A new scoring system for the chances of identifying a BRCA1/2 mutation outperforms existing models including BRCAPRO

• Published in: Journal of medical genetics Vol. 41; no. 6; pp. 474 - 480
• Main Authors: Evans, D G R, Eccles, D M, Rahman, N, Young, K, Bulman, M, Amir, E, Shenton, A, Howell, A, Lalloo, F
• Format: Journal Article
• Language: English
• Published: England BMJ Publishing Group Ltd 01.06.2004; BMJ Publishing Group LTD; BMJ Group
• Subjects: Age; Algorithms; BRCA1; BRCA1 Protein - genetics; BRCA2; BRCA2 Protein - genetics; Breast cancer; Breast Neoplasms - diagnosis; Breast Neoplasms - genetics; conformation sensitive gel electrophoresis; CSGE; FBC; Female; female breast cancer; Genetic Testing - methods; Genetic Testing - statistics & numerical data; Health risk assessment; hetero-duplex analysis; Humans; Male; male breast cancer; MBC; Medical Genetics in Practice; Models, Statistical; Mutation; mutation analysis; oestrogen receptor; Ovarian cancer; Ovarian Neoplasms - diagnosis; Ovarian Neoplasms - genetics; Population; protein truncation test; PTT; Reproducibility of Results; Sensitivity and Specificity; single strand conformation polymorphism; SSCP; triage; Tumors; United Kingdom > UK
• ISSN: 0022-2593; 1468-6244; 1468-6244
• DOI: 10.1136/jmg.2003.017996

Purpose: 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. Conclusion: 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.