title: Evaluating the performance of models for predicting the BRCA germline mutations in Han Chinese familial breast cancer patients.
abstract: OBJECTIVE
  Established models (Penn, Myraid and BRCApro) are useful of estimating the probability that a person has a BRCA mutation. But the value of these models in Chinese population is unclear. The aim of the study is to evaluate the performance of three models on the assisting in pre-test genetic risk counseling.
  
  
  METHODS
  Three risk assessment models, Penn II, Myriad and BRCApro, were applied to 212 familial breast cancer patients who had undergone BRCA1/2 mutation analysis. Sensitivity, specificity, positive and negative predictive values, likelihood ratios and area under the receiver operator characteristic (ROC) curve were calculated for each model.
  
  
  RESULTS
  Myriad showed a better ROC curve than BRCApro either for BRCA1 or BRCA1/2 combination mutation prediction, but BRCApro had a higher positive likelihood ratio when using 10% as the probability threshold. The performance of three models improved when they were evaluated in 66 patients from high risk families, presenting increased ROC and positive likelihood ratio. Especially that of BRCApro for BRCA2, the ROC was increased to 0.716 and its positive likelihood was 5.6.
  
  
  CONCLUSIONS
  Three models had the similar impact on the pre-test probability of BRCA mutation. But at a 10% cutoff point, BRCApro had the best BRCA mutation carrier prediction value. The performance of BRCApro for BRCA2 mutation prediction was improved when it was restricted in patients from high risk families.
authors.affiliation: Department of Oncology, Breast Cancer Institute, Cancer Hospital/Cancer Institute, Shanghai Medical College, Institutes of Biomedical Science, Fudan University, Shanghai 200032, People's Republic of China.
authors.forename: Nan-Yan
authors.initials: NY
authors.lastname: Rao
authors.forename: Zhen
authors.initials: Z
authors.lastname: Hu
authors.forename: Jin-Ming
authors.initials: JM
authors.lastname: Yu
authors.forename: Wen-Feng
authors.initials: WF
authors.lastname: Li
authors.forename: Bin
authors.initials: B
authors.lastname: Zhang
authors.forename: Feng-Xi
authors.initials: FX
authors.lastname: Su
authors.forename: Jiong
authors.initials: J
authors.lastname: Wu
authors.forename: Zhen-Zhou
authors.initials: ZZ
authors.lastname: Shen
authors.forename: Wei
authors.initials: W
authors.lastname: Huang
authors.forename: Zhi-Ming
authors.initials: ZM
authors.lastname: Shao
mesh_terms: D000328:Adult; D001943:Breast Neoplasms / Q000175:diagnosis / Q000235:genetics*; D003198:Computer Simulation; D004252:DNA Mutational Analysis; D005260:Female; D019398:Genes, BRCA1; D024522:Genes, BRCA2; D020022:Genetic Predisposition to Disease; D018095:Germ-Line Mutation / Q000235:genetics*; D006801:Humans; D008875:Middle Aged; D015233:Models, Statistical; D011237:Predictive Value of Tests; D011336:Probability; D012372:ROC Curve; D012680:Sensitivity and Specificity