A Novel Breast Cancer Index for Prediction of Distant Recurrence in HR+ Early-Stage Breast Cancer with One to Three Positive Nodes

Purpose: The study objective was to characterize the prognostic performance of a novel Breast Cancer Index model (BCIN+), an integration of BCI gene expression, tumor size, and grade, specifically developed for assessment of distant recurrence (DR) risk in HR+ breast cancer patients with one to three positive lymph nodes (pN1). Experimental Design: Analysis was conducted in a well-annotated retrospective series of pN1 patients (N = 402) treated with adjuvant endocrine therapy with or without chemotherapy using a prespecified model. The primary endpoint was time-to-DR. Results were determined blinded to clinical outcome. Kaplan-Meier estimates of overall (0-15 years) and late (>= 5 years) DR, HRs, and 95% confidence interval (CIs) were estimated. Likelihood ratio statistics assessed relative contributions of prognostic information. Results: BCIN+ classified 81 patients (20%) as low risk with a 15-year DR rate of 1.3% (95% CI, 0.0%-3.7%) versus 321 patients as high risk with a DR rate of 29.0% (95% CI, 23.2%34.4%). In patients DR-free for > 5 years (n = 349), the late DR rate was 1.3% (95% CI, 0.0%-3.7%) and 16.1% (95% CI, 10.6%-21.3%) in low-and high-risk groups, respectively. BCI gene expression alone was significantly prognostic (Delta LR-chi(2) = 20.12; P < 0.0001). Addition of tumor size (Delta LR-chi(2) = 13.29, P = 0.0003) and grade (Delta LR-chi(2) = 12.72; P = 0.0004) significantly improved prognostic performance. BCI added significant prognostic information to tumor size (Delta LR-chi(2) = 17.55; P < 0.0001); addition to tumor grade was incremental (Delta LR-chi(2) = 2.38; P = 0.1) with considerable overlap between prognostic values (Delta LR-chi(2) = 17.74). Conclusions: The integrated BCIN+ identified 20% of pN1 patients with limited risk of recurrence over 15 years, in whom extended endocrine treatment may be spared. Ongoing studies will characterize combined clinical-genomic risk assessment in node-positive patients. (C) 2017 AACR.