Literature DB >> 14744738

Risk estimation for healthy women from breast cancer families: new insights and new strategies.

Christi J van Asperen1, M A Jonker, C E Jacobi, J E M van Diemen-Homan, E Bakker, M H Breuning, J C van Houwelingen, G H de Bock.   

Abstract

Risk estimation in breast cancer families is often estimated by use of the Claus tables. We analyzed the family histories of 196 counselees; compared the Claus tables with the Claus, the BRCA1/2, the BRCA1/2/ models; and performed linear regression analysis to extend the Claus tables with characteristics of hereditary breast cancer. Finally, we compared the Claus extended method with the Claus, the BRCA1/2, and the BRCA1/2/u models. We found 47% agreement for Claus table versus Claus model; 39% agreement for Claus table versus BRCA1/2 model; 48% agreement for Claus table versus BRCA1/2/u model; 37% agreement for Claus extended method versus Claus model; 44% agreement for Claus extended model versus BRCA1/2 model; and 66% agreement for Claus extended method versus BRCA1/2/u model. The regression formula (Claus extended method) for the lifetime risk for breast cancer was 0.08 + 0.40 (*) Claus Table + 0.07 (*) ovarian cancer + 0.08 (*) bilateral breast cancer + 0.07 (*) multiple cases. This new method for risk estimation, which is an extension of the Claus tables, incorporates information on the presence of ovarian cancer, bilateral breast cancer, and whether there are more than two affected relatives with breast cancer. This extension might offer a good alternative for breast cancer risk estimation in clinical practice.

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Year:  2004        PMID: 14744738     DOI: 10.1158/1055-9965.epi-03-0090

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  17 in total

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2.  Does and should breast cancer genetic counselling include lifestyle advice?

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3.  Breast cancer genetic counselling referrals: how comparable are the findings between the UK and the Netherlands?

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4.  Risk prediction of complex diseases from family history and known susceptibility loci, with applications for cancer screening.

Authors:  Hon-Cheong So; Johnny S H Kwan; Stacey S Cherny; Pak C Sham
Journal:  Am J Hum Genet       Date:  2011-04-28       Impact factor: 11.025

5.  A case-control study on risk factors of breast cancer in China.

Authors:  Ya-Li Xu; Qiang Sun; Guang-Liang Shan; Jin Zhang; Hai-Bo Liao; Shi-Yong Li; Jun Jiang; Zhi-Min Shao; Hong-Chuan Jiang; Nian-Chun Shen; Yue Shi; Cheng-Ze Yu; Bao-Ning Zhang; Yan-Hua Chen; Xue-Ning Duan; Bo Li
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Review 6.  Breast cancer risk-assessment models.

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

7.  Breast cancer risk assessment in 8,824 women attending a family history evaluation and screening programme.

Authors:  D Gareth R Evans; Sarah Ingham; Sarah Dawe; L Roberts; F Lalloo; A R Brentnall; P Stavrinos; Anthony Howell
Journal:  Fam Cancer       Date:  2014-06       Impact factor: 2.375

8.  Breast density as indicator for the use of mammography or MRI to screen women with familial risk for breast cancer (FaMRIsc): a multicentre randomized controlled trial.

Authors:  Sepideh Saadatmand; Emiel J T Rutgers; Rob A E M Tollenaar; Hermien M Zonderland; Margreet G E M Ausems; Kristien B M I Keymeulen; Margreet S Schlooz-Vries; Linetta B Koppert; Eveline A M Heijnsdijk; Caroline Seynaeve; Cees Verhoef; Jan C Oosterwijk; Inge-Marie Obdeijn; Harry J de Koning; Madeleine M A Tilanus-Linthorst
Journal:  BMC Cancer       Date:  2012-10-02       Impact factor: 4.430

9.  DNA-testing for BRCA1/2 prior to genetic counselling in patients with breast cancer: design of an intervention study, DNA-direct.

Authors:  Aisha S Sie; Liesbeth Spruijt; Wendy A G van Zelst-Stams; Arjen R Mensenkamp; Marjolijn J Ligtenberg; Han G Brunner; Judith B Prins; Nicoline Hoogerbrugge
Journal:  BMC Womens Health       Date:  2012-05-08       Impact factor: 2.809

10.  Design of the BRISC study: a multicentre controlled clinical trial to optimize the communication of breast cancer risks in genetic counselling.

Authors:  Caroline F Ockhuysen-Vermey; Lidewij Henneman; Christi J van Asperen; Jan C Oosterwijk; Fred H Menko; Daniëlle R M Timmermans
Journal:  BMC Cancer       Date:  2008-10-03       Impact factor: 4.430

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