Literature DB >> 27928164

Comparison between CaGene 5.1 and 6.0 for BRCA1/2 mutation prediction: a retrospective study of 150 BRCA1/2 genetic tests in 517 families with breast/ovarian cancer.

Ivana Antonucci1, Martina Provenzano1, Luca Sorino1, Michela Balsamo2, Gitana Maria Aceto3,4, Pasquale Battista3,4, David Euhus5, Ettore Cianchetti6, Patrizia Ballerini7, Clara Natoli3, Giandomenico Palka3, Liborio Stuppia1,4.   

Abstract

During the past years, several empirical and statistical models have been developed to discriminate between carriers and non-carriers of germline BRCA1/BRCA2 (breast cancer 1, early onset/breast cancer 2, early onset) mutations in families with hereditary breast or ovarian cancer. Among these, the BRCAPRO or CaGene model is commonly used during genetic counseling, and plays a central role in the identification of potential carriers of BRCA1/2 mutations. We compared performance and clinical applicability of BRCAPRO version 5.1 vs version 6.0 in order to assess diagnostic accuracy of updated version. The study was carried out on 517 pedigrees of patients with familial history of breast or ovarian cancer, 150 of which were submitted to BRCA1/2 mutation screening, according to BRCAPRO evaluation or to criteria based on familial history. In our study, CaGene 5.1 was more sensitive than CaGene 6.0, although the latter showed a higher specificity. Both BRCAPRO versions better discriminate BRCA1 than BRCA2 mutations. This study evidenced similar performances in the two BRCAPRO versions even if the CaGene 6.0 has underestimated the genetic risk prediction in some BRCA mutation-positive families. Genetic counselors should recognize this limitation and during genetic counseling would be advisable to use a set of criteria in order to improve mutation carrier prediction.

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Year:  2016        PMID: 27928164     DOI: 10.1038/jhg.2016.138

Source DB:  PubMed          Journal:  J Hum Genet        ISSN: 1434-5161            Impact factor:   3.172


  45 in total

1.  Validation of three BRCA1/2 mutation-carrier probability models Myriad, BRCAPRO and BOADICEA in a population-based series of 183 German families.

Authors:  S M Schneegans; A Rosenberger; U Engel; M Sander; G Emons; M Shoukier
Journal:  Fam Cancer       Date:  2012-06       Impact factor: 2.375

2.  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

3.  Evaluation of widely used models for predicting BRCA1 and BRCA2 mutations.

Authors:  F Marroni; P Aretini; E D'Andrea; M A Caligo; L Cortesi; A Viel; E Ricevuto; M Montagna; G Cipollini; S Ferrari; M Santarosa; R Bisegna; J E Bailey-Wilson; G Bevilacqua; G Parmigiani; S Presciuttini
Journal:  J Med Genet       Date:  2004-04       Impact factor: 6.318

4.  Assessing the added value of breast tumor markers in genetic risk prediction model BRCAPRO.

Authors:  Swati Biswas; Neelam Tankhiwale; Amanda Blackford; Angelica M Gutierrez Barrera; Kaylene Ready; Karen Lu; Christopher I Amos; Giovanni Parmigiani; Banu Arun
Journal:  Breast Cancer Res Treat       Date:  2012-01-21       Impact factor: 4.872

5.  Breast cancer risks for BRCA1/2 carriers.

Authors:  Sholom Wacholder; Jeffery P Struewing; Patricia Hartge; Mark H Greene; Margaret A Tucker
Journal:  Science       Date:  2004-12-24       Impact factor: 47.728

Review 6.  Application of breast cancer risk prediction models in clinical practice.

Authors:  Susan M Domchek; Andrea Eisen; Kathleen Calzone; Jill Stopfer; Anne Blackwood; Barbara L Weber
Journal:  J Clin Oncol       Date:  2003-02-15       Impact factor: 44.544

7.  Optimal selection of individuals for BRCA mutation testing: a comparison of available methods.

Authors:  Paul A James; Rebecca Doherty; Marion Harris; Bickol N Mukesh; Alvin Milner; Mary-Anne Young; Clare Scott
Journal:  J Clin Oncol       Date:  2006-02-01       Impact factor: 44.544

8.  American Society of Clinical Oncology policy statement update: genetic testing for cancer susceptibility.

Authors: 
Journal:  J Clin Oncol       Date:  2003-04-11       Impact factor: 44.544

9.  Accuracy of the BRCAPRO model among women with bilateral breast cancer.

Authors:  Kaylene J Ready; Kristen J Vogel; Deann P Atchley; Kristine R Broglio; Kimberly K Solomon; Christopher Amos; Karen H Lu; Gabriel N Hortobagyi; Banu Arun
Journal:  Cancer       Date:  2009-02-15       Impact factor: 6.860

10.  Simplifying clinical use of the genetic risk prediction model BRCAPRO.

Authors:  Swati Biswas; Philamer Atienza; Jonathan Chipman; Kevin Hughes; Angelica M Gutierrez Barrera; Christopher I Amos; Banu Arun; Giovanni Parmigiani
Journal:  Breast Cancer Res Treat       Date:  2013-05-21       Impact factor: 4.872

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