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Clinical Medicine | Publishing Language: Chinese | Open Access

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

Chengfang WANGYuqin ZHOUYanling ZHANGXiaowei QIYi ZHANG( )
Department of Breast and Thyroid Surgery, First Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
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Abstract

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 1962 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.

CLC number: R392.11; R730.7; R737.9 Document code: A

References

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Journal of Army Medical University
Pages 2792-2804

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Cite this article:
WANG C, ZHOU Y, ZHANG Y, et al. 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. Journal of Army Medical University, 2025, 47(22): 2792-2804. https://doi.org/10.16016/j.2097-0927.202510028

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Received: 15 October 2025
Revised: 15 November 2025
Published: 30 November 2025
© 2025 Journal of Army Medical University

This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/).