Literature DB >> 11900216

Model-based predictions of BRCA1/2 mutation status in breast carcinoma patients treated at an academic medical center.

Kristen M Shannon1, Marcie L Lubratovich, Dianne M Finkelstein, Barbara L Smith, Simon N Powell, Michael V Seiden.   

Abstract

BACKGROUND: Women with an existing breast carcinoma diagnosis who are found to carry a BRCA1/2 mutation have a substantial risk of developing both a contralateral breast carcinoma and ovarian carcinoma. In a newly diagnosed breast carcinoma patient, this genetic information may influence the management of her disease. To assess the volume of patients who may need genetic services at the time of diagnosis, the authors determined the proportion of women with newly diagnosed breast carcinoma at the study institution who would be eligible for genetic testing.
METHODS: Fifty consecutive women with new breast carcinoma who were attending a multidisciplinary clinic were interviewed. Detailed, three-generation pedigrees were collected for each patient by a genetic counselor. Three commonly used probability models were used to calculate each woman's predicted risk of harboring a germline BRCA1/2 mutation.
RESULTS: Eleven of 50 patients (22% [95% confidence interval, 12-36%]) were calculated to have a > or = 10% probability of carrying a BRCA1/2 mutation by at least one mathematic model and should have been offered genetic counseling that included the discussion of genetic testing. There were considerable discrepancies between probability calculations among the three mathematic models. One of the 11 patients who was eligible for genetic testing pursued genetic counseling within 12 months of diagnosis.
CONCLUSIONS: At a large academic medical center, a substantial proportion of unselected women attending a multidisciplinary clinic were found to have a > or = 10% risk of carrying a BRCA1/2 mutation. The actual number of patients eligible to receive BRCA1/2 genetic testing outweighs the number of patients seen for genetic counseling at the study institution. Finally, limited correlation was found between current predictive models.

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Year:  2002        PMID: 11900216     DOI: 10.1002/cncr.10223

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  7 in total

1.  A new scoring system for the chances of identifying a BRCA1/2 mutation outperforms existing models including BRCAPRO.

Authors:  D G R Evans; D M Eccles; N Rahman; K Young; M Bulman; E Amir; A Shenton; A Howell; F Lalloo
Journal:  J Med Genet       Date:  2004-06       Impact factor: 6.318

2.  Exploring hereditary cancer among dying cancer patients--a cross-sectional study of hereditary risk and perceived awareness of DNA testing and banking.

Authors:  John Martin Quillin; Joann N Bodurtha; Laura A Siminoff; Thomas J Smith
Journal:  J Genet Couns       Date:  2010-08-03       Impact factor: 2.537

Review 3.  The contribution of breast cancer pathology to statistical models to predict mutation risk in BRCA carriers.

Authors:  Ana Cristina Vargas; Leonard Da Silva; Sunil R Lakhani
Journal:  Fam Cancer       Date:  2010-12       Impact factor: 2.375

4.  Automatic Genetic Risk Assessment Calculation Using Breast Cancer Family History Data from the EHR compared to Self-Report.

Authors:  Margaret Sin; Julia E McGuinness; Meghna S Trivedi; Alejandro Vanegas; Thomas B Silverman; Katherine D Crew; Rita Kukafka
Journal:  AMIA Annu Symp Proc       Date:  2018-12-05

Review 5.  Breast cancer risk-assessment models.

Authors:  D Gareth R Evans; Anthony Howell
Journal:  Breast Cancer Res       Date:  2007       Impact factor: 6.466

6.  Establishing a program for individuals at high risk for breast cancer.

Authors:  Fernando Cadiz; Henry M Kuerer; Julio Puga; Jamile Camacho; Eduardo Cunill; Banu Arun
Journal:  J Cancer       Date:  2013-07-01       Impact factor: 4.207

7.  A method to assess the clinical significance of unclassified variants in the BRCA1 and BRCA2 genes based on cancer family history.

Authors:  Encarna B Gómez García; Jan C Oosterwijk; Maarten Timmermans; Christi J van Asperen; Frans B L Hogervorst; Nicoline Hoogerbrugge; Rogier Oldenburg; Senno Verhoef; Charlotte J Dommering; Margreet G E M Ausems; Theo A M van Os; Annemarie H van der Hout; Marjolijn Ligtenberg; Ans van den Ouweland; Rob B van der Luijt; Juul T Wijnen; Jan J P Gille; Patrick J Lindsey; Peter Devilee; Marinus J Blok; Maaike P G Vreeswijk
Journal:  Breast Cancer Res       Date:  2009-02-06       Impact factor: 6.466

  7 in total

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