METHODS: The development data set comprised 138,309 women from 17 case-control studies. PRSs were generated using a clumping and thresholding method, lasso penalized regression, an Empirical Bayes approach, a Bayesian polygenic prediction approach, or linear combinations of multiple PRSs. These PRSs were evaluated in 89,898 women from 3 prospective studies (1592 incident cases).

RESULTS: The best performing PRS (genome-wide set of single-nucleotide variations [formerly single-nucleotide polymorphism]) had a hazard ratio per unit SD of 1.62 (95% CI = 1.46-1.80) and an area under the receiver operating curve of 0.635 (95% CI = 0.622-0.649). Combined Asian and European PRSs (333 single-nucleotide variations) had a hazard ratio per SD of 1.53 (95% CI = 1.37-1.71) and an area under the receiver operating curve of 0.621 (95% CI = 0.608-0.635). The distribution of the latter PRS was different across ethnic subgroups, confirming the importance of population-specific calibration for valid estimation of breast cancer risk.

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.

METHODS: Data were collected on 271 BRCA1 and 301 BRCA2 families from Malaysia and Singapore, ascertained through population/hospital-based case-series (88%) and genetic clinics (12%). Age-specific cancer risks were estimated using a modified segregation analysis method, adjusted for ascertainment.

FINDINGS: BC and OC relative risks (RRs) varied across age groups for both BRCA1 and BRCA2. The age-specific RR estimates were similar across ethnicities and country of residence. For BRCA1 carriers of Malay, Indian and Chinese ancestry born between 1950 and 1959 in Malaysia, the cumulative risk (95% CI) of BC by age 80 was 40% (36%-44%), 49% (44%-53%) and 55% (51%-60%), respectively. The corresponding estimates for BRCA2 were 29% (26-32%), 36% (33%-40%) and 42% (38%-45%). The corresponding cumulative BC risks for Singapore residents from the same birth cohort, where the underlying population cancer incidences are higher compared to Malaysia, were higher, varying by ancestry group between 57 and 61% for BRCA1, and between 43 and 47% for BRCA2 carriers. The cumulative risk of OC by age 80 was 31% (27-36%) for BRCA1 and 12% (10%-15%) for BRCA2 carriers in Malaysia born between 1950 and 1959; and 42% (34-50%) for BRCA1 and 20% (14-27%) for BRCA2 carriers of the same birth cohort in Singapore. There was evidence of increased BC and OC risks for women from >1960 birth cohorts (p-value = 3.6 × 10-5 for BRCA1 and 0.018 for BRCA2).

INTERPRETATION: The absolute age-specific cancer risks of Asian carriers vary depending on the underlying population-specific cancer incidences, and hence should be customised to allow for more accurate cancer risk management.

METHOD: Using linear regression adjusting for age, BMI, and ancestry-informative principal components, we evaluated the associations of previously reported MD-associated SNPs with MD in a multi-ethnic cohort of Asian ancestry. Area and volumetric mammographic densities were determined using STRATUS (N = 2450) and Volpara™ (N = 2257). We also assessed the associations of these SNPs with breast cancer risk in an Asian population of 14,570 cases and 80,870 controls.