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A novel estrogen receptor expression stratification (low/moderate/high) based on Chinese population provides more accurate prognosis prediction for HR+/HER2- early breast cancer patients
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Chengfang WANG, Yuqin ZHOU, Yanling ZHANG, Xiaowei QI, Yi ZHANG
Journal of Army Medical University | 2025, 47(22) : 2792 - 2804
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Journal of Army Medical University | 2025, 47(22): 2792-2804
• Clinical Medicine •
A novel estrogen receptor expression stratification (low/moderate/high) based on Chinese population provides more accurate prognosis prediction for HR+/HER2- early breast cancer patients
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Chengfang WANG, Yuqin ZHOU, Yanling ZHANG, Xiaowei QI, Yi ZHANG
Affiliations
  • 1Department of Breast and Thyroid Surgery,First Affiliated Hospital,Army Medical University (Third Military Medical University),Chongqing,China
Published: 2025-11-30 doi: 10.16016/j.2097-0927.202510028
Outline
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Objective

To stratify the estrogen receptor (ER) positive while human epidermal growth factor receptor 2 (HER2) negative breast cancer patients by the expression level of ER, providing new evidence for prognostic prediction and guiding precision endocrine therapy (ET) for those with different ER expression levels.

Methods

A retrospective cohort study was conducted on 1 962 ER-positive/HER2-negative breast cancer patients treated in our department from January 1, 2013 to December 31, 2018. X-tile was used to calculate the optimal cutoff point of ER expression level, and then based on the results, they were divided into low (1%~10%), moderate (11%~30%), and high expression (31%~100%) groups. After propensity score matching (PSM) was performed to balance baseline characteristics, their prognostic outcomes were compared and the responses to ET were analyzed in the groups. Cox proportional risk regression model was applied to analyze the prognostic factors, and subgroup analysis was further performed.

Results

After PAM, 129 (11.5%) were assigned into a low ER expression group, 151 (13.5%) and 840 (75%) into moderate and high ER expression groups, respectively. Statistical differences were observed in disease-free survival (DFS) and overall survival (OS) among the 3 groups (P=8e-6, P=8e-14). In the low ER expression group, the patients treated with selective estrogen receptor modulators (SERMs) showed no significant differences in DFS and OS than those treated with aromatase inhibitors (AIs) (P>0.05). However, the patients from the moderate and high ER expression groups demonstrated significantly better DFS when treated with AI than with SERM (P=0.02, P=0.03). Multivariate analysis showed that compared with the moderate ER expression group, the high ER expression group exhibited significantly lower risk of disease recurrence/metastasis (HR=0.62, 95%CI: 0.43~0.88, P=0.009) and risk of death (HR=0.49, 95%CI: 0.26~0.93, P=0.03). Subgroup analysis revealed that when compared with the high ER expression group, the moderate ER expression group exhibited notably worse DFS in the following subgroups: oral SERM, non-breast-conserving surgery, lymph node metastasis, TNM stage Ⅱ, and chemotherapy, and shorter OS in the subgroups of oral SERM, non-breast-conserving surgery, lymph node metastasis, TNM stage Ⅱ subgroup, and chemotherapy.

Conclusion

Taking ER expression of 11%~30% as an independent stratification criterion can guide more accurate prognostic assessment and more rational ET selection in ER-positive/HER2-negative breast cancer patients.

breast cancer  /  estrogen receptor  /  stratification by expression level  /  endocrine therapy  /  prognosis
王成方, 周于钦, 张艳玲, 齐晓伟, 张毅. 基于中国人群的雌激素受体表达新分层(低/中/高)可更精准地预测HR+/HER2-早期乳腺癌患者的预后. 陆军军医大学学报, 2025 , 47 (22) : 2792 -2804 . DOI: 10.16016/j.2097-0927.202510028
Chengfang WANG, Yuqin ZHOU, Yanling ZHANG, Xiaowei QI, Yi ZHANG. A novel estrogen receptor expression stratification (low/moderate/high) based on Chinese population provides more accurate prognosis prediction for HR+/HER2- early breast cancer patients[J]. Journal of Army Medical University, 2025 , 47 (22) : 2792 -2804 . DOI: 10.16016/j.2097-0927.202510028
Year 2025 volume 47 Issue 22
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doi: 10.16016/j.2097-0927.202510028
  • Receive Date:2025-10-15
  • Online Date:2026-10-30
  • Published:2025-11-30
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  • Received:2025-10-15
  • Revised:2025-11-15
Affiliations
    1Department of Breast and Thyroid Surgery,First Affiliated Hospital,Army Medical University (Third Military Medical University),Chongqing,China
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表12种不同金属材料的力学参数
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Family
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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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