Systemic Immune-Inflammation Index Is a Prognostic Factor for Breast Cancer Patients After Curative Resection

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

PURPOSE

Systemic immune-inflammatory markers have a certain predictive role in pathological complete response (pCR) after neoadjuvant treatment (NAT) in breast cancer. However, there is a lack of research exploring the predictive value of markers after treatment.

METHODS

This retrospective study collected data from 1994 breast cancer patients who underwent NAT. Relevant clinical and pathological characteristics were included, and pre- and post-treatment complete blood cell counts were evaluated to calculate four systemic immune-inflammatory markers: neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and systemic immune-inflammation index (SII). The optimal cutoff values for these markers were determined using ROC curves, and patients were classified into high-value and low-value groups based on these cutoff values. Univariate and multivariate logistic regression analyses were conducted to analyze factors influencing pCR. The factors with independent predictive value were used to construct a nomogram.

RESULTS

After NAT, 383 (19.2%) patients achieved pCR. The area under the ROC curve is generally larger for post-treatment markers compared to pre-treatment markers. Pre-treatment NLR and PLR, as well as post-treatment LMR and SII, were identified as independent predictive factors for pCR, along with Ki-67, clinical tumor stage, clinical lymph node stage, molecular subtype, and clinical response. Higher pre-NLR (OR = 1.320; 95% CI 1.016-1.716; P = 0.038), pre-PLR (OR = 1.474; 95% CI 1.058-2.052; P = 0.022), post-LMR (OR = 1.532; 95% CI 1.175-1.996; P = 0.002), and lower post-SII (OR = 0.596; 95% CI 0.429-0.827; P = 0.002) are associated with a higher likelihood of achieving pCR. The established nomogram had a good predictive performance with an area under the ROC curve of 0.754 (95% CI 0.674-0.835).

CONCLUSION

Both pre- and post-treatment systemic immune-inflammatory markers have a significant predictive role in achieving pCR after NAT in breast cancer patients. Indeed, it is possible that post-treatment markers have stronger predictive ability compared to pre-treatment markers.

Systemic immune-inflammation index as a prognostic marker in HER2-positive breast cancer patients undergoing trastuzumab therapy

The prognostic value of SII (Systemic Immune-Inflammation Index) in HER-2-positive breast cancer (BC) patients, regardless of whether they receive trastuzumab treatment, and its potential value to distinguish patients who may benefit from trastuzumab therapy, warrant further investigation. Clinical data was collected from 797 HER-2-positive BC patients between July 2013 and March 2018. Baseline data differences were adjusted with propensity score matching. Univariate and multivariate analyses explored the correlation between clinical pathological factors, SII, and DFS. Four groups were established. Based on the baseline SII values of the participants, patients who did not receive trastuzumab treatment were divided into Group 1 (Low-SII) and Group 2 (High-SII), where SII had no predictive value for prognosis between groups. Participants who received trastuzumab treatment were also divided into two groups: the Low-SII group (Group 3) and the High-SII group (Group 4). The 5-year DFS was significantly higher in Group 3 than in Group 4 (91.76% vs. 82.76%, P = 0.017). Furthermore, multivariate analysis demonstrated a significant association between high SII and shorter DFS (HR = 3.430, 95% CI = 1.830-6.420, P < 0.001). In HER-2-positive BC patients treated with trastuzumab, those with lower SII showed a longer DFS, suggesting that SII may help in identifying patients who benefit from trastuzumab therapy.

Development of a Novel Inflammatory Index to Predict Coronary Artery Disease Severity in Patients With Acute Coronary Syndrome

The systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI) have previously demonstrated predictive value in coronary artery disease (CAD). We developed on an expanded, novel systemic immune-inflammation response index (SIIRI), calculated as peripheral neutrophil × monocyte × platelet ÷ lymphocyte count. We assessed 240 patients with an acute coronary syndrome that subsequently underwent percutaneous coronary intervention. CAD severity was measured using the SYNTAX score. Laboratory measurements, including cell counts, were obtained on admission. On multivariate analysis, the SIIRI was an independent predictor of severe CAD with an adjusted odds ratio (OR) of 1.666 [1.376-2.017] per 105-unit increase. The SIIRI had the highest area under the receiver operator curve of .771 [.709-.833] compared to the SII, SIRI neutrophil-lymphocyte ratio, monocyte-lymphocyte ratio, and platelet-lymphocyte ratio. The optimal cut-off for SIIRI was 4.3 × 105, with sensitivity = 69.9% and specificity = 75.8%. Increment in model performance resulting from adding SIIRI versus other inflammatory indices was assessed using discrimination, calibration, and goodness-of-fit measures. When added to a baseline model, the SIIRI resulted in a significant increase in the c-statistic and significant net reclassification index (.808, P < .0001) and integrated discrimination index (.129, P < .0001), and a decrease in Akaike and Bayesian information criteria.

Peripheral blood inflammatory indexes in breast cancer: A review

Immune and inflammatory responses play an important role in tumorigenesis and metastasis. Inflammation is an important component of the tumor microenvironment, and the changes in inflammatory cells may affect the occurrence and development of tumors. Complete blood count at the time of diagnosis and treatment can reflect the inflammatory status within the tumor. Studies have shown that the number of certain inflammatory cells in peripheral blood and their ratios are important prognostic factors for many malignancies, including neutrophil, lymphocyte, monocyte, and platelet counts, as well as neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, systemic immune-inflammation index, systemic inflammation response index and pan-immune-inflammation-value. The value of peripheral blood inflammation indexes in predicting the efficacy and prognosis of breast cancer neoadjuvant therapy is worth recognizing. This review details the application of peripheral blood inflammation indexes in the evaluation of efficacy and prediction of prognosis in neoadjuvant therapy for breast cancer, aiming to provide a more comprehensive reference for the comprehensive diagnosis and treatment of breast cancer.

Association between admission systemic immune-inflammation index and mortality in critically ill patients with sepsis: a retrospective cohort study based on MIMIC-IV database

Systemic immune-inflammation index (SII) has been identified as a prognostic biomarker for various diseases. Our study aimed to investigate the association between SII and mortality risk in critically ill patients with sepsis, thus exploring possible tools for rapid screening. This retrospective cohort study was conducted using clinical data extracted from the Medical Information Mart for Intensive Care Database. The study included only patients diagnosed with sepsis admitted to the intensive care unit for the first time. We used the restricted cubic splines to explore the relationship between SII and 28-day mortality. Kaplan-Meier curve and Cox regression models were performed to evaluate the association between SII and mortality. Subgroup analysis was performed to explore the stability of the primary results. A total of 16,007 patients with sepsis were eligible in the final analysis. We found a J-shaped relationship between SII and mortality risk. The SII level associated with the lowest mortality risk was 774.46*109/L. Compared with the reference group (second SII quartile), the 28-day mortality was increased in the highest quartile and third quartile groups of SII levels; fully adjusted HRs were 1.16 (1.02 to 1.32) and 1.40 (1.23 to 1.58), respectively. However, although the lower SII (Q1 group) also showed a trend toward a higher hazard of 28-day mortality, there was no statistical difference, with a fully adjusted HR of 1.05 (0.92 to 1.21). In the population of critically ill patients with sepsis, low and high SII levels were associated with an increased risk of short-term mortality. The 28-day mortality risk was lowest at SII levels of 774.46*109/L.

Association between systemic immune-inflammation index (SII) and survival outcome in patients with primary glioblastoma

The purpose was to evaluate the prognostic value of systemic immune-inflammation index (SII) in glioblastoma patients. A total of 100 patients were retrospectively analyzed. We performed Kaplan-Meier and Cox regression analyses to determine the prognostic significance of SII. A nomogram was constructed by incorporating independent prognostic variables. The predictive accuracies of nomograms were evaluated by Harrell concordance index (c-index) and receiver operating characteristic curve analysis; the clinical benefit was evaluated by decision curve analysis. A high SII (>510.8 × 109 cells/L) (hazard ratio = 1.672, P = .034) and neutrophil count (>3.9 × 109 cells/L) (hazard ratio = 1.923, P = .009) were independently related with poor outcome in glioblastoma patients based on Cox analysis. The nomogram incorporating SII showed a good predictive accuracy (c-index = 0.866). Preoperative SII and neutrophil count are potential prognostic biomarkers for overall survival in glioblastoma patients and the nomogram model that integrated the SII may be used to facilitate a comprehensive preoperative survival evaluation.

Identification of a tumor immune-inflammation signature predicting prognosis and immune status in breast cancer

Background

Breast cancer has become the malignancy with the highest mortality rate in female patients worldwide. The limited efficacy of immunotherapy as a breast cancer treatment has fueled the development of research on the tumor immune microenvironment.

Methods

In this study, data on breast cancer patients were collected from The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohorts. Differential gene expression analysis, univariate Cox regression analysis, and least absolute shrinkage and selection operator (LASSO) Cox regression analysis were performed to select overall survival (OS)-related, tumor tissue highly expressed, and immune- and inflammation-related genes. A tumor immune-inflammation signature (TIIS) consisting of 18 genes was finally screened out in the LASSO Cox regression model. Model performance was assessed by time-dependent receiver operating characteristic (ROC) curves. In addition, the CIBERSORT algorithm and abundant expression of immune checkpoints were utilized to clarify the correlation between the risk signature and immune landscape in breast cancer. Furthermore, the association of IL27 with the immune signature was analyzed in pan-cancer and the effect of IL27 on the migration of breast cancer cells was investigated since the regression coefficient of IL27 was the highest.

Results

A TIIS based on 18 genes was constructed via LASSO Cox regression analysis. In the TCGA-BRCA training cohort, 10-year AUC reached 0.89, and prediction performance of this signature was also validated in the METABRIC set. The high-risk group was significantly correlated with less infiltration of tumor-killing immune cells and the lower expression level of the immune checkpoint. Furthermore, we recommended some small-molecule drugs as novel targeted drugs for new breast cancer types. Finally, the relationship between IL27, a significant prognostic immune and inflammation cytokine, and immune status was analyzed in pan-cancer. Expression of IL27 was significantly correlated with immune regulatory gene expression and immune cell infiltration in pan-cancer. Furthermore, IL27 treatment improved breast cancer cell migration.

Conclusion

The TIIS represents a promising prognostic tool for estimating OS in patients with breast cancer and is correlated with immune status.

Prognostic Value of Systemic Immune-Inflammation Index (SII) in Patients with Glioblastoma: A Comprehensive Study Based on Meta-Analysis and Retrospective Single-Center Analysis

Inflammation is related to cancer. The systemic immune-inflammation index (SII) has been linked to the prognosis of many types of cancer. The present study aimed to determine the prognostic value of the SII in glioblastoma (GBM) patients based on meta-analysis and single-center retrospective analysis. Relevant publications published before 1 October 2022 were identified by searching PubMed, EMBASE, Cochrane Library databases, and Web of Science. Moreover, 208 GBM patients from Zhongnan Hospital were incorporated. Kaplan−Meier and Cox regression analyses determined the prognostic significance of inflammatory markers. By combining these indicators, we developed scoring systems. Nomograms were also built by incorporating independent variables. The accuracies of nomograms were evaluated by Harrell’s concordance index (c-index) and the calibration curve. According to meta-analysis, an elevated SII predicted the worst overall survival (OS) (Hazard ratio [HR] = 1.87, p < 0.001). Furthermore, a higher SII (>510.8) (HR = 1.782, p = 0.007) also predicted a poorer outcome in a retrospective cohort. The scoring systems of SII-NLR (neutrophil-to-lymphocyte ratio) showed the best predictive power for OS. The nomogram without MGMT (c-index = 0.843) exhibited a similar accuracy to that with MGMT (c-index = 0.848). A pre-treatment SII is independently associated with OS in GBM. A nomogram integrating the SII-NLR score may facilitate a comprehensive survival evaluation independent of molecular tests in GBM.

Analysis of Clinical Characteristics of Connective Tissue Disease-Associated Interstitial Lung Disease in 161 Patients: A Retrospective Study

Objective

This study was conducted to retrospectively analyze the clinical characteristics of CTD-ILD patients to provide strategies for clinical management.

Methods

This study collected and analyzed the clinical data and relevant examination results of 161 patients diagnosed with CTD-ILD between 01 January 2018 and 01 January 2021.

Results

A total of 161 CTD-ILD patients, 74.53% were females and 25.47% were males, 32.92% were elderly and 67.08% were non-elderly. The main clinical symptoms of CTD-ILD patients were cough (44.72%), decreased activity tolerance (40.37%). RA-ILD was the most common one in the non-elderly and the elderly CTD-ILD patients (48.15% and 50.94%, respectively). Compared with non-elderly, elderly patients with CTD-ILD had a longer duration of CTD (p=0.04). However, fatigue (p=0.005), activity tolerance (p=0.029), the incidence of pulmonary diffusion dysfunction (p=0.047), and systemic immunoinflammatory index (SII, p=0.014) (platelet × NLR) were all decreased. The standard deviation of red blood cell distribution width (RDW) (p=0.024) and immunoglobulin (IgA) (p=0.033) was significantly increased. The smoking index was significantly higher in men than in women with CTD-ILD (p=0.000), but symptoms of reduced activity tolerance were less pronounced than in women (p<0.05). Elderly CTD-ILD patients (p=0.003) and women from non-elderly patients were prone to lower hemoglobin (p=0.000). Among the elderly, the lymphocyte ratio was more significantly elevated in female CTD-ILD patients than in males (p=0.018). In contrast, neutrophil to lymphocyte ratio (NLR) and SII were lower in female (p=0.038) than in male CTD-ILD patients (p=0.043).

Conclusion

CTD-ILD mainly affects non-elderly and women. Age may not be involved with decreased activity tolerance and increased lung function impairment in CTD-ILD patients. However, the elderly patients with CTD-ILD, especially the elderly female patients with low inflammation levels and high immune disorders, have a poor prognosis.

The systemic immune-inflammation index in predicting sepsis mortality

BACKGROUND

The systemic immune-inflammation index (SII) is a novel parameter and its role in the prognosis of sepsis has never been explored previously.

METHODS

We retrospectively assessed 267 patients with blood-culture confirmed sepsis. Clinical and laboratory data recorded at intensive care unit (ICU) admission were analyzed. Outcomes of interest included in-hospital mortality and length-of-stay (LOS) in the ICU. Sequential Organ Failure Assessment (SOFA) scores, SII, neutrophil-lymphocyte ratio (NLR), and platelet-lymphocyte ratio (PLR) were calculated. Multivariable regression analysis was used to identify independent predictors of LOS and mortality. Area under receiver operator characteristic (AUROC) curves were used to determine optimum cutoffs, and the incremental effect of SII on the SOFA score was assessed using model discrimination and calibration properties.

RESULTS

There were 76 (28.5%) non-survivors. SII, NLR, and PLR were independent predictors of sepsis mortality, with adjusted odds ratios of 1.51 (1.24-1.84), 1.67 (1.30-2.13) and 1.24 (1.11-1.39). SII and SOFA score were independent predictors of LOS. SII had an AUROC of 0.848, and the optimum cutoff was 564 with a sensitivity and specificity of 85.5% and 71.2%. The addition of SII to the model had a significant incremental effect on the predictive ability of SOFA score (Net Reclassification Index = 0.084, P = 0.025; Integrated Discrimination Index = 0.056, P = 0.001).

CONCLUSION

The SII is an inexpensive parameter that can be used in addition to clinical sepsis scores to improve the accuracy of patient assessment.

Neutrophil Counts, Neutrophil-to-Lymphocyte Ratio, and Systemic Inflammatory Response Index (SIRI) Predict Mortality after Off-Pump Coronary Artery Bypass Surgery

Background: Several perioperative inflammatory markers are postulated to be significant factors for long-term survival after off-pump coronary artery bypass surgery (OPCAB). Hematological parameters, whether single or combined as indices, provide higher predictive values. Methods: The study group comprised 538 consecutive patients (125 (23%) females and 413 (77%) males) with a mean age of 65 ± 9 years, who underwent OPCAB with a mean follow-up time of 4.7 ± 1.7 years. This single-center retrospective analysis included perioperative inflammatory markers such as the neutrophil-to-lymphocyte ratio (NLR), systemic inflammatory response index (SIRI), aggregate index of systemic inflammation (AISI), and systemic inflammatory index (SII). Results: Multivariable analysis identified levels of neutrophils above 4.3 × 109/L (HR 13.44, 95% CI 1.05−3.68, p = 0.037), values of SIRI above 5.4 (HR 0.29, 95% CI 0.09−0.92, p = 0.036) and values of NLR above 3.5 (HR 2.21, 95% CI 1.48−3.32, p < 0.001) as being significant predictors of long-term mortality. The multifactorial models revealed the possibility of strong prediction by combining preoperative factors (COPD, stroke, PAD, and preoperative PLR) and postoperative neutrophil counts (p = 0.0136) or NLR (p = 0.0136) or SIRI (p = 0.0136). Conclusions: Among the postoperative inflammatory indices, the levels of neutrophils, NLR, and SIRI are the most prominent markers for long-term survival after off-pump coronary artery bypass surgery, when combined with preoperative characteristics.