RT Journal Article
SR Electronic
T1 Predicting the likelihood of carrying a BRCA1 or BRCA2 mutation: validation of BOADICEA, BRCAPRO, IBIS, Myriad and the Manchester scoring system using data from UK genetics clinics
JF Journal of Medical Genetics
JO J Med Genet
FD BMJ Publishing Group Ltd
SP 425
OP 431
DO 10.1136/jmg.2007.056556
VO 45
IS 7
A1 A C Antoniou
A1 R Hardy
A1 L Walker
A1 D G Evans
A1 A Shenton
A1 R Eeles
A1 S Shanley
A1 G Pichert
A1 L Izatt
A1 S Rose
A1 F Douglas
A1 D Eccles
A1 P J Morrison
A1 J Scott
A1 R L Zimmern
A1 D F Easton
A1 P D P Pharoah
YR 2008
UL http://jmg.bmj.com/content/45/7/425.abstract
AB Objectives: Genetic testing for the breast and ovarian cancer susceptibility genes BRCA1 and BRCA2 has important implications for the clinical management of people found to carry a mutation. However, genetic testing is expensive and may be associated with adverse psychosocial effects. To provide a cost-efficient and clinically appropriate genetic counselling service, genetic testing should be targeted at those individuals most likely to carry pathogenic mutations. Several algorithms that predict the likelihood of carrying a BRCA1 or a BRCA2 mutation are currently used in clinical practice to identify such individuals.Design: We evaluated the performance of the carrier prediction algorithms BOADICEA, BRCAPRO, IBIS, the Manchester scoring system and Myriad tables, using 1934 families seen in cancer genetics clinics in the UK in whom an index patient had been screened for BRCA1 and/or BRCA2 mutations. The models were evaluated for calibration, discrimination and accuracy of the predictions.Results: Of the five algorithms, only BOADICEA predicted the overall observed number of mutations detected accurately (ie, was well calibrated). BOADICEA also provided the best discrimination, being significantly better (p<0.05) than all models except BRCAPRO (area under the receiver operating characteristic curve statistics: BOADICEA = 0.77, BRCAPRO = 0.76, IBIS = 0.74, Manchester = 0.75, Myriad = 0.72). All models underpredicted the number of BRCA1 and BRCA2 mutations in the low estimated risk category.Conclusions: Carrier prediction algorithms provide a rational basis for counselling individuals likely to carry BRCA1 or BRCA2 mutations. Their widespread use would improve equity of access and the cost-effectiveness of genetic testing.