Low Systemic Immune-inflammation Index Research Articles

Peripheral blood immunoinflammatory biomarkers: prospective predictors of postoperative long-term survival and chronic postsurgical pain in breast cancer

BackgroundTumor progression and chronic postsurgical pain (CPSP) in patients with breast cancer are both significantly influenced by inflammation. The associations between immunoinflammatory biomarkers and long-term survival, as well as CPSP, remain ambiguous. This study examined the predictive value of immunoinflammatory biomarkers for both long-term survival and CPSP.MethodsData on the clinicopathological characteristics and perioperative peripheral blood immunoinflammatory biomarkers of 80 patients who underwent breast cancer surgery were retrospectively collected. Optimal cut-off values for preoperative immunoinflammatory biomarkers, including the preoperative systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), neutrophil-to-lymphocyte ratio (NLR), and pan-immune-inflammation value (PIV), were established via receiver operating characteristic (ROC) curves. Kaplan−Meier curves and Cox regression analysis were used to evaluate the relationships between preoperative immunoinflammatory biomarkers and long-term survival. The relationships among the perioperative neutrophil count (NEU), monocyte count (MONO), lymphocyte count (LYM), platelet count (PLT), SII, SIRI, NLR, PIV, dynamic changes in peripheral blood cell counts, and CPSP were further assessed using logistic regression analysis.ResultsKaplan−Meier curves revealed a considerable prolongation of disease-free survival (DFS) and overall survival (OS) in the low preoperative SII, SIRI, NLR, and PIV groups. Multivariate Cox regression analysis revealed that only an elevated preoperative SIRI was an independent risk factor for postoperative DFS (HR=8.890, P=0.038). The incidence of CPSP was 28.75%. Univariate logistic regression analysis revealed that body mass index (BMI), postoperative NEU, MONO, SIRI, and PIV were negatively correlated with the occurrence of CPSP, whereas subsequent multivariate logistic regression analysis revealed that only BMI was independently associated with CPSP (OR=0.262, P=0.023).ConclusionElevated preoperative SIRI was an independent risk factor for poor DFS in breast cancer patients after surgery. In contrast, perioperative immunoinflammatory biomarkers had limited potential for predicting CPSP in patients who underwent breast cancer surgery.

Joint association of systemic immune-inflammation index and phenotypic age acceleration with chronic respiratory disease: a cross-sectional study

BackgroundChronic respiratory diseases (CRD) represents a series of lung disorders and is posing a global health burden. Systemic inflammation and phenotypic ageing have been respectively reported to associate with certain CRD. However, little is known about the co-exposures and mutual associations of inflammation and ageing with CRD. Here, we aim to systematically elucidate the joint and mutual mediating associations of systemic immune-inflammation index (SII) and phenotypic age acceleration (PhenoAgeAccel) with CRD based on data from National Health and Nutrition Examination Survey (NHANES).MethodsData for this study was obtained from NHANES 2007–2010 and 2015–2018. The single and combined associations of SII and PhenoAgeAccel with CRD were analyzed using multivariable logistic regression models. The dose-response relationship between exposures and outcomes was determined by restricted cubic splines (RCS) regression. Subgroup and mediation analyses were further conducted.ResultsTotally, 15,075 participants were enrolled in this study including 3,587 CRD patients. Compare with controls, CRD patients tended to be older, females and present higher SII and PhenoAgeAccel values. Single-index analysis indicated that either SII or PhenoAgeAccel demonstrated a significantly positive association with CRD via logistic regressions and RCS curves. Furthermore, the joint-indexes analysis revealed that compared to individuals with lower SII and PhenoAgeAccel, those with higher SII and PhenoAgeAccel exhibited remarkably stronger associations with CRD (adjusted OR [aOR], 1.56; 95% CI, 1.31–1.85; P < 0.001), chronic obstructive pulmonary disease (aOR, 1.56; 95% CI, 1.22-2.00; P = 0.001) and asthma (aOR, 1.40; 95% CI, 1.16–1.70; P = 0.001), which were predominant among those aged above 40 years, females and smokers. Eventually, mediation analyses suggested the mutual mediating effects of SII and PhenoAgeAccel on CRD and PhenoAgeAccel mediated SII resulting in CRD more significantly.ConclusionThis study confirmed the coexposure effect and mutual mediation between SII and PhenoAgeAccel on CRD. We recommend that the joint assessment may conduce to the accurate identification for populations susceptible to CRD and early prevention of chronic respiratory diseases.

The prognostic value of systemic immune-inflammation index in patients with unresectable hepatocellular carcinoma treated with immune-based therapy

BackgroundPredicting the efficacy of immune-based therapy in patients with unresectable hepatocellular carcinoma (HCC) remains a clinical challenge. This study aims to evaluate the prognostic value of the systemic immune-inflammation index (SII) in forecasting treatment response and survival outcomes for HCC patients undergoing immune-based therapy.MethodsWe analyzed a cohort of 268 HCC patients treated with immune-based therapy from January 2019 to March 2023. A training cohort of 93 patients received atezolizumab plus bevacizumab (T + A), while a validation cohort of 175 patients underwent treatment with tyrosine kinase inhibitors (TKIs) combined with anti-PD-(L)1 therapy. The SII cutoff value, determined using X-tile analysis based on overall survival (OS) in the training cohort, divided patients into high (> 752*109) and low (≤ 752*109) SII groups. Prognostic factors were identified through univariate and multivariate logistic and Cox regression analyses, and survival outcomes were assessed using Kaplan–Meier methods. The predictive accuracy of SII was evaluated using receiver operating characteristic (ROC) curves.ResultsAn optimal SII cutoff of 752*109 stratified patients into high and low SII groups. Univariate and multivariate logistic regression indicated that SII was a significant predictor of the objective response rate (ORR), which was markedly different between the low and high SII subgroups (34.72% vs. 9.52%, P = 0.019). This finding was consistent in the validation cohort (34.09% vs. 16.28%, P = 0.026). SII also demonstrated prognostic value in Cox regression and Kaplan–Meier analyses. ROC curves confirmed that SII had superior predictive accuracy compared to common clinical indicators, with predictive relevance even in AFP-negative patients. Furthermore, a lower SII was associated with a higher T cell ratio and an increased number of CD8+ T cells and Granzyme B+ CD8+ T cells in peripheral blood.ConclusionSII is a promising predictor of both therapeutic efficacy and prognosis in HCC patients undergoing immune-based treatments. Its application may enhance clinical decision-making, thereby improving patient outcomes from immune-based therapy.

Prognostic significance of systemic immune inflammation index in patients with urothelial carcinoma: a systematic review and meta-analysis

ObjectiveThis review assessed the prognostic significance of the systemic immune inflammation index (SII) in patients with urothelial carcinoma.MethodsWe performed a systematic review and cumulative meta-analysis of the primary outcomes according to the PRISMA criteria, and assessed study quality. Seven databases were searched: Embase, PubMed, Cochrane Library, Web of Science, China National Knowledge Infrastructure, Wanfang, and SinoMed, from the creation of each database until October 2024.ResultsThe meta-analysis included 31 studies, including 14,437 patients with urothelial carcinoma. A low SII was significantly associated with better recurrence-free survival (RFS) (HR = 1.37, 95%CI (1.19, 1.56), P &amp;lt; 0.05), cancer-specific survival (CSS) (HR = 1.87, 95%CI (1.50, 2.34), P &amp;lt; 0.05), and overall survival (OS) (HR = 1.42, 95%CI (1.23, 1.64), P &amp;lt; 0.05). In addition, subgroup analysis found that higher SII was associated with poorer prognosis regardless of treatment regimen, tumor type, or SII cutoff, and that high SII was an important prognostic biomarker in the UC population.ConclusionA low SII may be associated with better RFS, CSS, and OS. The SII can be used as a is a potentially noninvasive and promising prognostic indicator for urothelial carcinoma; however, further studies with appropriate designs and larger sample sizes are needed to verify these findings.

Association Between Systemic Immune-Inflammation Index and Outcomes of Acute Myocardial Infarction: A Systemic Review and Meta-Analysis.

Objective: To assess the link between systemic immune-inflammation index (SII) and risk of major adverse cardiovascular events (MACE), contrast-induced nephropathy (CIN), and overall mortality in patients with acute myocardial infarction (AMI). Patients and Methods: Electronic search of PubMed, EMBASE, Web of Science, and Scopus databases was done for observational studies with the data on the association of SII and outcomes, such as MACE, and CIN in adult (≥18 y) patients with AMI. A random-effects model was used, and the pooled effect sizes were expressed as relative risk (RR) with corresponding 95% confidence intervals (CI). Subgroup analysis was conducted on the basis of the type of AMI (ST elevation myocardial infarction and non-ST elevation myocardial infarction), sample size (≥500 and <500), and study design. GRADE assessment was used to evaluate the certainty of the evidence. Results: The analysis included 23 studies. Most studies were conducted in China (n = 13), followed by Turkey (n = 10). Majority of the studies (n = 20) had a retrospective cohort design. Patients with high SII had increased risk of MACE (RR 2.95, 95% CI: 1.25, 6.99; n = 5, I2 = 97.5%), overall mortality (RR 2.59, 95% CI: 1.64, 4.07; n = 6, I2 = 58.0%), and CIN (RR 4.58, 95% CI: 3.44, 6.10; n = 4, I2 = 0.0%), compared with patients with lower SII. Egger's test detected publication bias for MACE (p = 0.047) and overall mortality (p = 0.012) but not for CIN. These associations remained valid in subgroup analysis. Conclusion: Findings suggest that higher SII in patients with AMI is associated with increased risks of MACE, CIN, and overall mortality. This underscores SII's potential as a prognostic marker in AMI.

The Predictive Value of Preoperative Systemic Immune-Inflammation Index in Patients with Granulomatous Mastitis.

The systemic immune-inflammation index (SII) comprehensively reflects the balance between immune status and host inflammation. We aimed to investigate the potential predictive value of the SII in the prognosis of granulomatous mastitis (GM). We enrolled 245 patients with GM who underwent surgery between 2015 and 2020 in this study. Using the receiver operating characteristic (ROC) curve, we divided the patients into low SII groups (SII≤836×109/L) and high SII groups (SII>836×109/L). The associations between SII and clinical parameters were assessed using chi-squared or Fisher's exact tests. Kaplan-Meier plots and Log rank tests were performed to investigate the clinical outcomes of cumulative no-recurrence rates. Risk factors were analyzed by using logistic regression analysis. We found a correlation between the recurrence of GM and the preoperative level of SII, and the high SII group exhibited a higher recurrence rate than the low SII group. To further explore the factors affecting the risk of recurrence, we found that young age at disease onset, skin rupture, and the postoperative use of corticosteroids could increase the risk of GM recurrence. Multivariate logistic regression analysis suggested that young age and postoperative corticosteroid use were the risk factors for disease recurrence. As a noninvasive and readily available clinical parameter, the preoperative SII level has great significance in evaluating the efficacy and prognosis of surgical treatment for GM combined with age and postoperative corticosteroid use, which provides valuable insights for making treatment decisions.

The Prognostic Value of Systemic Immune-Inflammation Index Supporting Age-Adjusted Charlson Comorbidity Index in Non-Small Cell Lung Cancer Patients with First-Line Platinum-Based Chemotherapy.

This study aimed to examine the association between the systemic immune-inflammation index (SII) (ie, neutrophil count × platelet count/lymphocyte count), the age-adjusted Charlson comorbidity index (ACCI), and overall survival (OS) in non-small cell lung cancer (NSCLC) patients undergoing first-line platinum-based chemotherapy (PBC), with a particular emphasis on the role of SII in supporting ACCI. This retrospective study enrolled 353 cases treated between July 2013 and November 2020. Mann-Whitney U-test and Kruskal-Wallis test were employed to compare parameters between high and low SII groups. The cut-off values for SII and ACCI were determined using the X-tile software. Prognostic significance was evaluated through the utilization of Kaplan-Meier curves and Cox regression analysis. In a univariate Cox regression analysis, sex, age, TNM, lymph node, therapy, SII, and ACCI were associated with OS. After adjusting for confounders in the multivariate analysis, TNM, SII, and ACCI remained independent prognostic factors for OS. Furthermore, within the ACCI subgroups (ACCI<5 or ACCI≥5), a high SII was significantly associated with an increased risk of death. Patients with both a high ACCI and a high SII had the highest risk of death (p < 0.001), with a loss of approximately ten months of survival during the first three years after treatment. SII was proven to be valuable in predicting OS and, when complemented by ACCI, can help tailor prognostic assessment and treatment strategies in assessing the survival of NSCLC patients with first-line PBC.

Prognostic Value of the Baseline Systemic Immune-Inflammation Index in HER2-Positive Metastatic Breast Cancer: Exploratory Analysis of Two Prospective Trials.

The systemic immune-inflammation index (SII) is a hematological marker that reflects the immune status of the body. This study was designed to evaluate the prognostic significance of the baseline SII in HER2-positive metastatic breast cancer (MBC) patients receiving chemotherapy plus trastuzumab without or with pertuzumab. Data were collected from 774 patients from the CLEOPATRA trial, 196 patients from the H0648G trial, and 229 patients from six clinical centers in China. Patients were divided into the low and high SII subgroups according to the median SII value. The inverse probability of treatment weighting (IPTW) method was used to control bias. Associations between the SII and progression-free survival (PFS) and overall survival (OS) were analyzed. In the CLEOPATRA trial, a lower SII was associated with better PFS (hazard ratio [HR] 1.31, 95% confidence interval [CI] 1.04-1.65, P = 0.02) and OS (HR 1.42, 95% CI 1.07-1.88, P = 0.02) in the trastuzumab and docetaxel groups, as well as improved PFS in the trastuzumab and pertuzumab and docetaxel groups (HR 1.39, 95% CI 1.10-1.77, P < 0.01) after IPTW. In the H0648G trial, a lower SII was associated with better PFS (P = 0.04) and OS (P = 0.02) in HER2-positive MBC patients receiving trastuzumab-based therapy. According to real-world data, a lower SII predicted an improvement in PFS for patients treated with docetaxel plus trastuzumab without or with pertuzumab (P = 0.02 and 0.01, respectively). A low baseline SII is associated with better survival outcomes among HER2-positive MBC patients receiving trastuzumab-based first-line therapy.

Systemic immune-inflammation index and 2-year all-cause mortality in elderly patients with hip fracture

PurposeTo assess the association between systemic immune-inflammation index (SII) and 2-year all-cause mortality in elderly patients with hip fractures. MethodsWe performed a cohort study of hip fracture patients aged 65 years or older who received hip fracture surgery at a tertiary hospital from January 2005 to March 2022. The SII was calculated as: SII = (neutrophil count * platelet count) / lymphocyte count, based on the latest blood test before discharge. Patients were categorized into 3 groups according to SII tertiles: low SII group (≤770.92 × 109/L), medium SII group (770.92 × 109/L -1293.03 × 109/L), and high SII group (>1293.03 × 109/L). The primary outcome was 2-year all-cause mortality. We evaluated the association between SII and 2-year all-cause mortality using the multivariate Cox regression model. ResultsAmong 2766 patients, 296 patients died during the 2-year follow-up period. The incidence of 2-year all-cause mortality per 1000 persons was 90.0 (95 % CI: 73.2–110.2) in the low SII group, 86.8 (95 % CI: 70.3–106.7) in the medium SII group, and 144.3 (95 % CI: 123.1–168.5) in the high SII group. Compared with patients in the low SII group, the hazard ratio for 2-year all-cause mortality was 0.97 (95 % CI: 0.69–1.37) in the medium SII group and 1.47 (95 % CI: 1.07–2.01) in the high SII group (P for trend, 0.010). ConclusionSII is significantly associated with 2-year all-cause mortality in elderly patients with hip fracture. SII may be used to identify patients at high risk of mortality after hip fracture surgery.

Prognostic Value of Preoperative Systemic Immune-Inflammation Index in Non-Metastatic Paediatric Wilms' Tumour Patients Undergoing Upfront Radical Nephrectomy.

To analyse the relationship between the preoperative systemic immune-inflammation index (SII) and the relapse-free survival (RFS) of paediatric patients with Wilms' tumour (WT) after radical surgery, and to establish and validate a prognostic survival model. Observational study. Place and Duration of the Study: Department of Oncologic Surgery, Anhui Children's Hospital of Fudan University, Hefei, China, from January 2013 to August 2023. A retrospective analysis was conducted on 79 WT patients treated with radical resection, with their preoperative SII values computed. The best cut-off for SII was determined through the ROC curve, categorising patients into high and low SII groups. The Kaplan-Meier method and Cox-regression were used for survival analysis. A survival prognostic model was constructed and its predictive capability gauged (AUC of the ROC). The study included 79 WT patients with a median RFS of 65 months and an average of 75.5 ± 3.4 months. The optimal cut-off value for SII was 534.95. The low SII group had a higher RFS (Log-rank: χ2 = 9.380, p = 0.002). Preoperative SII (HR = 3.277, 95% CI: 1.167 - 9.200, p = 0.024), clinical staging (HR = 8.408, 95% CI: 2.604 - 27.147, p <0.001), and tissue differentiation (HR = 2.237, 95% CI: 1.043 - 5.828, p = 0.039) were independent risk factors for RFS. The model's diagnostic performance was 0.749 (95% CI: 0.636 - 0.861). Internal validation showed an AUC of 0.723 (95% CI: 0.608 - 0.838). Lower preoperative SII suggests a more favourable prognosis. The SII-based nomogram efficiently forecasts post-radical surgery prognosis for WT. Wilms' Tumour, Systemic immune-inflammation index, Relapse-free survival, Nomogram.

Prognostic Value of Preoperative Systemic Immune-Inflammation Index in Non-Metastatic Paediatric Wilms' Tumour Patients Undergoing Upfront Radical Nephrectomy.

To analyse the relationship between the preoperative systemic immune-inflammation index (SII) and the relapse-free survival (RFS) of paediatric patients with Wilms' tumour (WT) after radical surgery, and to establish and validate a prognostic survival model. Observational study. Place and Duration of the Study: Department of Oncologic Surgery, Anhui Children's Hospital of Fudan University, Hefei, China, from January 2013 to August 2023. A retrospective analysis was conducted on 79 WT patients treated with radical resection, with their preoperative SII values computed. The best cut-off for SII was determined through the ROC curve, categorising patients into high and low SII groups. The Kaplan-Meier method and Cox-regression were used for survival analysis. A survival prognostic model was constructed and its predictive capability gauged (AUC of the ROC). The study included 79 WT patients with a median RFS of 65 months and an average of 75.5 ± 3.4 months. The optimal cut-off value for SII was 534.95. The low SII group had a higher RFS (Log-rank: χ2 = 9.380, p = 0.002). Preoperative SII (HR = 3.277, 95% CI: 1.167 - 9.200, p = 0.024), clinical staging (HR = 8.408, 95% CI: 2.604 - 27.147, p <0.001), and tissue differentiation (HR = 2.237, 95% CI: 1.043 - 5.828, p = 0.039) were independent risk factors for RFS. The model's diagnostic performance was 0.749 (95% CI: 0.636 - 0.861). Internal validation showed an AUC of 0.723 (95% CI: 0.608 - 0.838). Lower preoperative SII suggests a more favourable prognosis. The SII-based nomogram efficiently forecasts post-radical surgery prognosis for WT. Wilms' Tumour, Systemic immune-inflammation index, Relapse-free survival, Nomogram.

Prognostic impact of systemic immune-inflammation index in patients with acute decompensated heart failure with preserved ejection fraction -PURSUIT-HFpEF Registry-

Abstract Background Systemic inflammation has been implicated in the pathophysiology of heart failure with preserved ejection fraction. Several studies have shown that systemic immune-inflammation index (SII), a novel index based on platelets, neutrophils, and lymphocytes, predicts poor prognosis in patients with cardiovascular disease. However, it remains to be elucidated whether SII could have predictive value in patients with acute decompensated heart failure with preserved ejection fraction (ADHF-HFpEF). Purpose This study is designed to investigate the association of SII at admission or discharge with poor clinical outcome in patients with ADHF-HFpEF. Methods Patients’ data were extracted from The Prospective mUlticenteR obServational stUdy of patIenTs with Heart Failure with Preserved Ejection Fraction (PURSUIT HFpEF) study, which is a prospective multicenter observational registry for ADHF-HFpEF in a city. Laboratory data and body weight measurements were performed just before discharge. We analyzed 966 patients (mean age: 81 years old, male: 45%) after exclusion of patients on dialysis, missing follow-up data, or missing data to calculate SII. SII was calculated as follows: SII = platelet count × neutrophil count / lymphocyte count on admission and at discharge. The primary endpoint was the composite of all-cause death and rehospitalization for worsening heart failure. Results During a mean follow-up period of 1.8±1.3 years, the primary endpoint was observed in 435 patients (259 patients died and 176 patients underwent rehospitalization for worsening heart failure). In multivariate Cox analysis, high SII at discharge (&amp;gt; 536×109 determined by receiver operating characteristic curve analysis (AUC: 0.564 [0.526-0.602]) was significantly independently associated with not only the primary endpoint (hazard ratio 1.28 [1.04-1.57], p=0.020) but also all-cause death ((hazard ratio 1.39 [1.06-1.81], p=0.018) after adjustment for major confounders such as age, gender, body mass index, NYHA class, systolic blood pressure, heart rate and laboratory data including NT-proBNP and CRP. However, high SII on admission was not significantly associated with primary endpoint after multivariate adjustment. Kaplan-Meier analysis revealed that patients with high SII at discharge had significantly greater risk of both the primary endpoint (56% vs 43%, p&amp;lt;0.001) and all-cause mortality than those with low SII (36% vs 24%, p&amp;lt;0.001). Conclusion Systemic immune-inflammation index at discharge, but not on admission, would be associated with post-discharge poor outcome in patients with acute decompensated heart failure with preserved ejection fraction.

Predicting the prognosis of patients with renal cell carcinoma based on the systemic immune inflammation index and prognostic nutritional index

The aim of the study was to analyze and discuss the value of preoperative systemic immune inflammation index (SII) and prognostic nutritional index (PNI) in predicting the prognosis of patients with renal cell carcinoma (RCC) after operation, and to establish a nomogram prediction model for patients with RCC after operation based on SII and PNI. From January 2014 to December 2018, 210 patients with RCC who underwent surgical treatment at the Xuzhou Central Hospital were selected as the research object. The receiver operating characteristic curve (ROC) was used to determine the optimal cut-off value for preoperative SII, PNI, LMR, PLR, NLR and the patients were divided into groups according to the optimal cutoff values. The survival rate of patients was evaluated. The risk factors that affect the prognosis of patients with RCC were determined by LASSO and Cox regression analysis, and a prognostic nomogram was constructed based on this result. The bootstrap method was used for internal verification of the nomogram model. The prediction efficiency and discrimination of the nomogram model were evaluated by the calibration curve and index of concordance (C-index), respectively. The average overall survival (OS) of all patients was 75.385 months, and the 1-, 2-and 3-year survival rates were 95.5%, 86.6% and 77.2%, respectively. The survival curve showed that the 5-year OS rate of low SII group was significantly higher than that of high SII group (89.0% vs. 64.5%; P < 0.05), and low PNI group was significantly lower than those in high PNI group (43.4% vs. 87.9%; p < 0.05). There were significant differences between preoperative SII and CRP, NLR, PLR, LMR, postoperative recurrence, pathological type and AJCC stage (P < 0.05). There were significant differences between preoperative PNI and BMI, platelet, NLR, PLR, LMR, postoperative recurrence, surgical mode and Fuhrman grade (P < 0.05). The ROC curve analysis showed that the AUC of PNI (AUC = 0.736) was higher than that of other inflammatory indicators, followed by the AUC of SII (0.718), and the difference in AUC area between groups was statistically significant (P < 0.05). The results from multivariate Cox regression analysis showed that SII, PNI, tumor size, tumor necrosis, surgical mode, pathological type, CRP, AJCC stage and Fuhrman grade were independent risk factors for postoperative death of patients with RCC. According to the results of Cox regression analysis, a prediction model for the prognosis of RCC patients was established, and the C-index (0.918) showed that the model had good calibration and discrimination. The subject’s operating characteristic curve indicates that the nomogram has good prediction efficiency (the AUC = 0.953). Preoperative SII and PNI, tumor size, tumor necrosis, surgical mode, pathological type, CRP, AJCC stage and Fuhrman grade are closely related to the postoperative prognosis of patients with renal cell carcinoma. The nomogram model based on SII, PNI, tumor size, tumor necrosis, surgical mode, pathological type, CRP, AJCC stage and Fuhrman grade has good accuracy, discrimination and clinical prediction efficiency.

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

BackgroundThe relationship between the systemic immune-inflammation index (SII), chemotherapy sensitivity, and prognosis in HR+HER2– breast cancer (BC) has not been extensively studied. Patients and methodsClinical data from 980 patients diagnosed with HR+HER2– BC between June 2012 and June 2016 were collected. Patients were divided into low- and high-SII groups according to median SII value. Differences among variables were assessed using the chi-squared test. The inverse probability of treatment weighting (IPTW) method was used to control bias. The associations between clinicopathological factors, baseline SII, and disease-free survival (DFS) were analyzed using Kaplan–Meier curves and Cox analyses. ResultsThe median follow-up period was 37 months (5-77). 480 patients underwent neoadjuvant chemotherapy, and low baseline SII values were associated with higher pathological complete response (pCR) rates than those in the high SII group (16.4% vs. 9.2%; P = .019). Multivariate analyses revealed that larger tumor size, more lymph node involvement, high Ki-67 score, and high baseline SII were independent prognostic factors for worse outcomes in patients with HR+HER2– BC. The risk for metastasis/recurrence was higher in the high SII group compared with that in the low SII group (hazard ratio 2.07 [95% CI, 1.35-3.19]; P = .001). After IPTW, a similar result was obtained, in that a high SII value was significantly associated with worse DFS among patients with HR+HER2– BC. ConclusionA low baseline SII was associated with higher pCR rates after neoadjuvant chemotherapy and was an independent prognostic factor for better DFS outcomes in patients with HR+HER2– BC.

ABO Blood Type and Pretreatment Systemic Inflammatory Response Index Associated with Lymph Node Metastasis in Patients with Breast Cancer.

Lymph node metastasis (LNM) is an important prognostic factor for breast cancer. Inflammatory stimulation can change tumor microenvironment and lead to LNM, but the relationship between LNM and peripheral immunoinflammatory indices has not been clarified in breast cancer. The clinical information of 1918 patients with breast cancer admitted to Meizhou People's Hospital from October 2017 to December 2023 were retrospectively analyzed. The relationship of clinicopathological features (age, body mass index (BMI), ABO blood types, family history of cancer, tumor site, disease stage, LNM, distant metastasis, and molecular subtypes) and peripheral immunoinflammatory indices (pan-immune inflammation value (PIV), systemic immune inflammation index (SII), and system inflammation response index (SIRI)) were analyzed. There were 935 (48.7%) patients had no LNM and 983 (51.3%) had LNM. There were statistically significant differences in the distributions of ABO blood groups (p=0.022) and molecular subtypes (p<0.001) between the two groups. PIV, SII, and SIRI levels in patients with LNM were significantly higher than those without LNM (all p<0.05). The proportions of LNM in patients with high PIV, SII, and SIRI levels were higher than those with low PIV, SII, and SIRI levels, respectively. Logistic regression analysis showed that non-O blood type (non-O blood type vs O blood type, odds ratio (OR): 1.327, 95% confidence interval (CI): 1.056-1.667, p=0.015), luminal B subtype (luminal B vs luminal A, OR: 2.939, 95% CI: 2.147-4.022, p<0.001), HER2+ subtype (HER2+ vs luminal A, OR: 2.044, 95% CI: 1.388-3.009, p<0.001), and high SIRI level (≥0.875 vs <0.875, OR: 1.572, 95% CI: 1.092-2.265, p=0.015) were independently associated with LNM. Non-O blood type, luminal B and HER2+ subtypes, and high SIRI level (≥0.875) have potential role in predicting the status of LNM in breast cancer patients.

Preoperative Inflammatory Scores Do Not Accurately Predict Early Recurrence of Pancreatic Ductal Adenocarcinoma After Resection: A Systematic Review and Meta‐Analysis

ABSTRACTBackgroundDisease recurrence after surgical resection for pancreatic ductal adenocarcinoma can affect more than 50% of patients in the first 12 months after resection. The goal of this current systematic review and meta‐analysis is to assess the ability of preoperative inflammatory scores to predict early recurrence after resection and to identify the best candidates for surgical resection.MethodsMedline and Web of Science databases were searched for studies reporting inflammatory scores and oncological outcomes in patients with PDAC after curative‐intent resection. The systematic review revealed that the most common scores were modified Glasgow Prognostic Score (mGPS), Prognostic Nutritional Index (PNI), platelet‐to‐lymphocyte ratio (PLR), neutrophil‐to‐lymphocyte ratio (NLR), and Systemic Immune‐Inflammation Index (SII). After, a meta‐analysis was performed to determine the prognostic value of these scores in early recurrence (12 months) after resection. A subgroup analysis was also carried out in patients who had upfront surgery and in those who underwent neoadjuvant chemotherapy. The ROBINS‐I tool was used to assess the risk of bias.ResultsThe literature search retrieved 1864 articles, 16 of which were eligible for analysis. The included studies comprised 4460 patients. Nine studies reported outcomes for mGPS, four studies for PNI, seven studies for PLR, eight studies for NLR, and two studies for SII. In the meta‐analysis, mGPS, NLR, and PLR showed significantly higher rates of early recurrence in the high‐score groups compared to the low‐score groups. Analyzing the sensitivity and specificity of these scores showed no significant difference in their diagnostic accuracy (mGPS area under the curve [AUC] = 0.534; NLR AUC = 0.628, and PLR AUC = 0.607). High and low PNI and SII scores demonstrated similar rates of early recurrence.ConclusionmGPS, PNI, PLR, NLR, and SII scores did not show a suitable diagnostic accuracy to predict PDAC recurrence in the first 12 months after resection. Therefore, these inflammatory scores should not be used to select the best candidates or to preclude a possible surgical indication.

Systemic Inflammation Indexes and Risk of Immune-related Adverse Events in Patients With Metastatic Urothelial Carcinoma Treated With Immunotherapy.

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of metastatic urothelial carcinoma (mUC). However, they could be associated with immune-related adverse events (irAEs), which may be clinically significant. Identifying clinical characteristics that may be associated with a higher risk of irAEs is of great importance. We retrospectively collected data from all patients who received anti-PD1 or anti-PD-L1 for metastatic UC at our Institution from January 2017 to December 2022. Patients were dichotomized according to baseline neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and platelet-to-lymphocyte ratio (PLR) values. We performed univariate and multivariate logistic regression to determine the association between baseline characteristics and the development of irAEs. A total of 119 patients were identified. At a median follow-up of 29.6 months, 96 patients progressed and 82 died. Forty-five patients developed irAEs of any grade, 8 patients developed grade 3 toxicities. In the univariate analysis PS of 0 (p<0.01), baseline NLR <3.52, baseline PLR <194 (p=0.04) and baseline SII <906 (p=0.01) were significantly associated with a higher risk of developing irAEs, whereas in the multivariate analysis only PS=0 (p<0.01) and NLR <3.52 (p=0.03) maintained their correlation. Median progression-free survival (mPFS) and overall survival (mOS) were significantly longer in patients with NLR <3 (mPFS 3.8 vs. 2.6 months, p=0.01; mOS 15.3 vs. 5.6 months, p=0.002) and PS=0 (mPFS 4.8 vs. 2.1 months, p<0.001; mOS 15.3 vs. 3.8 months, p<0.001). Low baseline NLR, PLR, and SII and good PS are associated with a higher risk of developing irAEs in patients treated with ICIs for mUC.

Prognostic model for predicting recurrence in hepatocellular carcinoma patients with high systemic immune-inflammation index based on machine learning in a multicenter study.

This study aims to use machine learning to conduct in-depth analysis of key factors affecting the recurrence of HCC patients with high preoperative systemic immune-inflammation index (SII) levels after receiving ablation treatment, and based on this, construct a nomogram model for predicting recurrence-free survival (RFS) of patients. This study included clinical data of 505 HCC patients who underwent ablation therapy at Beijing You'an Hospital from January 2014 to January 2020, and accepted 65 HCC patients with high SII levels from Beijing Ditan Hospital as an external validation cohort. 505 patients from Beijing You'an Hospital were divided into low SII and high SII groups based on the optimal cutoff value of SII scores. The high SII group was further randomly divided into training and validation cohorts in a 7:3 ratio. eXtreme Gradient Boosting (XGBoost), random survival forest (RSF), and multivariate Cox regression analysis, were used to explore the factors affecting the post-ablation RFS of HCC patients. Based on the identified key factors, a nomogram model were developed to predict RFS in HCC patients, and their performance were evaluated using the concordance index (C index), receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA). The optimal cutoff value for nomogram scores was used to divide patients into low- and high-risk groups, and the effectiveness of the model in risk stratification was evaluated using Kaplan-Meier (KM) survival curves. This study confirmed that age, BCLC stage, tumor number, and GGT level were independent risk factors affecting RFS in HCC patients. Based on the selected risk factors, an RFS nomogram was successfully constructed. The C-index, ROC curve, calibration curve, and DCA curve each demonstrated the discrimination, accuracy, and decision-making utility of the nomogram, indicating that it has good predictive performance. KM curve revealed the nomogram could significantly differentiate patient populations with different recurrence risk. We developed a reliable nomogram that can accurately predict the 1-, 3-, and 5-year RFS for HCC patients with high SII levels following ablation therapy.

Prognostic Value of Estimated Glucose Disposal Rate and Systemic Immune-Inflammation Index in Non-Diabetic Patients Undergoing PCI for Chronic Total Occlusion.

Chronic total occlusion (CTO) is a complex lesion of coronary artery disease (CAD) with a detection rate of approximately 25% on coronary angiography. CTO patients generally experience poor quality of life and prognosis. This study aims to evaluate the association between the estimated glucose disposal rate (eGDR), a surrogate marker for insulin resistance (IR), and the prognosis of CTO PCI patients, as well as to investigate the potential role of the systemic immune-inflammation index (SII) in this process. We retrospectively included 1482 non-diabetic patients who underwent successful CTO PCI at Anzhen Hospital between January 2018 and December 2021. The primary endpoint was major adverse cardiovascular events (MACEs). Clinical characteristics, biochemical markers, and interventional records were collected, and the eGDR and SII were calculated. Cox regression, restricted cubic splines (RCSs), receiver operating characteristic (ROC) analysis, and Kaplan-Meier curves were used to assess associations. MACEs occurred in 158 patients (10.67%). Patients with MACEs had lower eGDR and higher SII levels. A high eGDR significantly reduced MACE risk (Q4 vs. Q1: HR 0.06, 95% CI 0.03-0.12), while a high SII increased it (Q4 vs. Q1: HR 3.32, 95% CI 1.78-6.33). The combination of low eGDRs and high SIIs predicted the highest MACE risk (HR 4.36, 95% CI 2.71-6.01). The SII partially mediated the relationship between eGDR and MACEs. A low eGDR and high SII are significant predictors of poor prognosis in non-diabetic CTO PCI patients. Combining the eGDR and the SII provides a comprehensive assessment for better predicting cardiovascular outcomes.

Performance of nutritional and inflammatory markers in patients with pancreatic cancer.

Systemic inflammation and nutrition play pivotal roles in cancer progression and can increase the risk of delayed recovery after surgical procedures. To assess the significance of inflammatory and nutritional indicators for the prognosis and postoperative recovery of patients with pancreatic cancer (PC). Patients who were diagnosed with PC and underwent surgical resection at our hospital between January 1, 2019, and July 31, 2023, were enrolled in this retrospective observational cohort study. All the data were collected from the electronic medical record system. Seven biomarkers - the albumin-to-globulin ratio, prognostic nutritional index (PNI), systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), nutritional risk index (NRI), and geriatric NRI were assessed. A total of 446 patients with PC met the inclusion criteria and were subsequently enrolled. Patients with early postoperative discharge tended to have higher PNI values and lower SII, NLR, and PLR values (all P < 0.05). Through multivariable logistic regression analysis, the SII value emerged as an independent risk factor influencing early recovery after surgery. Additionally, both univariable and multivariable Cox regression analyses revealed that the PNI value was the strongest prognostic marker for overall survival (OS; P = 0.028) and recurrence-free survival (RFS; P < 0.001). The optimal cutoff PNI value was established at 47.30 using X-tile software. Patients in the PNI-high group had longer OS (P < 0.001) and RFS (P = 0.0028) times than those in the PNI-low group. Preoperative systemic inflammatory-nutritional biomarkers may be capable of predicting short-term recovery after surgery as well as long-term patient outcomes.