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Review summarizes approaches to personalize extended endocrine therapy in early HR+/HER2- breast cancer, suggesting improved decision-making using genomic tools.
Hormone receptor-positive (HR+) and HER2-negative (HER2-) breast cancer represents the most prevalent subtype of early-stage breast cancer. Adjuvant endocrine therapy (ET) substantially reduces recurrence and breast cancer mortality; however, late relapse remains a major challenge, with a considerable proportion of recurrences occurring beyond 5 years after diagnosis. Although extended ET can modestly reduce late recurrence, it is associated with cumulative toxicities and impaired quality of life, highlighting the urgent need for biomarkers to identify patients who truly benefit from treatment escalation or extension, while sparing low-risk individuals from overtreatment. Tissue-based multigene expression assays, including the Breast Cancer Index (BCI), EndoPredict, Prosigna, Oncotype DX, and MammaPrint, have improved risk stratification and informed treatment decisions, with BCI demonstrating the strongest evidence for predicting benefit from extended endocrine therapy. Among currently available assays, BCI has the strongest level of evidence supporting its use in guiding extended endocrine therapy decisions. In parallel, liquid biopsy approaches, particularly circulating tumor DNA (ctDNA)/minimal residual disease (MRD) detection, have emerged as promising tools for dynamic monitoring and early detection of molecular relapse. This review summarizes current evidence supporting biomarker-guided decision-making in early-stage HR+/HER2- breast cancer, focusing on three clinically relevant questions: who requires treatment escalation, who benefits from extended endocrine therapy, and who may safely de-escalate. We further discuss challenges and future directions toward integrated models combining genomic assays with longitudinal ctDNA monitoring to refine personalized adjuvant endocrine strategies. However, current evidence remains limited, and prospective validation is required.
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Liu et al. (2026) studied this question.
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