The regrouping of Luminal B (HER2 negative), a better discriminator of outcome and recurrence score

BACKGROUND: Breast cancer (BC) remains the leading cause of cancer‐related deaths worldwide. High recurrence risk Luminal BC receives adjuvant chemotherapy in addition to standard hormone therapy. Considering the heterogeneity of Luminal B BC, a more accurate classification model is urgently needed. METHODS: In this study, we retrospectively reviewed the data of 1603 patients who were diagnosed with HER2‐negative breast invasive ductal carcinoma. According to the expression level of PR and Ki‐67 index, the Luminal B (HER2‐negative) BCs were divided into three groups: ER+PR−Ki67(low) (ER‐positive, PR‐negative, and Ki‐67 index <20%), ER+PR+Ki67(high) (ER‐positive, PR‐positive, and Ki‐67 index ≥20%), and ER+PR−Ki67(high) (ER‐positive, PR‐negative, and Ki‐67 index ≥20%). The cox proportional hazards regression model was used to evaluate the correlation between each variable and outcomes. Besides, discriminatory accuracy of the models was compared using the area under the receiver operating characteristic curve and log‐rank χ (2) value. RESULTS: The analysis results showed that there was a significant correlation between subtypes using this newly defined classification and overall survival (p < 0.001) and disease‐free survival (DFS) (p < 0.001). Interestingly, patients in the ER+PR−Ki67(high) subgroup have the worst survival outcome in Luminal B (HER2‐negative) subtype, similar to Triple‐negative patients. Besides, the ER+PR+Ki67(high) has worse 5‐year DFS compared with Luminal A group. There was a significant relationship between the regrouping subtype and the recurrence score index (RI) (p < 0.001). Moreover, the results showed that patients in ER+PR–Ki67(high) subtype were more likely to have high RI for distance recurrence (RI‐DR) and local recurrence (RI‐LRR). Our newly defined classification has a better discrimination ability to predict survival outcome and recurrence score of Luminal B (HER2‐negative) BC patients, which may help in clinical decision‐making for individual treatment.