Utility of Magee algorithm in stratification of patients with breast cancer

Background: Breast cancer is the leading malignancy among women worldwide. In hormone receptor–positive, predicting the response to neoadjuvant chemotherapy (NACT) is essential for appropriate treatment planning. Although informative, molecular assays are costly and less accessible in many settings. Magee equation 3 (ME3), based on routine histopathological and immunohistochemical parameters, offers a practical alternative for patient stratification. Aims and Objectives: The aims and objectives of this study are to evaluate estrogen receptor (ER), progesterone receptor (PR), HER2, and Ki-67 expression in pre-treatment biopsies, calculate ME3 scores, and correlate them with Residual Cancer Burden (RCB) following NACT. Materials and Methods: This hospital-based cross-sectional study included 50 patients with invasive breast carcinoma of no special type. Immunohistochemistry for ER, PR, HER2, and Ki-67 was performed on trucut biopsies, and ME3 scores were calculated. Post-NACT RCB was assessed and correlated with the ME3 scores. Results: A significant inverse association was found between ME3 scores and RCB classes (P<0.0001). All patients with ME3 scores <18 were classified as RCB Class III, indicating a poor response. In contrast, 81.8% of patients with ME3 scores ≥31 achieved RCB Class 0, indicating a complete pathological response. Intermediate ME3 scores (18–30.99) showed a mixed distribution, mostly correlating with RCB Classes I and II. Conclusion: ME3 scoring shows a strong predictive correlation with RCB and can aid in stratifying patients for NACT, especially where genomic assays are unavailable.