ReviewFamilial cancer2010
The contribution of breast cancer pathology to statistical models to predict mutation risk in BRCA carriers.
Review in Familial cancer, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 24 citations in OpenAlex.
- Single-Cell Analysis in the Mouse and Human Mammary Gland.Advances in experimental medicine and biology · 2025Review
- Globally RareFrontiers in oncology · 2020Article
- Histopathological Features of Non-Neoplastic Breast Parenchyma Do Not Predict BRCA Mutation Status of Patients with Invasive Breast Cancer.Biomarkers in cancer · 2015Article
- 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
- Large deletion causing von Hippel-Lindau disease and hereditary breast cancer syndrome.Hereditary cancer in clinical practice · 2014Article
- Limited significance of family history for presence of BRCA1 gene mutation in Polish breast and ovarian cancer cases.Familial cancer · 2012Article
- 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 epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2012Article
- BRCA1/2 mutations and triple negative breast cancers.Breast disease · 2010Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BRCA1 and BRCA2 associated breast cancer comprises a small but important group of hereditary breast cancer. Testing for BRCA1 and BRCA2 has significant clinical and personal implications for the patients in terms of therapy and follow-up of individual family members. The sequencing of the genes is expensive and since the information derived may have a profound effect on the individual and family members, it is important that testing is done only when the risk of carrying a mutation is thought to be high. Over the last decade, researchers have developed a number of statistical models for predicting risk for harboring mutations in these genes and the risk of subsequently developing breast and ovarian cancer. These models usually take into account the type of tumor and age at occurrence as well as family history. Data from pathological analysis show that although breast tumours are heterogeneous, there are histological characteristics that are seen more frequently in carriers of BRCA1 germ line mutations compared to BRCA2 and sporadic breast cancers. A number of authors have suggested that the addition of pathological data to risk algorithms may improve the predictive power of these models and provide a more accurate way of identifying individuals who may benefit from testing. Here we review the pathology of familial breast cancer and assess the evidence to justify the use of pathology in refining risk assessment models.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.