Germline BRCA1/2 pathogenic or likely pathogenic (P/LP) variant identification is critical for guiding surgical and systemic therapy in breast cancer. However, prediction tools developed in high-risk cohorts remain limited, hindering large-scale adoption in clinical pathways in China. We included 1,204 high-risk breast cancer patients during 2017-2021 from Zhejiang Cancer Hospital, eastern China. Clinical data were collected and blood samples underwent targeted NGS for BRCA1/2, with variants classified by ClinVar and the American College of Medical Genetics and Genomics-Association for Molecular Pathology (ACMG-AMP). Predictors (histology, molecular subtype, age, and family history) were included with missing data imputed using Multiple Imputation by Chained Equations (MICE). We developed a multivariable logistic regression model to predict P/LP carrier status and evaluated its performance across imputed datasets with bootstrap internal validation. In 1,204 high-risk Chinese breast cancer patients, BRCA1/2 P/LP variants were detected in 102 (8.5%), with strong associations for triple-negative breast cancer (TNBC) (55.9%), invasive ductal carcinoma (IDC) (94.1%), and family history, while older age reduced risk. The final model incorporated histology, molecular subtype, age, and family history. It achieved good discrimination and acceptable calibration, with a low Brier score. The area under the receiver operating characteristic curve (AUC) was 0.758, the Hosmer-Lemeshow (HL) P value was 0.349, and the Brier score was 0.071. Sensitivity, stratified, and bootstrap validation (500 resamples, calibration error 0.007) confirmed robustness. Decision Curve Analysis (DCA) demonstrated clear net clinical benefit over test-all and test-none strategies. We developed a clinicopathology-based model from a high-risk Chinese breast cancer cohort to predict BRCA1/2 P/LP carrier probability, which was the large high-risk clinical cohort with information of BRCA1/2 variants and clinical characteristics in mainland China. It supported clinical implementation by extending testing beyond current guidelines and optimizing the use of limited genetic resources.
山东省济南市章丘区文博路2号
齐鲁师范学院 genelibs生信实验室
山东省济南市高新区舜华路750号
大学科技园北区F座4单元2楼
电话: 0531-88819269