title: A new scoring system for the chances of identifying a BRCA1/2 mutation outperforms existing models including BRCAPRO.
abstract: OBJECTIVE
  To develop a simple scoring system for the likelihood of identifying a BRCA1 or BRCA2 mutation.
  
  
  METHODS
  DNA samples from affected subjects from 422 non-Jewish families with a history of breast and/or ovarian cancer were screened for BRCA1 mutations and a subset of 318 was screened for BRCA2 by whole gene screening techniques. Using a combination of results from screening and the family history of mutation negative and positive kindreds, a simple scoring system (Manchester scoring system) was devised to predict pathogenic mutations and particularly to discriminate at the 10% likelihood level. A second separate dataset of 192 samples was subsequently used to test the model's predictive value. This was further validated on a third set of 258 samples and compared against existing models.
  
  
  RESULTS
  The scoring system includes a cut-off at 10 points for each gene. This equates to >10% probability of a pathogenic mutation in BRCA1 and BRCA2 individually. The Manchester scoring system had the best trade-off between sensitivity and specificity at 10% prediction for the presence of mutations as shown by its highest C-statistic and was far superior to BRCAPRO.
  
  
  CONCLUSIONS
  The scoring system is useful in identifying mutations particularly in BRCA2. The algorithm may need modifying to include pathological data when calculating whether to screen for BRCA1 mutations. It is considerably less time-consuming for clinicians than using computer models and if implemented routinely in clinical practice will aid in selecting families most suitable for DNA sampling for diagnostic testing.
authors.affiliation: Academic Unit of Medical Genetics and Regional Genetics Service, St Mary's Hospital, Manchester M13 0JH, UK. gareth.evans@cmmc.nhs.uk
authors.forename: D G R
authors.initials: DG
authors.lastname: Evans
authors.forename: D M
authors.initials: DM
authors.lastname: Eccles
authors.forename: N
authors.initials: N
authors.lastname: Rahman
authors.forename: K
authors.initials: K
authors.lastname: Young
authors.forename: M
authors.initials: M
authors.lastname: Bulman
authors.forename: E
authors.initials: E
authors.lastname: Amir
authors.forename: A
authors.initials: A
authors.lastname: Shenton
authors.forename: A
authors.initials: A
authors.lastname: Howell
authors.forename: F
authors.initials: F
authors.lastname: Lalloo
mesh_terms: D000465:Algorithms; D019313:BRCA1 Protein / Q000235:genetics*; D024682:BRCA2 Protein / Q000235:genetics*; D001943:Breast Neoplasms / Q000175:diagnosis / Q000235:genetics; D005260:Female; D005820:Genetic Testing / Q000379:methods / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D015233:Models, Statistical; D009154:Mutation; D010051:Ovarian Neoplasms / Q000175:diagnosis / Q000235:genetics; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D019313:BRCA1 Protein; D024682:BRCA2 Protein