Affiliations 

  • 1 Faculty of Science and Engineering, School of Mathematical Sciences, University of Nottingham Malaysia, Jalan Broga, Semenyih, Selangor, Malaysia
  • 2 Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, United Kingdom
  • 3 Faculty of Medicine, University Malaya Cancer Research Institute, University of Malaya, Jalan Universiti, Kuala Lumpur, Malaysia
  • 4 Subang Jaya Medical Centre, Subang Jaya, Malaysia
  • 5 Department of Surgery, National University Hospital and NUHS, Singapore, Singapore
  • 6 Breast Department, KK Women's and Children's Hospital, Singapore, Singapore
  • 7 Department of General Surgery, Tan Tock Seng Hospital, Singapore, Singapore
  • 8 Division of Surgery and Surgical Oncology, National Cancer Centre Singapore, Singapore, Singapore
  • 9 Division of Breast Surgery, Department of General Surgery, Changi General Hospital, Singapore, Singapore
  • 10 Laboratory of Women's Health and Genetics, Genome Institute of Singapore, Singapore, Singapore
  • 11 Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, United Kingdom
J Clin Oncol, 2022 May 10;40(14):1542-1551.
PMID: 35143328 DOI: 10.1200/JCO.21.01647

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.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.