Breast cancer is the most common form of cancer among women worldwide, with 2.3 million new cases and 685,000 deaths in 2020 globally.¹ Currently, most of the mutation prediction models identifying BRCA pathogenic variants (PVs) are developed in Western countries.² These models are based on clinical genetic data obtained from women of European or North American descent which are different from the Asian population, displaying different cancer-subtype distributions and younger age of diagnosis.² In a recent study published in the Journal of Clinical Oncology, a logistic regression prediction model for Southeast Asian breast cancer patients to estimate the likelihood of carrying PVs in the BRCA1 or BRCA2 gene has been developed and validated.² Named “Asian Risk Calculator (ARiCa)”, the prediction model was created based on the necessity of having an Asian population-specific prediction tool available to income-challenged Asian countries where the provision of genetic services can be difficult with a lack of supply.^1,2

In this cross-sectional population-based study, 8,162 breast cancer patients were recruited from 2 hospitals in Malaysia (the Malaysian Breast Cancer Genetic study) and 6 hospitals in Singapore (the Singapore Breast Cancer Cohort study).² The ethnicities of the patients pooled were Chinese, Indian and Malay, with a mean age of diagnosis of 52.3 years.² The study sample was randomly divided into training (70%) and validation (30%) sets.² Predictors of BRCA PV were the age of diagnosis, ethnic origin, bilateral breast cancer, pathologic characteristics, and familial history of ovarian or breast cancers.²

Some 5,714 breast cancer cases (228 BRCA carriers) were used to develop prediction models and validated using 2,448 cases (95 BRCA carriers).² Six combinations of tumor biomarkers and predictors were used in the evaluation: 1) Triple-negative breast cancer (TNBC); 2) Estrogen receptor (ER); 3) ER and human epidermal growth factor receptor 2 (HER2); 4) Hormone receptor (HR) and HER2; and 5) Immune-histochemical subtypes.²

The model with the highest receiver operating curve (AUC) and the lowest non-significant Hosmer-Lemeshow (HL) test score was considered the best performance model for predicting the overall BRCA PV carrier status and named the ARiCa.² The AUC for differentiating between BRCA vs. non-BRCA carriers was 0.80 (95% CI:0.75-0.84).^2,3 The model was calibrated with an HL p=0.614.2 The evaluation of ARiCa by ethnicity possessed strong discriminatory power and was calibrated well among the ethnic groups.² Variables associated with ARiCa’s overall BRCA PV carrier status were younger age of diagnosis, ER-negativity, HER2-negativity, higher tumor grade, Indian ethnicity, and the existence of first-degree family history with breast or ovarian cancer.²