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ORIGINAL RESEARCH

Predictive Significance of Systemic Immune-Inflammation Index in Patients with Breast Cancer: A Retrospective Cohort Study

ORCID Icon, , , , , , , , , , , , & show all
Pages 939-960 | Received 06 Aug 2023, Accepted 09 Nov 2023, Published online: 15 Nov 2023

Figures & data

Figure 1 Conceptual framework of the study. Immuno-inflammatory cells play pivotal roles in tumorigenesis and progression. α-granules released by platelets in the TME promote tumor angiogenesis and boost metastasis of breast cancer cells. Through an intimate cellular interaction with platelets and endothelial cells, neutrophils are tethered to the vascular endothelial cells and migrate from the vascular compartment to the tissue. Subsequently, activated neutrophils produce a large amount of ROS, which together with ARG1 suppress the antitumor function of lymphocytes and NK cells. Peripheral blood inflammation indices reflect the level of local immune inflammation in the TME. These parameters collected before, during, and after initial treatment may aid in precision medicine in patients with breast cancer.

Abbreviations: NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; SII, systemic immune-inflammation index; TME, tumor microenvironment; CBC, complete blood count; ROS, reactive oxygen species; ARG1, arginase 1; NK, natural killer; IL, interleukin.
Figure 1 Conceptual framework of the study. Immuno-inflammatory cells play pivotal roles in tumorigenesis and progression. α-granules released by platelets in the TME promote tumor angiogenesis and boost metastasis of breast cancer cells. Through an intimate cellular interaction with platelets and endothelial cells, neutrophils are tethered to the vascular endothelial cells and migrate from the vascular compartment to the tissue. Subsequently, activated neutrophils produce a large amount of ROS, which together with ARG1 suppress the antitumor function of lymphocytes and NK cells. Peripheral blood inflammation indices reflect the level of local immune inflammation in the TME. These parameters collected before, during, and after initial treatment may aid in precision medicine in patients with breast cancer.

Figure 2 Patient flowchart.

Abbreviation: NAC, neoadjuvant chemotherapy.
Figure 2 Patient flowchart.

Table 1 Clinicopathological Characteristics of All 1489 Patients with Breast Cancer

Table 2 The Correlation Between Pretherapeutic NLR/PLR/SII and Clinicopathological Characteristics Among All 1489 Patients with Breast Cancer

Table 3 Clinicopathological Characteristics of 258 Patients Undergoing Neoadjuvant Chemotherapy

Table 4 Univariate and Multivariable Analysis for Risk Factors of Poor Chemotherapy Response

Figure 3 Univariate and multivariate analyses of pathological complete response by forest plots. P: p-value, bold p-value indicated a statistical difference. Other bold text represents methods or variables for regression analysis.

Abbreviations: OR, odds ratio; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; SII, systemic immune-inflammation index; AJCC, American Joint Committee on Cancer; IDC, invasive ductal carcinoma; ER, estrogen receptor; PR, progesterone receptor; HER2, human epidermal growth factor receptor 2.
Figure 3 Univariate and multivariate analyses of pathological complete response by forest plots. P: p-value, bold p-value indicated a statistical difference. Other bold text represents methods or variables for regression analysis.

Table 5 The Predictive Scoring System for Breast Cancer Chemotherapy Efficacy

Figure 4 The newly established predictive scoring model efficiently predicts poor chemotherapeutic response in breast cancer patients. (a) Receiver operating characteristic (ROC) and area under the curve (AUC) analyses pertaining to pretherapeutic systemic immune-inflammation index (SII)-based predictive scoring model. (b) Comparison between the SII-based predictive scoring model and other models. Figure 4 was generated by GraphPad Prism version 8.

Abbreviations: HER2, human epidermal growth factor receptor 2; CI, confidence interval; P, p-value.
Figure 4 The newly established predictive scoring model efficiently predicts poor chemotherapeutic response in breast cancer patients. (a) Receiver operating characteristic (ROC) and area under the curve (AUC) analyses pertaining to pretherapeutic systemic immune-inflammation index (SII)-based predictive scoring model. (b) Comparison between the SII-based predictive scoring model and other models. Figure 4 was generated by GraphPad Prism version 8.

Table 6 The Accuracy of the Predictive Scoring Model Tested by an Independent Cohort

Table 7 Dynamic Changes of NLR/PLR/SII Before, During, and After Initial Treatment