外周血炎症指标NLR、PLR、LMR、SII在 乳腺癌中的作用
The Role of Peripheral Blood Inflammatory Markers NLR, PLR, LMR, and SII in Breast Cancer
DOI: 10.12677/acm.2026.1652136, PDF,   
作者: 李子鹏：赣南医科大学研究生院第一临床医学院，江西 赣州
关键词: NLR；PLR；LMR；SII；乳腺癌；肿瘤微环境；预后评估；NLR； PLR； LMR； SII； Breast Cancer； Tumor Microenvironment； Prognostic Assessment
摘要: 外周血炎症指标中性粒细胞与淋巴细胞比值(NLR)、血小板与淋巴细胞比值(PLR)、淋巴细胞与单核细胞比值(LMR)及全身免疫炎症指数(SII = 血小板 × 中性粒细胞/淋巴细胞)等作为系统性炎症的生物标志物，反映肿瘤微环境(TME)中免疫与炎症的动态平衡。在乳腺癌预后评估和治疗反应预测中体现出重要价值。本文旨在系统综述上述指标在乳腺癌预后评估及新辅助治疗反应预测中的研究进展、临床价值与现存挑战。多项研究证实，NLR、PLR、LMR和SII均可作为独立预后因子，与病理完全缓解(pCR)率、腋窝淋巴结转移风险及生存结局显著相关。综合分析提示，这些低成本、易获取的指标具有临床辅助决策能力，但其临界值标准化及多模态联合应用仍需前瞻性研究。
Abstract: Peripheral blood inflammatory markers such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and systemic immune-inflammation index (SII = platelets × neutrophils/lymphocytes) serve as biomarkers of systemic inflammation, reflecting the dynamic balance of immunity and inflammation in the tumor microenvironment (TME). They have shown significant value in breast cancer prognosis evaluation and treatment response prediction. This article aims to systematically review the research progress, clinical value, and existing challenges of these markers in breast cancer prognosis assessment and neoadjuvant treatment response prediction. Multiple studies have confirmed that NLR, PLR, LMR, and SII can serve as independent prognostic factors, significantly associated with the rate of pathological complete response (pCR), the risk of axillary lymph node metastasis, and survival outcomes. Overall analysis suggests that these low-cost and easily obtainable markers have potential clinical decision-making utility, but the standardization of their cutoff values and their combined use in multimodal approaches still require prospective studies.
文章引用：李子鹏. 外周血炎症指标NLR、PLR、LMR、SII在 乳腺癌中的作用[J]. 临床医学进展, 2026, 16(5): 3176-3184. https://doi.org/10.12677/acm.2026.1652136

参考文献

[1] Bray, F., Laversanne, M., Sung, H., Ferlay, J., Siegel, R.L., Soerjomataram, I., et al. (2024) Global Cancer Statistics 2022: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: A Cancer Journal for Clinicians, 74, 229-263. [Google Scholar] [CrossRef] [PubMed]
[2] Balkwill, F. and Mantovani, A. (2001) Inflammation and Cancer: Back to Virchow? The Lancet, 357, 539-545. [Google Scholar] [CrossRef] [PubMed]
[3] Elhanani, O., Ben-Uri, R. and Keren, L. (2023) Spatial Profiling Technologies Illuminate the Tumor Microenvironment. Cancer Cell, 41, 404-420. [Google Scholar] [CrossRef] [PubMed]
[4] Briukhovetska, D., Dörr, J., Endres, S., Libby, P., Dinarello, C.A. and Kobold, S. (2021) Interleukins in Cancer: From Biology to Therapy. Nature Reviews Cancer, 21, 481-499. [Google Scholar] [CrossRef] [PubMed]
[5] Fridman, W.H., Zitvogel, L., Sautès-Fridman, C. and Kroemer, G. (2017) The Immune Contexture in Cancer Prognosis and Treatment. Nature Reviews Clinical Oncology, 14, 717-734. [Google Scholar] [CrossRef] [PubMed]
[6] Arneth, B. (2019) Tumor Microenvironment. Medicina, 56, Article No. 15. [Google Scholar] [CrossRef] [PubMed]
[7] Hui, L. and Chen, Y. (2015) Tumor Microenvironment: Sanctuary of the Devil. Cancer Letters, 368, 7-13. [Google Scholar] [CrossRef] [PubMed]
[8] Wang, Z., Hu, H., Bao, Y., Pang, L. and Yang, C. (2025) Neutrophils in Cancer: From Immune Defense to Tumor Promotion. Cancer Biology & Medicine, 22, 59-617.
[9] Xiong, S., Dong, L. and Cheng, L. (2021) Neutrophils in Cancer Carcinogenesis and Metastasis. Journal of Hematology & Oncology, 14, 173. [Google Scholar] [CrossRef] [PubMed]
[10] Xie, J., Guo, Z., Zhu, Y., Ma, M. and Jia, G. (2023) Peripheral Blood Inflammatory Indexes in Breast Cancer: A Review. Medicine, 102, e36315. [Google Scholar] [CrossRef] [PubMed]
[11] Kraja, F.P., Jurisic, V.B., Hromić-Jahjefendić, A., Rossopoulou, N., Katsila, T., Mirjacic Martinovic, K., et al. (2025) Tumor-Infiltrating Lymphocytes in Cancer Immunotherapy: From Chemotactic Recruitment to Translational Modeling. Frontiers in Immunology, 16, Article ID: 1601773. [Google Scholar] [CrossRef] [PubMed]
[12] Jackson, C.M., Pant, A., Dinalankara, W., Choi, J., Jain, A., Nitta, R., et al. (2024) The Cytokine Meteorin-Like Inhibits Anti-Tumor CD8+ T Cell Responses by Disrupting Mitochondrial Function. Immunity, 57, 1864-1877.e9. [Google Scholar] [CrossRef] [PubMed]
[13] Hendry, S., Salgado, R., Gevaert, T., Russell, P.A., John, T., Thapa, B., et al. (2017) Assessing Tumor-Infiltrating Lymphocytes in Solid Tumors: A Practical Review for Pathologists and Proposal for a Standardized Method from the International Immunooncology Biomarkers Working Group: Part 1: Assessing the Host Immune Response, TILs in Invasive Breast Carcinoma and Ductal Carcinoma in Situ, Metastatic Tumor Deposits and Areas for Further Research. Advances in Anatomic Pathology, 24, 235-251. [Google Scholar] [CrossRef] [PubMed]
[14] Fernández-Nogueira, P., Fuster, G., Gutierrez-Uzquiza, Á., Gascón, P., Carbó, N. and Bragado, P. (2021) Cancer-Associated Fibroblasts in Breast Cancer Treatment Response and Metastasis. Cancers, 13, Article No. 3146. [Google Scholar] [CrossRef] [PubMed]
[15] Pan, Y., Yu, Y., Wang, X. and Zhang, T. (2020) Tumor-Associated Macrophages in Tumor Immunity. Frontiers in Immunology, 11, Article ID: 583084. [Google Scholar] [CrossRef] [PubMed]
[16] Osterberg, N., Ferrara, N., Vacher, J., Gaedicke, S., Niedermann, G., Weyerbrock, A., et al. (2016) Decrease of VEGF-A in Myeloid Cells Attenuates Glioma Progression and Prolongs Survival in an Experimental Glioma Model. Neuro-Oncology, 18, 939-949. [Google Scholar] [CrossRef] [PubMed]
[17] Liu, W. and Luo, G. (2024) NEDD9 Is Transcriptionally Regulated by HDAC4 and Promotes Breast Cancer Metastasis and Macrophage M2 Polarization via the FAK/NF-κB Signaling Pathway. Neoplasia, 57, Article ID: 101059. [Google Scholar] [CrossRef] [PubMed]
[18] Li, J., Wang, S., Wang, N., Zheng, Y., Yang, B., Wang, X., et al. (2021) Aiduqing Formula Inhibits Breast Cancer Metastasis by Suppressing TAM/CXCL1-Induced Treg Differentiation and Infiltration. Cell Communication and Signaling, 19, Article No. 89. [Google Scholar] [CrossRef] [PubMed]
[19] Tian, Y., Zong, Y., Pang, Y., Zheng, Z., Ma, Y., Zhang, C., et al. (2025) Platelets and Diseases: Signal Transduction and Advances in Targeted Therapy. Signal Transduction and Targeted Therapy, 10, Article No. 159. [Google Scholar] [CrossRef] [PubMed]
[20] Sylman, J.L., Mitrugno, A., Tormoen, G.W., Wagner, T.H., Mallick, P. and McCarty, O.J.T. (2017) Platelet Count as a Predictor of Metastasis and Venous Thromboembolism in Patients with Cancer. Convergent Science Physical Oncology, 3, Article ID: 023001. [Google Scholar] [CrossRef] [PubMed]
[21] Wicki, A.N. and Clemetson, K.J. (1987) The Glycoprotein Ib Complex of Human Blood Platelets. European Journal of Biochemistry, 163, 43-50. [Google Scholar] [CrossRef] [PubMed]
[22] Miao, Y., Xu, Z., Feng, W., Zheng, M., Xu, Z., Gao, H., et al. (2022) Platelet Infiltration Predicts Survival in Postsurgical Colorectal Cancer Patients. International Journal of Cancer, 150, 509-520. [Google Scholar] [CrossRef] [PubMed]
[23] Cullinane, C., Creavin, B., O’Leary, D.P., O’Sullivan, M.J., Kelly, L., Redmond, H.P., et al. (2020) Can the Neutrophil to Lymphocyte Ratio Predict Complete Pathologic Response to Neoadjuvant Breast Cancer Treatment? A Systematic Review and Meta-Analysis. Clinical Breast Cancer, 20, e675-e681. [Google Scholar] [CrossRef] [PubMed]
[24] Chen, X., Ye, H., Xu, D., Chen, S., Wu, W., Qian, X., et al. (2025) Pathological Complete Response and Prognostic Predictive Factors of Neoadjuvant Chemoimmunotherapy in Early Stage Triple-Negative Breast Cancer. Frontiers in Immunology, 16, Article ID: 1570394. [Google Scholar] [CrossRef] [PubMed]
[25] 李小敏. 治疗前外周血中性粒细胞与淋巴细胞比值和肿瘤浸润淋巴细胞对乳腺癌患者新辅助化疗疗效和预后的预测价值[D]: [硕士学位论文]. 成都: 四川大学, 2021.
[26] 潘婉婉, 董孟浩, 余发智, 宛凌峰, 吴德林, 刘峰, 孟凡伦, 马小鹏. 外周血炎症指标NLR、PLR、LMR预测乳腺癌新辅助化疗疗效的价值[J]. 中华全科医学, 2021, 19(9): 1442-1446.
[27] 郭婉莹, 畅昶, 刘起鹏, 邓淼. 中性粒细胞与淋巴细胞比值对乳腺癌新辅助治疗的疗效预测[J]. 罕少疾病杂志, 2025(4): 33-35.
[28] Yang, L., Wang, H., Ma, J., Hao, J., Zhang, C., Ma, Q. and Wang, B. (2021) Association between the Platelet to Lymphocyte Ratio, Neutrophil to Lymphocyte Ratio and Axillary Lymph Node Metastasis in cT1N0 Breast Cancer Patients. American Journal of Translational Research, 13, 1854-1861.
[29] 李娟, 李婵, 李阔, 郑新宇. 中性粒细胞与淋巴细胞比值在女性乳腺癌患者腋窝淋巴结转移中判断价值[J]. 临床军医杂志, 2021(5): 578-579+581.
[30] 冯帆, 王一刻, 张峰. 术前外周血中性粒细胞/淋巴细胞比值对早期乳腺癌患者非前哨淋巴结转移的预测分析[J]. 浙江中西医结合杂志, 2021(6): 549-553.
[31] 杨柳, 涂剑宏, 陈月霞, 周国凤, 龚丹, 黄梦怡. 术前NLR对浸润性乳腺癌腋窝淋巴结转移预测价值研究[J]. 齐齐哈尔医学院学报, 2024(23): 2280-2284.
[32] Chen, C., Yang, H., Cai, D., Xiang, L., Fang, W. and Wang, R. (2021) Preoperative Peripheral Blood Neutrophil-to-Lymphocyte Ratios (NLR) and Platelet-to-Lymphocyte Ratio (PLR) Related Nomograms Predict the Survival of Patients with Limited-Stage Small-Cell Lung Cancer. Translational Lung Cancer Research, 10, 866-877. [Google Scholar] [CrossRef] [PubMed]
[33] Zhang, L., Shi, F.Y., Qin, Q., Liu, G.X., Zhang, H.W., Yan, J., et al. (2022) Relationship between Preoperative Inflammatory Indexes and Prognosis of Patients with Rectal Cancer and Establishment of Prognostic Nomogram Prediction Model. Chinese Journal of Oncology, 44, 402-409. (In Chinese)
[34] 王雪莲, 郭宝良. PLR与乳腺癌预后的关系[J]. 医学信息, 2020(6): 40-42.
[35] Qi, X., Chen, J., Wei, S., Ni, J., Song, L., Jin, C., et al. (2023) Prognostic Significance of Platelet-to-Lymphocyte Ratio (PLR) in Patients with Breast Cancer Treated with Neoadjuvant Chemotherapy: A Meta-Analysis. BMJ Open, 13, e074874. [Google Scholar] [CrossRef] [PubMed]
[36] Gong, Z., Xin, R., Li, L., Lv, L. and Wu, X. (2022) Platelet-to-Lymphocyte Ratio Associated with the Clinicopathological Features and Prognostic Value of Breast Cancer: A Meta-Analysis. The International Journal of Biological Markers, 37, 339-348. [Google Scholar] [CrossRef] [PubMed]
[37] 胡传朋, 杨俊, 汪俊, 陈立权, 荣枫. 术前外周血NLR PLR对cT1-2N0M0乳腺癌腋窝淋巴结转移的预测价值[J]. 安徽医学, 2022(2): 191-195.
[38] 王海龙, 王运昌, 张芳, 张周龙, 梅文娟. 超声引导下穿刺活检及NLR、PLR对乳腺癌腋窝淋巴结转移的诊断价值[J]. 实用癌症杂志, 2023(11): 1891-1894.
[39] Ishizuka, Y., Horimoto, Y., Nakamura, M., Arakawa, A., Fujita, T., Iijima, K., et al. (2020) Predictive Factors for Non-Sentinel Nodal Metastasis in Patients with Sentinel Lymph Node-Positive Breast Cancer. Anticancer Research, 40, 4405-4412. [Google Scholar] [CrossRef] [PubMed]
[40] Wang, H., Huang, Z., Xu, B., Zhang, J., He, P., Gao, F., et al. (2024) The Predictive Value of Systemic Immune-Inflammatory Markers before and after Treatment for Pathological Complete Response in Patients Undergoing Neoadjuvant Therapy for Breast Cancer: A Retrospective Study of 1994 Patients. Clinical and Translational Oncology, 26, 1467-1479. [Google Scholar] [CrossRef] [PubMed]
[41] Ma, Y., Zhang, J. and Chen, X. (2021) Lymphocyte-to-Monocyte Ratio Is Associated with the Poor Prognosis of Breast Cancer Patients Receiving Neoadjuvant Chemotherapy. Cancer Management and Research, 13, 1571-1580. [Google Scholar] [CrossRef] [PubMed]
[42] Dong, J., Sun, Q., Pan, Y., Lu, N., Han, X. and Zhou, Q. (2021) Pretreatment Systemic Inflammation Response Index Is Predictive of Pathological Complete Response in Patients with Breast Cancer Receiving Neoadjuvant Chemotherapy. BMC Cancer, 21, Article No. 700. [Google Scholar] [CrossRef] [PubMed]
[43] Hu, B., Yang, X., Xu, Y., Sun, Y., Sun, C., Guo, W., et al. (2014) Systemic Immune-Inflammation Index Predicts Prognosis of Patients after Curative Resection for Hepatocellular Carcinoma. Clinical Cancer Research, 20, 6212-6222. [Google Scholar] [CrossRef] [PubMed]
[44] Zhu, M., Chen, L., Kong, X., Wang, X., Li, X., Fang, Y., et al. (2022) The Systemic Immune-Inflammation Index Is an Independent Predictor of Survival in Breast Cancer Patients. Cancer Management and Research, 14, 775-820. [Google Scholar] [CrossRef] [PubMed]
[45] Gu, Q., Zhao, J., Liu, Y., Chen, H. and Wang, L. (2023) Association between the Systemic Immune-Inflammation Index and the Efficacy of Neoadjuvant Chemotherapy, Prognosis in HER2 Positive Breast Cancer—A Retrospective Cohort Study. Gland Surgery, 12, 609-618. [Google Scholar] [CrossRef] [PubMed]
[46] Zhou, Y., Guo, X., Shen, L., Liu, K., Sun, Q., Wang, Y., et al. (2023) Predictive Significance of Systemic Immune-Inflammation Index in Patients with Breast Cancer: A Retrospective Cohort Study. OncoTargets and Therapy, 16, 939-960. [Google Scholar] [CrossRef] [PubMed]
[47] Liu, X., Yan, G., Pang, J., Xiao, Z. and Xie, H. (2025) The Systemic Immune-Inflammation Index Is a Predictor of Chemotherapy Sensitivity and Disease-Free Survival in Patients with Hormone Receptor-Positive Human Epidermal Growth Factor Receptor 2-Negative Breast Cancer. Clinical Breast Cancer, 25, e190-e195. [Google Scholar] [CrossRef] [PubMed]
[48] Tong, L., Wang, S., Zhang, R., Wu, Y., Xu, D. and Chen, L. (2023) High Levels of SII and PIV Are the Risk Factors of Axillary Lymph Node Metastases in Breast Cancer: A Retrospective Study. International Journal of General Medicine, 16, 2211-2218. [Google Scholar] [CrossRef] [PubMed]
[49] Ciurescu, S., Tomescu, L., Șerban, D., Nicolae, N., Nan, G., Buciu, V., et al. (2025) The Prognostic Value of Systemic Inflammation Index in Breast Cancer: A Retrospective Study in Western Romania. Journal of Clinical Medicine, 14, Article No. 1081. [Google Scholar] [CrossRef] [PubMed]

为你推荐