J Med Genet 50:360-367 doi:10.1136/jmedgenet-2012-101415
  • Cancer genetics
  • Original article

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

  1. on behalf of the German Consortium for Hereditary Breast and Ovarian Cancer
  1. 1Institute of Human Genetics, University of Heidelberg, Heidelberg, Germany
  2. 2Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
  3. 3Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
  4. 4Department of Gynaecology and Obstetrics, Center for Familiar Breast and Ovarian Cancer, University Hospital of Cologne, Köln, Germany
  5. 5Department of Obstetrics and Gynecology, Division of Tumor Genetics, Klinikum rechts der Isar der Technischen Universität Muenchen, Munich, Germany
  6. 6Institute of Human Genetics, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
  7. 7Institute of Human Genetics, University Hospital of Schleswig-Holstein, Campus Kiel, Christian-Albrechts-University of Kiel, Kiel, Germany
  8. 8Institute of Human Genetics, University of Ulm, Ulm, Germany
  9. 9Institute of Human Genetics, Biozentrum University of Würzburg, Würzburg, Germany
  10. 10Institute of Cell and Molecular Pathology, Medical School Hannover, Hannover, Germany
  11. 11Institute of Medical Genetics and Human Genetics, Charite’-Universitätsmedizin Berlin, Berlin, Germany
  12. 12Institute of Human Genetics, University of Münster, Münster, Germany
  13. 13Institute of Clinical Genetics, Medical School, Technical University of Dresden, Dresden, Germany
  14. 14Institute of Human Genetics, University of Leipzig, Leipzig, Germany
  15. 15Institute of Human Genetics, University of Frankfurt/Main, Frankfurt/Main, Germany
  16. 16Praxis für Humangenetik, Wiesbaden, Germany
  17. 17Department of Statistics, University of Oxford, Oxford, UK
  1. Correspondence to Dr Christine Fischer, Institute of Human Genetics, University of Heidelberg, Im Neuenheimer Feld 366, Heidelberg 69120, Germany; cfischer{at}
  • Received 14 October 2012
  • Revised 6 February 2013
  • Accepted 21 February 2013
  • Published Online First 6 April 2013


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.