Association between BI-RADS scoring and disease staging in breast cancer: A prospective observational study

Background: Breast cancer remains a major health challenge in India, with delayed diagnosis contributing to advanced staging. The Breast Imaging-Reporting and Data System (BI-RADS) standardizes imaging findings, but its association with disease staging in Indian populations is understudied. This study evaluates the correlation between BI-RADS scores and breast cancer staging, including histopathological burden. Methods: A prospective observational study was conducted at a tertiary center in New Delhi from March 2024 to October 2025. Fifty-eight patients with breast masses were enrolled after ethical approval and informed consent. Exclusion criteria included pregnancy, lactation, breast abscess, and recurrent lumps. Patients underwent clinical examination, ultrasound/mammography with BI-RADS scoring, core needle biopsy with histopathology and immunohistochemistry, and staging via TNM classification. Data were analysed using SPSS, with chi-square, Fisher's exact, ANOVA, and Kruskal-Wallis tests; p≤0.05 was considered significant. Results: Mean age was 55.3±12.1 years; 75.9% were postmenopausal. BI-RADS IV (56.9%) and V (36.2%) predominated. Mean tumour size was 3.2±1.8 cm, and Ki67% was 21.5±17.3%. Axillary lymph node involvement occurred in 63.8%, with Grade II tumours in 63.8%. BIRADS classification was significantly associated with the presence of distant metastasis (23.8%; p=0.03). BI-RADS V showed trends toward larger tumours (3.8±2.1 cm), higher Ki67% (median 25%), Grade III histology (58.3%), and advanced stages (III-IV) (71.4%) However the differences were not statistically significant. No significant associations were found with age, menopausal status, tumour site, or receptor status. Conclusion: In this cohort BI-RADS V correlates with large tumours with aggressive histopathological features and metastatic disease at presentation, supporting its role in risk stratification. Also advanced staging is more frequently seen in higher BI-RADS however, larger studies are needed to validate trends in resource-limited settings.