Systemic inflammation markers and axillary involvement in early breast cancer: A retrospective cross-sectional study

Authors

Abstract

Aim This study aimed to evaluate the predictive value of preoperative systemic inflammation indices—Systemic Immune-Inflammation Index (SII), Neutrophil- to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR), and Monocyte-to-Lymphocyte Ratio (MLR)—for axillary lymph node involvement in patients with early-stage breast cancer.
Materials and Methods In this retrospective, cross-sectional study, data from 334 patients who underwent surgery for early breast cancer between January 2015 and January 2023 were analyzed. Preoperative hematologic parameters and postoperative axillary status were collected. ROC analysis and logistic regression were used to assess the diagnostic performance and predictive value of each marker.
Results Among the evaluated markers, only SII was found to be an independent predictor of axillary metastasis in multivariate analysis (OR: 1.00, 95% CI: 1.00– 1.03, p = 0.002). NLR showed significance in univariate analysis but lost statistical relevance after adjustment (p = 0.741). PLR and MLR did not demonstrate predictive utility. ROC analysis revealed limited discriminatory power for all markers (AUC < 0.50).
Discussion SII appears to be an independent predictor of axillary lymph node metastasis in early-stage breast cancer, whereas NLR, PLR, and MLR showed limited prognostic value. These findings highlight the potential role of SII in preoperative risk assessment, warranting further validation in large-scale prospective studies.

Keywords

Introduction

Breast cancer is the most commonly diagnosed cancer worldwide, with an estimated 2.26 million new cases recorded in 2020, and it remains the leading cause of cancer-related death among women . Axillary lymph node metastasis is frequently observed in breast cancer and serves as a major prognostic factor in early-stage disease . Many studies have sought to identify predictors of axillary metastasis and have proposed various risk estimation models . Inflammatory responses play a crucial role in the development and progression of various malignancies, including breast cancer .
Cancer-related inflammation promotes angiogenesis, metastasis, and supports tumor cell proliferation and survival. Recent evidence also suggests a strong relationship between inflammatory activity and lymph node metastasis in breast cancer . The systemic immune-inflammation index (SII), a relatively novel biomarker integrating neutrophil, platelet, and lymphocyte counts, has been reported as a promising prognostic indicator in cancer, as it comprehensively reflects the host’s inflammatory and immune status . In addition, other hematological ratios such as platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and neutrophil-to- lymphocyte ratio (NLR) have been investigated as prognostic, predictive, and metastatic indicators in several studies . High PLR and pre-treatment NLR levels have been associated with increased lymph node metastasis and advanced tumor stage, respectively, while lower SII values have been linked to improved prognosis in both colorectal and breast cancers . Therefore, in this study, we aimed to evaluate the predictive performance of SII, NLR, PLR, and MLR for axillary metastasis and to compare their relative diagnostic utility.

Materials and Methods

Study Design and Patients
The present study was conducted as a single-arm, cross-sectional, retrospective study. A retrospective review was conducted using the hospital’s database for patients who underwent surgery for breast cancer at the General Surgery Department of Derince Training and Research Hospital, University of Health Sciences, between January 2015 and January 2023. Patients diagnosed with early-stage breast cancer—stages 1A, 1B, 2A, and 2B according to final pathological TNM staging—were evaluated for inclusion in the study. Patients with advanced-stage breast cancer, preoperative immunodeficiency or related conditions, those who had received neoadjuvant chemotherapy, and those with hematologic disorders were excluded to avoid potential confounding effects on hematologic parameters.
All patients who met the inclusion criteria and underwent surgery for breast cancer were identified through the hospital database, and their data were recorded for statistical analysis. The data included demographic characteristics, tumor features, preoperative white blood cell, neutrophil, lymphocyte, platelet, and monocyte counts, and postoperative axillary lymph node involvement. The systemic immune-inflammation index (SII) was calculated using the formula: SII = (platelet count × neutrophil count) / lymphocyte count. The platelet-to-lymphocyte ratio (PLR) was calculated as: PLR = platelet count/lymphocyte count. The neutrophil-to-lymphocyte ratio (NLR) was calculated as: NLR = neutrophil count / lymphocyte count. The monocyte- to-lymphocyte ratio (MLR) was calculated as: MLR = monocyte count/lymphocyte count.
Outcomes
The primary outcome was to determine whether preoperative inflammatory markers are associated with the presence of axillary lymph node metastasis. Secondary outcomes were to evaluate the diagnostic performance of these markers and to identify independent predictors of axillary metastasis using multivariate logistic regression.
Statistical Analyses
Descriptive statistics were presented as counts and percentages for categorical variables and as mean ± standard deviation or median (interquartile range: 25th–75th percentile) for continuous variables. Normal distribution was assessed using histograms, Q–Q plots, and normality tests. Categorical variables were compared using the Pearson chi-square test or Fisher’s exact test, where appropriate. For contingency tables larger than 2×2 with a high number of expected values <5, the Fisher–Freeman–Halton test was applied. For continuous variables, the independent samples t-test or the Mann–Whitney U test was used depending on the distribution. Receiver Operating Characteristic (ROC) curve analysis was used to determine the optimal cut-off values of PLR, NLR, MLR, and SII for predicting axillary metastasis. Univariate and multivariate logistic regression analyses were conducted to identify risk factors associated with axillary metastasis. Risk was expressed as odds ratios with 95% confidence intervals (OR, 95% CI). A two-tailed p-value <0.05 was considered statistically significant. All data analyses and visualizations were performed using R software version 4.2.3 (https://www.r-project.org/).
Ethical Approval
This study was approved by the Ethics Committee of Kocaeli City Hospital (Date: 2023-09-01, No: 2023/9).

Results

A total of 334 female patients, with a mean age of 55.8 years (range, 25–88 years), were included in the study. Of these, 130 patients (38.9%) were premenopausal and 204 (61.1%) were postmenopausal. A family history of breast cancer was present in 25 patients (7.48%), while 309 patients (92.52%) had no such history. While 261 patients (78.1%) had no history of smoking, 73 (21.9%) reported a history of smoking. No statistically significant difference was observed in the demographic variables in relation to axillary lymph node metastasis. Compared to Stage 1, Stage 2a and 2b were associated with significantly higher risks of metastasis (OR: 6.87, 95% CI: 1.60–29.59, p < 0.001, and OR: 2940.0, 95% CI: 164.0–52,707.0, p < 0.001, respectively). In terms of molecular subtypes, both Luminal B Her2− and Luminal B Her2+ were significantly associated with increased risk of metastasis compared to Luminal A (OR: 2.02, 95% CI: 1.11–3.77, p = 0.031 and OR: 2.59, 95% CI: 1.19–5.72, p = 0.031, respectively). The presence of lymphovascular invasion was a strong predictor of metastasis (OR: 11.5, 95% CI: 6.82– 19.7, p < 0.001), and perineural invasion was also significantly associated with increased risk (OR: 2.89, 95% CI: 1.75–4.82, p < 0.001). Patients with histologic Grade 2 tumors had a significantly higher risk compared to those with Grade 1 tumors (OR: 2.17, 95% CI: 1.27–3.80, p = 0.015), while Grade 3 tumors did not show a statistically significant increase. No statistically significant association was found between T stage groups and axillary metastasis (p = 0.120), (Table 1). The predictive performance of inflammatory markers for axillary involvement was evaluated using ROC analysis (Table 2) (Figure 1). PLR had an AUC of 0.49 (95% CI: 0.43–0.56) with a cut-off value of 171.5, showing a sensitivity of 22% and specificity of 86%. MLR demonstrated an AUC of 0.49 (95% CI: 0.43–0.56) with a sensitivity of 23% and specificity of 81% at a threshold of 0.31. NLR showed high sensitivity (99%) but poor specificity (1%) at a cut-off of 0.56, with an AUC of 0.42 (95% CI: 0.36–0.49). SII had the lowest AUC at 0.41 (95% CI: 0.35–0.47), with a sensitivity of 1% and specificity of 100% at a threshold of 1607.11. Overall, none of the markers demonstrated sufficient discriminatory power for clinical use.
In the univariate logistic regression analysis, an NLR greater than 0.56 was found to be significantly associated with a lower likelihood of axillary involvement (OR: 0.74, 95% CI: 0.57–0.97, p = 0.028), suggesting a potential protective role (Table 3). Systemic immune-inflammation index greater than 1607.11 was also significantly associated with axillary metastasis (OR: 1.00, 95% CI: 1.00–1.04, p = 0.009), albeit with a marginal odds ratio. Other variables, including age > 70, PLR > 171.5, and MLR > 0.31, did not show significant associations in univariate models. In the multivariate analysis, after adjusting for confounders, only SII remained an independent predictor of axillary metastasis (OR: 1.00, 95% CI: 1.00–1.03, p = 0.002), indicating that systemic inflammation may play a meaningful role in tumor spread. The effect of NLR was no longer statistically significant (OR: 0.96, 95% CI: 0.75–1.22, p = 0.741), suggesting that its apparent univariate association may have been confounded by other inflammatory parameters.

Discussion

Our study shows SII is an independent risk factor for axillary lymph node metastasis in early-stage breast cancer. The immune- inflammatory microenvironment significantly contributes to tumor progression and metastasis . Several studies have shown that the systemic immune-inflammation index (SII), a relatively novel marker based on neutrophil, lymphocyte, and platelet counts, serves as a potential prognostic indicator in various tumors, with evidence suggesting its predictive value for overall survival and disease outcomes in breast cancer, outperforming traditional markers like NLR and PLR, particularly in patients receiving neoadjuvant chemotherapy . A recent meta-analysis demonstrated that both elevated SII are significant predictors of poor overall and disease-free survival in breast cancer patients, reinforcing the prognostic relevance of systemic inflammatory markers. In line with this, our study also investigated the role of various preoperative inflammatory indices, including NLR, PLR, MLR, and SII, in predicting axillary lymph node metastasis. Although NLR showed a statistically significant association with axillary involvement in univariate analysis (p = 0.028), this association lost significance after adjustment for confounders in multivariate analysis (p = 0.741). This suggests that the prognostic role of NLR may be limited when considered independently and potentially influenced by other overlapping inflammatory pathways. In contrast, SII remained an independent predictor of axillary metastasis in our cohort, supporting the growing body of evidence favoring its clinical utility.
Studies have indicated that elevated PLR levels are associated with an increased risk of lymph node metastasis in patients with T1-stage breast cancer . In our study, although PLR was evaluated for its predictive value in axillary metastasis, it did not show a statistically significant association, suggesting limited utility of PLR as an independent marker in early- stage breast cancer. In a retrospective study of cT1N0 breast cancer patients, Yang et al. identified high PLR levels and the presence of vascular tumor thrombus as independent risk factors for sentinel lymph node metastasis, while NLR did not retain significance in multivariate analysis . In contrast, our study found no statistically significant association between PLR and axillary lymph node involvement, suggesting that the predictive utility of PLR may vary across different breast cancer populations or clinical settings.

Limitations

This study has several limitations. First, its retrospective and single-center design may introduce selection bias and limit the generalizability of the findings. Second, we did not evaluate long-term outcomes such as overall or disease-free survival, which would provide more insight into the prognostic value of inflammatory markers. Finally, the lack of external validation limits the ability to apply the findings universally.

Conclusion

In conclusion, our findings suggest that among the evaluated systemic inflammatory markers, only SII demonstrated independent predictive value for axillary lymph node metastasis in early-stage breast cancer. While NLR and PLR have shown potential in previous studies, their predictive strength was not confirmed in our cohort. These results highlight the importance of SII as a clinically relevant biomarker and support further investigation into its role in preoperative risk stratification. Further large-scale prospective studies are needed to confirm these results and evaluate their generalizability in clinical practice.

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