Reassessing Estrogen Receptor Expression Thresholds for Breast Cancer Prognosis in HER2-negative Patients Using Shape Restricted Modeling

PURPOSE: To assess the dynamic link between continuous estrogen receptor (ER) expression and long-term clinical outcomes in non-metastatic breast cancer and to identify the ideal cutoff value for ER expression to optimize endocrine therapy use. METHODS: The study included 3055 female patients with stage II or III HER2-negative breast cancer. The primary outcomes were time to recurrence or death (TTR) and overall survival (OS). We used a novel shape-restricted Cox model to determine the desirable ER expression cutoff to predict breast cancer prognoses. Our novel model allows ER as a continuous variable, utilizing a flexible monotone-shaped Cox regression to assess its association with survival outcomes holistically. RESULTS: The shape-restricted Cox model identified 10% ER as the preferred cutoff to predict TTR. The finding was confirmed by the log-rank test and standard Cox model that patients with ER ≥ 10% had TTR benefit over ER < 10% (log-rank p < 0.001). No OS or TTR benefit of adjuvant endocrine therapy was observed in patients with 1% ≤ ER < 10% (HR 0.877, 95% CI 0.481–1.600, p = 0.668 for TTR and HR 0.698, 95% CI 0.337–1.446, p = 0.333 for OS). CONCLUSIONS: Using the shape-restricted Cox model, this study suggests a potential preferred threshold of 10% for predicting TTR. The findings could assist physicians in effectively weighing the benefits and risks of adjuvant endocrine therapy for patients with ER < 10% disease, particularly in cases involving severe adverse events. Further prospective studies are warranted to validate the recommended cutoff value.