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Risk estimation as a decision-making tool for genetic analysis of the breast cancer susceptibility genes. EC Demonstration Project on Familial Breast Cancer.

Chang-Claude, J; Becher, H; Caligo, M; Eccles, D; Evans, G; Haites, N; Hodgson, S; Møller, P; Weber, B H; Stoppa-Lyonnet, D

Disease markers. 1999;15(1-3):53-65.

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Abstract

For genetic counselling of a woman on familial breast cancer, an accurate evaluation of the probability that she carries a germ-line mutation is needed to assist in making decisions about genetic-testing. We used data from eight collaborating centres comprising 618 families (346 breast cancer only, 239 breast or ovarian cancer) recruited as research families or counselled for familial breast cancer, representing a broad range of family structures. Screening was performed in affected women from 618 families for germ-line mutations in BRCA1 and in 176 families for BRCA2 mutations, using different methods including SSCP, CSGE, DGGE, FAMA and PTT analysis followed by direct sequencing. Germ-line BRCA1 mutations were detected in 132 families and BRCA2 mutations in 16 families. The probability of being a carrier of a dominant breast cancer gene was calculated for the screened individual under the established genetic model for breast cancer susceptibility, first, with parameters for age-specific penetrances for breast cancer only [7] and, second, with age-specific penetrances for ovarian cancer in addition [20]. Our results indicate that the estimated probability of carrying a dominant breast cancer gene gives a direct measure of the likelihood of detecting mutations in BRCA1 and BRCA2. For breast/ovarian cancer families, the genetic model according to Narod et al. [20] is preferable for calculating the proband's genetic risk, and gives detection rates that indicate a 50% sensitivity of the gene test. Due to the incomplete BRCA2 screening of the families, we cannot yet draw any conclusions with respect to the breast cancer only families.

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Place of publication:
NETHERLANDS
Volume:
15
Issue:
1-3
Pagination:
53-65
Pubmed Identifier:
10595253
Access state:
Active

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Record metadata

Manchester eScholar ID:
uk-ac-man-scw:210880
Created by:
Evans, Gareth
Created:
12th October, 2013, 14:52:28
Last modified by:
Evans, Gareth
Last modified:
12th October, 2013, 14:52:28

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