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

Abstract

Abstract 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.