RT Journal Article SR Electronic T1 Evaluating the performance of the breast cancer genetic risk models BOADICEA, IBIS, BRCAPRO and Claus for predicting BRCA1/2 mutation carrier probabilities: a study based on 7352 families from the German Hereditary Breast and Ovarian Cancer Consortium JF Journal of Medical Genetics JO J Med Genet FD BMJ Publishing Group Ltd SP 360 OP 367 DO 10.1136/jmedgenet-2012-101415 VO 50 IS 6 A1 Christine Fischer A1 Karoline Kuchenbäcker A1 Christoph Engel A1 Silke Zachariae A1 Kerstin Rhiem A1 Alfons Meindl A1 Nils Rahner A1 Nicola Dikow A1 Hansjörg Plendl A1 Irmgard Debatin A1 Tiemo Grimm A1 Dorothea Gadzicki A1 Ricarda Flöttmann A1 Judit Horvath A1 Evelin Schröck A1 Friedrich Stock A1 Dieter Schäfer A1 Ira Schwaab A1 Christiana Kartsonaki A1 Nasim Mavaddat A1 Brigitte Schlegelberger A1 Antonis C Antoniou A1 Rita Schmutzler A1 on behalf of the German Consortium for Hereditary Breast and Ovarian Cancer YR 2013 UL http://jmg.bmj.com/content/50/6/360.abstract AB Background Risk prediction models are widely used in clinical genetic counselling. Despite their frequent use, the genetic risk models BOADICEA, BRCAPRO, IBIS and extended Claus model (eCLAUS), used to estimate BRCA1/2 mutation carrier probabilities, have never been comparatively evaluated in a large sample from central Europe. Additionally, a novel version of BOADICEA that incorporates tumour pathology information has not yet been validated. Patients and methods Using data from 7352 German families we estimated BRCA1/2 carrier probabilities under each model and compared their discrimination and calibration. The incremental value of using pathology information in BOADICEA was assessed in a subsample of 4928 pedigrees with available data on breast tumour molecular markers oestrogen receptor, progesterone receptor and human epidermal growth factor 2. Results BRCAPRO (area under receiver operating characteristic curve (AUC)=0.80 (95% CI 0.78 to 0.81)) and BOADICEA (AUC=0.79 (0.78–0.80)), had significantly higher diagnostic accuracy than IBIS and eCLAUS (p<0.001). The AUC increased when pathology information was used in BOADICEA: AUC=0.81 (95% CI 0.80 to 0.83, p<0.001). At carrier thresholds of 10% and 15%, the net reclassification index was +3.9% and +5.4%, respectively, when pathology was included in the model. Overall, calibration was best for BOADICEA and worst for eCLAUS. With eCLAUS, twice as many mutation carriers were predicted than observed. Conclusions Our results support the use of BRCAPRO and BOADICEA for decision making regarding genetic testing for BRCA1/2 mutations. However, model calibration has to be improved for this population. eCLAUS should not be used for estimating mutation carrier probabilities in clinical settings. Whenever possible, breast tumour molecular marker information should be taken into account.