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Optimal selection for BRCA1 and BRCA2 mutation testing using a combination of 'easy to apply' probability models.
- Source :
-
British journal of cancer [Br J Cancer] 2006 Sep 18; Vol. 95 (6), pp. 757-62. Date of Electronic Publication: 2006 Aug 15. - Publication Year :
- 2006
-
Abstract
- To establish an efficient, reliable and easy to apply risk assessment tool to select families with breast and/or ovarian cancer patients for BRCA mutation testing, using available probability models. In a retrospective study of 263 families with breast and/or ovarian cancer patients, the utility of the Frank (Myriad), Gilpin (family history assessment tool) and Evans (Manchester) model was analysed, to select 49 BRCA mutation-positive families. For various cutoff levels and combinations, the sensitivity and specificity were calculated and compared. The best combinations were subsequently validated in additional sets of families. Comparable sensitivity and specificity were obtained with the Gilpin and Evans models. They appeared to be complementary to the Frank model. To obtain an optimal sensitivity, five 'additional criteria' were introduced that are specific for the selection of small or uninformative families. The optimal selection is made by the combination 'Frank >or=16% or Evans2 >or=12 or one of five additional criteria'. The efficiency of the selection of families for mutation testing of BRCA1 and BRCA2 can be optimised by using a combination of available easy to apply risk assessment models.
- Subjects :
- Adult
Breast Neoplasms genetics
Cohort Studies
Female
Genetic Predisposition to Disease
Humans
Middle Aged
Mutation
Ovarian Neoplasms genetics
Pedigree
Predictive Value of Tests
Probability
Retrospective Studies
Risk Assessment
Sensitivity and Specificity
BRCA1 Protein genetics
BRCA2 Protein genetics
Breast Neoplasms diagnosis
Models, Statistical
Ovarian Neoplasms diagnosis
Patient Selection
Subjects
Details
- Language :
- English
- ISSN :
- 0007-0920
- Volume :
- 95
- Issue :
- 6
- Database :
- MEDLINE
- Journal :
- British journal of cancer
- Publication Type :
- Academic Journal
- Accession number :
- 16909138
- Full Text :
- https://doi.org/10.1038/sj.bjc.6603306