e13637 Background: International guidelines recommend the 21-gene Recurrence Score (RS) to guide adjuvant chemotherapy decisions in early-stage luminal breast cancer. However, high costs and limited availability create significant barriers to access in countries like Mexico, where only a minority of patients can afford genomic testing. We developed a multivariable linear regression equation based on standard clinico-pathological features to predict RS, aiming to provide a practical tool for treatment optimization in resource-constrained environments. Methods: We analyzed 90 Mexican patients with HR+/HER2- early breast cancer (Stages IA-IIB, pT1b-c, pN0-1) . Clinicopathological variables were correlated with RS results using SPSS v31 . RS was analyzed as a continuous and a dichotomous variable (Low-Intermediate: 0-25; High: > = 26). A multivariable regression model was constructed using an interaction term between SBR grade and Ki67 . The model's performance was compared against actual RS results and the Magee Score (Equation 1) using 2x2 contingency tables to calculate sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Results: Median age was 57 years; 32% were premenopausal, 37% were node-positive (1-3 nodes), and median Ki67 was 13% . Univariate analysis showed that Progesterone Receptor (PR) intensity, Nottingham (SBR) score/grade, and Ki67 significantly correlated with RS (p =26) Low-Intermediate Risk (0-25) Total High Risk 7 (87.5% PPV) 1 (46.7% Sensitivity) 8 Low-Intermediate Risk 8 (90.2% NPV) 74 ( 98.7% Specificity) 82 Total 15 75 90
Millan et al. (Thu,) studied this question.