Evaluating the performance of the breast cancer genetic risk models BOADICEA, IBIS, BRCAPRO and Claus for predictingBRCA1/2mutation carrier probabilities: a study based on 7352 families from the German Hereditary Breast and Ovarian Cancer Consortium

接收机工作特性 突变 人口 宜必思 医学 遗传学 肿瘤科 计算机科学 生物 内科学 环境卫生 基因 古生物学
作者
Christine Fischer,Karoline Kuchenbäcker,Christoph Engel,Silke Zachariae,Kerstin Rhiem,Alfons Meindl,Nils Rahner,Nicola Dikow,Hansjörg Plendl,Irmgard Debatin,T. Grimm,Dorothea Gadzicki,Ricarda Flöttmann,Judit Horváth,Evelin Schröck,Friedrich Stock,Dieter Schäfer,Ira Schwaab,Christiana Kartsonaki,Nasim Mavaddat
出处
期刊:Journal of Medical Genetics [BMJ]
卷期号:50 (6): 360-367 被引量:91
标识
DOI:10.1136/jmedgenet-2012-101415
摘要

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.
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