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PMID: 17413421 Published · ppublish English

Prediction of BRCA1/2 mutation status in patients with ovarian cancer from a hospital-based cohort.

Jacobi Catharina E, van Ierland Yvette, van Asperen Christi J, Hallensleben Eric, Devilee Peter, Jan Fleuren Gert, Kenter Gemma G

Abstract

To describe patient, tumor, and family histories of cancer in a hospital-based cohort of patients with ovarian cancer and to identify the predictive value of these characteristics for (non)carrying a BRCA1 or BRCA2 mutation.,Women diagnosed with invasive ovarian cancer between 1999 and 2003 in the west region of The Netherlands and unselected for age at diagnosis or cancer family history were included. Information was gathered on patient and tumor characteristics; p53; HER-2/neu, and KI-67 protein-expression; BRCA1/2 mutations; and family histories of cancer. Prediction tests were constructed using multivariate analyses.,Our study included 85 women (mean age at diagnosis, 57.6 years; standard deviation, 11.0 years). Six of these women had been previously or concurrently diagnosed with another tumor. Of the ovarian cancers, 41 (48.2%) were in an early stage (FIGO I or II). Five pathogenic mutations (6.1%) and six unclassified variants (7.3%) were identified in BRCA1/2; when the total sensitivity of the mutation scanning was taken into account, it was estimated to reflect seven pathogenic mutations (8.5%) and eight unclassified variants (9.8%). Sixty-nine women (81.2%) had at least one relative with cancer. A personal history of breast cancer and a family history of breast, ovarian, or uterine/endometrioid cancer were found to predict the presence of pathogenic mutations.,As the combination of a personal history of breast cancer and a family history of breast, ovarian, or uterine/endometrioid cancer had good predictive value for the presence of a pathogenic BRCA1/2 mutation, the presented prediction test is a useful instrument to identify those women eligible for DNA testing.

Article Info
Journal
Genetics in medicine : official journal of the American College of Medical Genetics
Abbr.
Genet Med
Published
2007-06-06
Indexed
2007-04-06
Updated
2010-11-18
Language
English
Country/Region
United States
NLM ID
9815831
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