JCO Clin Cancer Inform. 2026 Mar;10:e2500173. doi: 10.1200/CCI-25-00173. Epub 2026 Mar 3.
ABSTRACT
PURPOSE: Early-stage breast cancer (ESBC) in women younger than 50 years often presents with tumor features, including grade and hormone receptor and human epidermal growth factor receptor 2 (HER2) status different from older women. Machine learning clustering techniques can reveal underlying patterns in the inter-relationships of these features and provide novel insights to inform and guide decision making by patients and providers.
METHODS: Partitioning around medoids (PAM) was applied to SEER data from 67,746 women age 18-49 years diagnosed with ESBC. PAM clustering based on tumor size (T), nodal status (N), grade, and receptor status identified 10 distinct clusters. The PAM clusters and American Joint Committee on Cancer (AJCC) anatomic and prognostic stages were compared in terms of their tumor features and their association with chemotherapy and survival.
RESULTS: AJCC anatomic and prognostic stages are primarily defined by T and N. PAM clusters were primarily defined by receptor status and grade. PAM clusters align closely with luminal A, luminal B, triple-negative, or HER2-overexpressing treatment-related subtypes. PAM clusters better discriminated chemotherapy treatment, with C-statistic 0.839 (95% CI, 0.836 to 0.842), than either anatomic, with C-statistic 0.770 (95% CI, 0.767 to 0.773), or prognostic staging, with C-statistic 0.796 (95% CI, 0.794 to 0.800). PAM clusters were better predictors of 5-year overall survival, with C-statistic 0.733 (95% CI, 0.727 to 0.739), than anatomic stages, with C-statistic 0.721 (95% CI, 0.715 to 728), but not as predictive as prognostic stages, with C-statistic 0.759 (95% CI, 0.753 to 0.764).
CONCLUSION: Data-driven PAM clusters provide novel insights into the inter-relationship of tumor features and their association with hormonal, targeted, and chemotherapy treatment and with survival outcomes in women younger than 50 years with ESBC. An online application was created so that the PAM clusters could be used as alternatives or in addition to traditional AJCC staging to inform and guide patients and providers.
PMID:41774882 | DOI:10.1200/CCI-25-00173
