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A probability model for predicting BRCA1 and BRCA2 mutations in breast and breast-ovarian cancer families
Germline mutations in BRCA1 and BRCA2 genes predispose to hereditary breast and ovarian cancer. Our aim was to find associations between the clinical characteristics and positive mutation status in 148 breast cancer families in order to predict the probability of finding a BRCA mutation in a family....
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
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Nature Publishing Group
2001
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2363799/ https://www.ncbi.nlm.nih.gov/pubmed/11237395 http://dx.doi.org/10.1054/bjoc.2000.1626 |
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author | Vahteristo, P Eerola, H Tamminen, A Blomqvist, C Nevanlinna, H |
author_facet | Vahteristo, P Eerola, H Tamminen, A Blomqvist, C Nevanlinna, H |
author_sort | Vahteristo, P |
collection | PubMed |
description | Germline mutations in BRCA1 and BRCA2 genes predispose to hereditary breast and ovarian cancer. Our aim was to find associations between the clinical characteristics and positive mutation status in 148 breast cancer families in order to predict the probability of finding a BRCA mutation in a family. Several factors were associated with mutations in univariate analysis, whereas in multivariate analysis (logistic regression with backward selection) only the age of the youngest breast cancer patient and the number of ovarian cancer cases in a family were independent predictors of BRCA mutations. A logistic model was devised to estimate the probability for a family of harbouring a mutation in either BRCA1 or BRCA2. Altogether, 63 out of 148 families (43%) and 28 out of 29 (97%) mutation carrier families obtained probabilities over 10%. The mean probability was 55% for mutation-positive families and 11% for mutation-negative families. The models by Couch et al (1997) and Shattuck-Eidens et al (1997) previously designed for BRCA1 were also tested for their applicability to distinguish carrier families with mutations in either gene. The probability model should be a useful tool in genetic counselling and focusing the mutation analyses, and thus increasing also the cost-effectiveness of the genetic screening. © 2001 Cancer Research Campaign http://www.bjcancer.com |
format | Text |
id | pubmed-2363799 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2001 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-23637992009-09-10 A probability model for predicting BRCA1 and BRCA2 mutations in breast and breast-ovarian cancer families Vahteristo, P Eerola, H Tamminen, A Blomqvist, C Nevanlinna, H Br J Cancer Regular Article Germline mutations in BRCA1 and BRCA2 genes predispose to hereditary breast and ovarian cancer. Our aim was to find associations between the clinical characteristics and positive mutation status in 148 breast cancer families in order to predict the probability of finding a BRCA mutation in a family. Several factors were associated with mutations in univariate analysis, whereas in multivariate analysis (logistic regression with backward selection) only the age of the youngest breast cancer patient and the number of ovarian cancer cases in a family were independent predictors of BRCA mutations. A logistic model was devised to estimate the probability for a family of harbouring a mutation in either BRCA1 or BRCA2. Altogether, 63 out of 148 families (43%) and 28 out of 29 (97%) mutation carrier families obtained probabilities over 10%. The mean probability was 55% for mutation-positive families and 11% for mutation-negative families. The models by Couch et al (1997) and Shattuck-Eidens et al (1997) previously designed for BRCA1 were also tested for their applicability to distinguish carrier families with mutations in either gene. The probability model should be a useful tool in genetic counselling and focusing the mutation analyses, and thus increasing also the cost-effectiveness of the genetic screening. © 2001 Cancer Research Campaign http://www.bjcancer.com Nature Publishing Group 2001-03 /pmc/articles/PMC2363799/ /pubmed/11237395 http://dx.doi.org/10.1054/bjoc.2000.1626 Text en Copyright © 2001 Cancer Research Campaign https://creativecommons.org/licenses/by/4.0/This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material.If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Regular Article Vahteristo, P Eerola, H Tamminen, A Blomqvist, C Nevanlinna, H A probability model for predicting BRCA1 and BRCA2 mutations in breast and breast-ovarian cancer families |
title | A probability model for predicting BRCA1 and BRCA2 mutations in breast and breast-ovarian cancer families |
title_full | A probability model for predicting BRCA1 and BRCA2 mutations in breast and breast-ovarian cancer families |
title_fullStr | A probability model for predicting BRCA1 and BRCA2 mutations in breast and breast-ovarian cancer families |
title_full_unstemmed | A probability model for predicting BRCA1 and BRCA2 mutations in breast and breast-ovarian cancer families |
title_short | A probability model for predicting BRCA1 and BRCA2 mutations in breast and breast-ovarian cancer families |
title_sort | probability model for predicting brca1 and brca2 mutations in breast and breast-ovarian cancer families |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2363799/ https://www.ncbi.nlm.nih.gov/pubmed/11237395 http://dx.doi.org/10.1054/bjoc.2000.1626 |
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