Predicting the Likelihood of Carrying a BRCA1 or BRCA2 Mutation in Asian Patients With Breast Cancer. Issue 14 (10th May 2022)

• Record Type: Journal Article
• Authors: Ang, Boon Hong; Ho, Weang Kee; Wijaya, Eldarina; Kwan, Pui Yoke; Ng, Pei Sze; Yoon, Sook Yee; Hasan, Siti Norhidayu; Lim, Joanna M.C.; Hassan, Tiara; Tai, Mei-Chee; Allen, Jamie; Lee, Andrew; Taib, Nur Aishah Mohd; Yip, Cheng Har; Hartman, Mikael; Lim, Swee Ho; Tan, Ern Yu; Tan, Benita K.T.; Tan, Su-Ming; Tan, Veronique K.M.; Ho, Peh Joo; Khng, Alexis J.; Dunning, Alison M.; Li, Jingmei; Easton, Douglas F.; Antoniou, Antonis C.; Teo, Soo Hwang
• Is Part Of: Journal of clinical oncology. Volume 40:Issue 14(2022)
• Page Start: 1542
• Page End: 1551
• Publication Date: 2022-05-10
• Subjects: Oncology -- Periodicals; Cancer -- Periodicals; Oncology; Medical Oncology; Cancérologie -- Périodiques; Cancer -- Périodiques; Cancérologie; Cancer; Oncology; Oncologia; Càncer; Periodicals; 616.994
• DOI: 10.1200/JCO.21.01647
• Languages: English
• ISSNs: 0732-183X

Abstract

Abstract : PURPOSE: With the development of poly (ADP-ribose) polymerase inhibitors for treatment of patients with cancer with an altered BRCA1 or BRCA2 gene, there is an urgent need to ensure that there are appropriate strategies for identifying mutation carriers while balancing the increased demand for and cost of cancer genetics services. To date, the majority of mutation prediction tools have been developed in women of European descent where the age and cancer-subtype distributions are different from that in Asian women. METHODS: In this study, we built a new model (Asian Risk Calculator) for estimating the likelihood of carrying a pathogenic variant in BRCA1 or BRCA2 gene, using germline BRCA genetic testing results in a cross-sectional population-based study of 8, 162 Asian patients with breast cancer. We compared the model performance to existing mutation prediction models. The models were evaluated for discrimination and calibration. RESULTS: Asian Risk Calculator included age of diagnosis, ethnicity, bilateral breast cancer, tumor biomarkers, and family history of breast cancer or ovarian cancer as predictors. The inclusion of tumor grade improved significantly the model performance. The full model was calibrated (Hosmer-Lemeshow P value = .614) and discriminated well between BRCA and non- BRCA pathogenic variant carriers (area under receiver operating curve, 0.80; 95% CI, 0.75 to 0.84). Addition of grade to the existing clinical genetic testing criteria targeting patients with breast cancer age younger than 45 years reduced the proportion of patients referred for genetic counseling and testing from 37% to 33% ( P value = .003), thereby improving the overall efficacy. CONCLUSION: Population-specific customization of mutation prediction models and clinical genetic testing criteria improved the accuracy of BRCA mutation prediction in Asian patients.