Biological, And Clinical Aspects].Le Mali medical · 2025Review
- Validation of the BOADICEA model for predicting the likelihood of carrying pathogenic variants in eight breast and ovarian cancer susceptibility genes.Scientific reports · 2023Article
- Article
- Enhancing the BOADICEA cancer risk prediction model to incorporate new data onJournal of medical genetics · 2022Article
- Patient and provider perspectives on polygenic risk scores: implications for clinical reporting and utilization.Genome medicine · 2022Article
- Feasibility of personalized screening and prevention recommendations in the general population through breast cancer risk assessment: results from a dedicated risk clinic.Breast cancer research and treatment · 2022Article
- Personalized Risk-Based Screening Design for Comparative Two-Arm Group Sequential Clinical Trials.Journal of personalized medicine · 2022Article
- DrABC: deep learning accurately predicts germline pathogenic mutation status in breast cancer patients based on phenotype data.Genome medicine · 2022Article
- Risk factors for breast cancer development by tumor characteristics among women with benign breast disease.Breast cancer research : BCR · 2021Article
- Non-Coding Variants inCancers · 2018Review
- Risk algorithms that include pathology adjustment for HER2 amplification need to make further downward adjustments in likelihood scores.Familial cancer · 2017Article
- Association of breast adipose tissue levels of polychlorinated biphenyls and breast cancer development in women from Chaoshan, China.Environmental science and pollution research international · 2017Article
- Article
- Recommendations on breast cancer screening and prevention in the context of implementing risk stratification: impending changes to current policies.Current oncology (Toronto, Ont.) · 2016Article
- Incorporating truncating variants in PALB2, CHEK2, and ATM into the BOADICEA breast cancer risk model.Genetics in medicine : official journal of the American College of Medical Genetics · 2016Article
- Population-based screening for cancer: hope and hype.Nature reviews. Clinical oncology · 2016Review
- KOHBRA BRCA risk calculator (KOHCal): a model for predicting BRCA1 and BRCA2 mutations in Korean breast cancer patients.Journal of human genetics · 2016Article
- Refined histopathological predictors of BRCA1 and BRCA2 mutation status: a large-scale analysis of breast cancer characteristics from the BCAC, CIMBA, and ENIGMA consortia.Breast cancer research : BCR · 2014Article
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5 authors.
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Abstract
introductionMutations in BRCA1 and BRCA2 confer high risks of breast cancer and ovarian cancer. The risk prediction algorithm BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) may be used to compute the probabilities of carrying mutations in BRCA1 and BRCA2 and help to target mutation screening. Tumours from BRCA1 and BRCA2 mutation carriers display distinctive pathological features that could be used to better discriminate between BRCA1 mutation carriers, BRCA2 mutation carriers and noncarriers. In particular, oestrogen receptor (ER)-negative status, triple-negative (TN) status, and expression of basal markers are predictive of BRCA1 mutation carrier status.
methodsWe extended BOADICEA by treating breast cancer subtypes as distinct disease end points. Age-specific expression of phenotypic markers in a series of tumours from 182 BRCA1 mutation carriers, 62 BRCA2 mutation carriers and 109 controls from the Breast Cancer Linkage Consortium, and over 300,000 tumours from the general population obtained from the Surveillance Epidemiology, and End Results database, were used to calculate age-specific and genotype-specific incidences of each disease end point. The probability that an individual carries a BRCA1 or BRCA2 mutation given their family history and tumour marker status of family members was computed in sample pedigrees.
resultsThe cumulative risk of ER-negative breast cancer by age 70 for BRCA1 mutation carriers was estimated to be 55% and the risk of ER-positive disease was 18%. The corresponding risks for BRCA2 mutation carriers were 21% and 44% for ER-negative and ER-positive disease, respectively. The predicted BRCA1 carrier probabilities among ER-positive breast cancer cases were less than 1% at all ages. For women diagnosed with breast cancer below age 50 years, these probabilities rose to more than 5% in ER-negative breast cancer, 7% in TN disease and 24% in TN breast cancer expressing both CK5/6 and CK14 cytokeratins. Large differences in mutation probabilities were observed by combining ER status and other informative markers with family history.
conclusionsThis approach combines both full pedigree and tumour subtype data to predict BRCA1/2 carrier probabilities. Prediction of BRCA1/2 carrier status, and hence selection of women for mutation screening, may be substantially improved by combining tumour pathology with family history of cancer.
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