Optimal Cut-off Value For Systemic Immune-inflammation Index Research Articles

Systemic immune-inflammation index predicts the clinical outcomes in patients with acute uncomplicated type-B aortic dissection undergoing optimal medical therapy

BackgroundOptimal medical therapy (OMT) for uncomplicated type B aortic dissection (uTBAD) provides excellent short-term outcomes during follow up; however, its long-term therapeutic effectiveness is unsatisfactory. This study evaluated the predictive value of systemic immune-inflammation index (SII) for adverse events among patients with acute uTBAD undergoing OMT.MethodsWe performed a retrospective analysis of a prospectively maintained database between 2013 and 2020. The primary end point in this study was composite outcomes including aortic intervention, all-cause mortality, retrograde type A aortic dissection (rTAAD) and aortic diameter growth > 5 mm. The patients were divided into high and low SII groups according to the optimal cut-off value of SII as determined using the receiver operating characteristic curve. Cox proportional hazards models were constructed to estimate the hazards ratios and identify the predictors of composite outcomes.ResultsA total of 124 patients with acute uTBAD who underwent OMT were enrolled. One patient died during hospitalisation. At the end of a mean follow-up duration of 51 ± 23 months, 53 (43.1%) patients experienced composite outcomes, 15 patients (12.2%) died, 31 (25.2%) underwent aortic intervention, 21 (17.1%) exhibited diameter growth of > 5 mm, and 2 developed rTAAD. The patients were divided into low SII group (n = 78, 62.9%) and high SII group (n = 46, 37.1%) as per the optimal cut-off SII value of 1449. The incidence of composite outcomes in high SII group was significantly higher than that in low SII (28 [60.9%] vs. 26[33.3%], p < 0.01). Patients with high SII demonstrated significantly higher mortality rate than those with a low SII (11 [23.9%] vs. 5 [6.4%], respectively; p < 0.01). In addition, the high SII group had significantly higher rate of aortic-related reinterventions than the low SII group (16 [34.8%] vs. 15 [19.2%], p = 0.03). Multivariable Cox analyses showed that a high SII score was independently associated with composite outcomes rate (hazard ratio, 2.15; 95% confidence interval, 1.22–3.78; p < 0.01).ConclusionsThe long-term therapeutic effectiveness of OMT alone in patients with acute uTBAD is unsatisfactory. An SII > 1449 at the time of diagnosis is an independent predictor of OMT failure.

The Combined Effect of Systemic Immune-Inflammation Index and Type 2 Diabetes Mellitus on the Prognosis of Patients Undergoing Percutaneous Coronary Intervention: A Large-Scale Cohort Study.

Chronic low-grade inflammation is the common mechanism of both atherosclerosis and type 2 diabetes mellitus (T2DM), and systemic immune-inflammation index (SII) has been emerged as a novel and simple inflammatory biomarker. However, the association between SII and glycemic metabolism and their synergetic effect on the prognosis of coronary artery disease (CAD) patients remains unclear. A total of 8602 patients hospitalized for percutaneous coronary intervention (PCI) were included. The primary endpoint was major adverse cardiovascular events (MACE), including all-cause death, myocardial infarction (MI), and target vessel revascularization. According to the optimal cut-off value of SII for MACEs, patients were grouped into higher levels of SII (SII-H) and lower levels of SII (SII-L) and further divided by the concomitance of T2DM into four groups: SII-H/T2DM, SII-H/Non-T2DM, SII-L/T2DM, SII-L/Non-T2DM. During a median 2.4-year follow-up, 522 MACEs occurred. The optimal cut-off value of SII for MACEs was 502.5. A 1-unit increase of SII (transformed by natural logarithm) was associated with a 29% increase of MACE risks in the T2DM cohort [adjusted hazard ratio (HR): 1.29, 95% confidence interval (CI): 1.03 to 1.61, P = 0.024], while had no effect in the non-T2DM cohort (HR: 1.03, 95% CI: 0.80 to 1.34, P = 0.800). Compared to those in SII-H/T2DM group, patients in SII-H/Non-T2DM, SII-L/T2DM, SII-L/Non-T2DM had significantly decreased risk of MACEs [adjusted HR: 0.77, 95% CI: 0.61 to 0.98, P = 0.036; adjusted HR: 0.66, 95% CI: 0.50 to 0.87, P = 0.003; adjusted HR: 0.58, 95% CI: 0.45 to 0.74, P < 0.001; respectively]. Multivariable Cox regression analysis also indicated the highest risk in T2DM patients with higher levels of SII than others (P for trend < 0.001). In this large-scale real-world study, diabetic patients with elevated SII levels were associated with worse clinical outcomes after PCI.

Kasa İnvaze Olmayan Mesane Kanserinde Sistemik İmmün-İnflamasyon İndeksi ve Nötrofil-Lenfosit Oranının Hastalık Nüksü ve İlerleme Riski ile İlişkisi

Objective: Some systemic inflammatory response-based biomarkers are promising for predicting prognosis of non-muscle-invasive bladder cancer (NMIBC) patients and can contribute to the risk classification without any significant cost. We aimed to evaluate the neutrophil-lymphocyte ratio (NLR) and systemic immune-inflammation index (SII) for the prediction of recurrence and progression risk in patients with NMIBC. Material and Methods: The study included a retrospective analysis of 211 patients who underwent transurethral resection of bladder (TURB) in a tertiary referral center between 2015 and 2019. The receiver operating characteristic (ROC) curve was used to determine the cut-off value. The Kaplan-Meier curves and the log-rank test were constructed to evaluate the recurrence-free and progression-free survival rates according to different levels of inflammatory markers. The multivariate regression analysis was undertaken to estimate the independent prognostic factors. Results: The optimal cut-off value of SII was found to be 568 in the ROC analysis. According to the multivariate analysis, the SII value, number of tumors at the time of initial TURB, and European Organization for Research and Treatment of Cancer (EORTC) recurrence classification were statistically significant parameters in predicting recurrence. While tumor size, NLR, and SII achieved statistically significant levels in the univariate analysis, they didn’t have significance in the multivariate analysis. Conclusion: The SII, number of tumors, and EORTC recurrence classification are prognostic parameters that can be used in the assessment of recurrence. However, inflammatory parameters do not have the same predictive ability in the prediction of the progression rate.

High systemic immune-inflammation index is relevant to osteoporosis among middle-aged and older people: A cross-sectional study.

As one of novel inflammatory indexes proposed in recent years, systemic immune-inflammation index (SII) can comprehensively reflect the inflammatory and immune state of the body. This study aims to explore the relationship between SII and osteoporosis among middle-aged and older people. Our study includes 20,497 individuals from National Health and Nutrition Examination Survey (NHANES) 2005-2008, and target study population are confined to people aged 45 years and above. SII is calculated as platelet count × neutrophil count/lymphocyte count. Multivariate logistic regression analysis is used to explore the link between SII and osteoporosis, and receiver operating characteristics curve is used to screen optimal cut-off value of SII for indicating the occurrence of osteoporosis. A total of 435 people with osteoporosis are screened among 4625 middle-aged and older people, and individuals in osteoporosis group have higher SII than those in nonosteoporosis group (p = .024). Logistic regression analysis indicates that with the enhancement of SII, prevalence of osteoporosis in each tertile category also increases (p < .001). This tendency is also not changed in univariate model (p < .001), as well as the adjustments for different parameters. Moreover, we also identify that SII of 530.09 is the optimal cut-off value for indicating the occurrence of osteoporosis among middle-aged and older people. This present NHANES-based study noticed that higher SII is positively linked to osteoporosis among middle-aged and older people, and SII should not exceed 530.09 for them to obtain a potentially lower risk of osteoporosis.

Prognostic value of systemic inflammatory response in early-stage triple-negative breast cancer.

e14562 Background: Among breast cancer (BC) triple-negative (TN) subtype is the most immunogenic. Host and systemic immune response characterised by tumor-infiltrating lymphocytes (TILs) and immune cells in peripheral blood shape the net anti-tumor immune status. The systemic immune-inflammation index (SII) represents an effective indicator of the peripheral immune status. To date, TILs and SII have been largely examined separately. Therefore, in the present study, we investigated the prognostic value and relationship between pretreatment TILs and SII in a large number of unselected patients (pts) with early (e) stage TNBC. Methods: A total of 301 consecutive eTNBC pts treated with curative intent at Oncology Institute Ljubljana from January 2000 till August 2007 were investigated. Histopathological and clinical data were obtained retrospectively from the medical records. TILs were scored as intensive vs others. SII was determined by platelet × neutrophil/lymphocyte. Univariate and multivariate analyses were performed using the Cox proportional hazard model. The optimal cut-off value of SII was 675 and was evaluated using the receiver operating characteristic (ROC) curve. Results: The median follow-up period was 17,6 years (16.9-18.3), and the entire cohort`s 10-year DFS was 67.5% and 10-year OS 72.1%. The median age was 54 (53-57) years. Most pts were diagnosed node negative (40.7%), with larger tumors (≥ 2 cm, 57.1%), grade 3 (83.5%) and underwent perioperative chemotherapy (cht) (81%). Patients with positive lymph nodes (LN) had higher SII (r=0.21, p=0.003), no correlation between LN and TILs was found. Patients with higher TILs had significantly better OS (HR: 0.40, 95% CI 0.37-0.97, p=00.004), and lower SII predicted significantly better DFS and OS (HR for DFS: 1.65 95% CI 1,03-2.67, p=0.038, HR for OS: 1.72, 95% CI 1.11-2.65, p=0,015). In multivariate analysis, positive LN status retained its independent prognostic value for worse DFS and positive LN and higher SII for worse OS. Conclusions: Our data confirms important role of systemic immune response in the prognosis of eTNBC. The survival of these pts is significantly influenced by the pretreatment SII and TILs, the prognostic value of SII seems to be stronger in our cohort. However, positive lymph node status remains the strongest predictor for worse survival in eTNBC. [Table: see text]

Impact of systemic immune-inflammation index in patients with limited-stage small cell lung cancer.

e20626 Background: The systemic immune-inflammation index (SII) has been suggested as a prognostic marker in several solid malignant neoplasms. However, there are few studies on the prognostic value of SII in patients with limited-stage SCLC. This study explored the impact of SII on overall survival (OS) and progression-free survival (PFS) in patients with limited-stage small cell lung cancer, and compared the predictive ability of SII and platelet/lymphocyte ratio (PLR) to find a better prognostic marker. Methods: In total, 572 patients with new diagnosis of limited-stage SCLC were included in this study. The optimal threshold of SII and PLR were determined using the outcome(OS)-based method by maximizing the log-rank test statistic and the survival differences.The predictive ability of SII and PLR were compared by drawing the continuous time-dependent receiver operating characteristic curves (time-dependent ROC). Logistic multivariable analysis was performed to identify factors associated with high SII. Propensity score matching (PSM) was used to balance confounders between groups and adjust observed selection bias. Kaplan-Meier methods and Cox proportional hazards models were used to assess the impact of pre-treatment SII on OS and PFS. Results: The median age of the whole group was 60.0 (25.0-81.0) years, and the median follow-up time was 56.5 (2.5-95.4) months. The optimal cutoff value of SII and PLR were 760.6 and 137.3, respectively. The area under the time-dependent ROC curves of SII and PLR in 1-, 2- and 3-year were 0.727, 0.708, 0.680 and 0.680, 0.669, 0.649, respectively. The high SII group was correlated with pleural effusion (P = 0.001), T stage (P = 0.009), N stage (P = 0.048), and pretreatment serum sodium (P = 0.003). The median OS and PFS of the whole group was 26.0 months (95%CI 23.8-28.2) and 13.0 months (95%CI 11.3 -14.7), and the 1-, 3-, 5-year OS rates and the 1-, 3-, 5-year PFS rates were 81.1%, 35.5%, 27.1% and 52.8%, 24.8%, 19.9%, respectively.There were 414 patients after PSM. In multivariable survival analysis, SII remained an independent prognostic factor for OS (HR1.792; 95%CI 1.416-2.268; P &lt; 0.001) and PFS (HR1.410; 95%CI 1.043-1.906; P = 0.025). Conclusions: Elevated SII is an independent adverse prognostic factor in patients with limited-stage SCLC and is superior to PLR in terms of prognostic ability.

Prognostic and recurrent significance of SII in patients with pancreatic head cancer undergoing pancreaticoduodenectomy.

To investigate the clinical significance of preoperative inflammatory status in patients with pancreatic head carcinoma (PHC), we performed a single-center study to assess it. We studied a total of 164 patients with PHC undergoing PD surgery (with or without allogeneic venous replacement) from January 2018 to April 2022. Systemic immune-inflammation index (SII) was the most important peripheral immune index in predicting the prognosis according to XGBoost analysis. The optimal cutoff value of SII for OS was calculated according to Youden index based on the receiver operating characteristic (ROC) curve and the cohort was divided into Low SII group and High SII group. Demographic, clinical data, laboratory data, follow-up data variables were obtained and compared between the two groups. Kaplan-Meier curves, univariable and multivariable Cox regression models were used to determine the association between preoperative inflammation index, nutritional index and TNM staging system with OS and DFS respectively. The median follow-up time was 16 months (IQR 23), and 41.4% of recurrences occurred within 1 year. The cutoff value of SII was 563, with a sensitivity of 70.3%, and a specificity of 60.7%. Peripheral immune status was different between the two groups. Patients in High SII group had higher PAR, NLR than those in Low SII group (P <0.01, <0.01, respectively), and lower PNI (P <0.01). Kaplan-Meier analysis showed significantly poorer OS and DFS (P < 0.001, <0.001, respectively) in patients with high SII. By using the multivariable Cox regression model, high SII (HR, 2.056; 95% CI, 1.082-3.905, P=0.028) was significant predictor of OS. Of these 68 high-risk patients who recurrence within one year, patients with widespread metastasis had lower SII and worse prognosis (P <0.01). High SII was significantly associated with poor prognosis in patients with PHC. However, in patients who recurrence within one year, SII was lower in patients at TNM stage III. Thus, care needs to be taken to differentiate those high-risk patients.

Prognostic Value of Systemic Immune-Inflammation Index-Based Nomogram in Patients with Extrahepatic Cholangiocarcinoma Treated by Percutaneous Transhepatic Biliary Stenting Combined with 125I Seed Intracavitary Irradiation.

This study aimed to investigate the prognostic value of systemic immune-inflammation index (SII) in patients with extrahepatic cholangiocarcinoma (EHCC) treated by percutaneous transhepatic biliary stenting (PTBS) combined with 125I seed intracavitary irradiation and further develop a predictive model related to SII. A total of 145 patients with EHCC who received PTBS combined with 125I seed implantation were retrospectively analyzed. The optimal cut-off value of SII was identified by receiver operating characteristic (ROC) curve analysis. Kaplan-Meier curves and Cox regression were applied to estimate the prognostic value of SII and identify other significant factors of overall survival (OS). Additionally, a novel nomogram was constructed. The concordance index (C-index), calibration plots and decision curve analysis were used to evaluate the performance of the nomogram model. The optimal cut-off value for preoperative SII of 890.2 stratified the patients into High-SII (H-SII) and Low-SII (L-SII) groups. Univariate and multivariate analyses demonstrated that SII was an independent factor for OS. We also found that better therapeutic effect could be obtained with combined postoperative chemotherapy (P < 0.001). Moreover, we revealed that elevated preoperative CA19-9 (P = 0.038) and TBIL level (P = 0.024) were reason for poor prognosis of EHCC. A well-discriminated and calibrated nomogram was developed to predict the 1-year and 2-year OS of EHCC (C-index: 0.709). The SII may be a feasible and convenient prognosis predictor for EHCC. The comprehensive nomogram based on SII presented in this study is a promising model for predicting OS in EHCC patients after PTBS combined with 125I seed intracavitary irradiation.

Assessment of systemic immune-inflammation index as an independent surrogate biomarker of no-reflow phenomenon in acute coronary syndrome patients with coronary artery bypass grafting undergoing percutaneous coronary intervention of saphenous vein graft.

Numerous mechanisms have been proposed for the no-reflow phenomenon (NRP) in the literature including leukocyte intravascular plugging, microembolisms, and extrinsic coagulation pathway activation. Some of the more recent studies suggested a relationship between NRP and systemic immune-inflammation index (SII) in different contexts. To this end, the objective of this study was to investigate the relationship between NRP and SII in acute coronary syndrome (ACS) patients with coronary artery bypass grafting (CABG) who underwent percutaneous transluminal coronary angioplasty (PTCA) or percutaneous coronary intervention (PCI) of saphenous vein graft (SVG). The sample of this retrospective study consisted of 124 ACS patients with CABG who underwent PTCA/PCI of SVG. The incidence of NRP in the study group was 30.6% (n=38). The results of the multivariate logistic regression analysis indicated that ST-elevation myocardial infarction (STEMI) and SII were independent predictors for NRP (p<0.05). The receiver operating characteristic (ROC) curve analysis revealed that the optimal cut-off value of SII in predicting the development of NRP in patients undergoing PTCA/PCI of SVG and the sensitivity and specificity values thereof are 975, 74%, and 80%, respectively [Area under the curve (AUC): 0.84, 95% confidence interval (CI): 0.76-0.91, p-value <0.001]. The study findings indicated that SII, which can be easily calculated from a single complete blood count test, is an independent predictor of the development of NRP in ACS patients undergoing PTCA/PCI of the SVG.

Correlation between systemic immune inflammatory index and prognosis of patients with hepatic alveolar hydatid disease and establishment of a nomogram prediction model.

To explore the evaluation value of systemic immune inflammation index (SII) in the prognosis of patients with alveolar hydatid disease, and establish a nomogram prediction model. Collect the clinical data of 351 patients undergoing hepatic alveolar hydatid surgery admitted to the Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hospital of Qinghai University from January 2015 to December 2020, calculate the SII value, and use the receiver operating characteristic curve (ROC curve) to determine According to the optimal clinical cut-off value of SII, patients were divided into two groups with high SII and low SII, and the relationship between SII and clinicopathological factors and prognosis of patients with alveolar echinococcosis was analyzed. Establish a nomogram prediction model based on independent risk factors for patient prognosis, and evaluate the prediction accuracy and discrimination ability of the nomogram through the consistency index (C-index) and calibration curve. The result is through the use of bootstrapping validation with 1,000 re-sampling Method for internal verification. The ROC curve was used to determine the optimal cut-off value of SII before operation 761.192, and patients were divided into low SII group (n = 184) cases and high SII group (n = 167) cases. The 1, 3, and 5-year survival rates of patients with hepatic alveolar hydatid in the low SII group and the high SII group were 98.90%, 96.90%, 86.50% and 98.20%, 72.50%, 40.30%, respectively. The survival rate of worm disease patients was significantly better than that of the high SII group, and the overall survival rate difference between the two groups was statistically significant (P < 0.001). Multivariate Cox regression model analysis results showed that intraoperative blood loss (HR = 1.810, 95%CI: 1.227-2.668, P = 0.003), SII (HR = 5.011, 95%CI: 3.052-8.228, P < 0.001), Complications (HR = 1.720, 95%CI: 1.162-2.545, P = 0.007) are independent risk factors for the prognosis of patients with alveolar hydatid disease. Draw a nomogram and include statistically significant factors in the multivariate Cox regression model to predict the overall survival rate of patients with alveolar hydatid disease at 1, 3, and 5 years. The survival probability calibration curve is displayed. The nomogram is compared with The actual results have a high degree of agreement. The concordance index (C-index) of the nomogram model in the modeling sample is 0.777, and the C-index in the verification sample is 0.797, indicating that the nomogram model of this study has good accuracy and discrimination. SII has a clear correlation to the prognosis of patients with alveolar echinococcosis. The nomogram prediction model constructed on this basis is beneficial to the clinically individualized analysis of the patient's prognosis.

The Systemic Immune-Inflammation Index May Predict the Coronary Slow Flow Better Than High-Sensitivity C-Reactive Protein in Patients Undergoing Elective Coronary Angiography.

A total of 197 patients (102 patients with CSF; 95 patients with normal coronary flow) were included in this retrospective study. Clinical and angiographic characteristics of patients were obtained from hospital records. Patients with CSF had higher SII, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte (PLR), and high-sensitivity C-reactive protein (hsCRP) levels compared with the control group. Body mass index (p=0.022, OR 1.151, 95% CI 1.121-1.299), low-density lipoprotein (p=0.018, OR 1.028, 95% CI 1.005-1.052), hsCRP (p=0.044, OR 1.161, 95% CI 1.004-1.343), and SII (p < 0.001, OR 1.015, 95% CI 1.003-1.026) were independent predictors of CSF in the multivariable analysis. The optimal cutoff value of SII in predicting CSF was >877 in ROC curve analysis (p < 0.001, AUC = 0.892, 95% CI 0.848-0.936). This cutoff value of SII predicted the CSF with a sensitivity of 71.5% and specificity of 92.4%. Spearman correlation analysis showed a positive correlation between the mean TFC value and PLR, NLR, hsCRP, and SII. SII may be used as a better indicator for the prediction of CSF than hsCRP.

Evaluating systemic immune-inflammation index in patients with implantable cardioverter defibrillator for heart failure with reduced ejection fraction

Abstract Background Pro-inflammatory pathways play a serious role in the follow-up of patients with intracardiac defibrillator (ICD) for heart failure reduced with ejection fraction (HFrEF). A newly defined index, which is named as systemic immune-inflammation index (SII), has been recently reported to have prognostic value in patients with cardiovascular disease. Purpose The aim of this investigation is to evaluate the value of SII in terms of its association with long-term mortality and appropriate ICD therapy during in 10-year follow-up. Methods This retrospective study included 1011 patients with ICD for HFrEF. The study population was divided into two groups according to optimal cut-off value of SII to predict long-term mortality. The long-term prognostic impact of SII on these patients were evaluated in terms of mortality and appropriate ICD therapy. Results A receiver operating characteristic curve analyses of systemic immune-inflammation index, platelet-to-lymphocyte ratio and neutrophil-to-lymphocyte ratio in long-term mortality and appropriate intracardiac defibrillator therapy for patients intracardiac defibrillator for heart failure reduced with ejection fraction were presented in Figure 1A and 1B respectively. The patients with higher SII had significantly higher long-term mortality and appropriate ICD therapy. After adjustment for all confounding factors, the long-term mortality had 5.1 higher rates at higher SII. (95% CI: 2.9–8.1). The long-term appropriate ICD therapy also had 2.0 higher rates at higher SII (95% CI: 1.4–3.0). Kaplan Meier survival analysis of patients according to the systemic immune-inflammation index was presented in Figure 2. Conclusion SII, calculated using neutrophil, platelet, and lymphocyte counts, may be an independent predictive marker for both long-term mortality and appropriate ICD therapy in patients with HFrEF. Funding Acknowledgement Type of funding sources: None.

Preoperative Systemic Immune–Inflammation Index (SII) as a Superior Predictor of Long-Term Survival Outcome in Patients With Stage I–II Gastric Cancer After Radical Surgery

BackgroundSystemic immune–inflammation index (SII), calculated by immunoinflammatory cell counts of peripheral blood, is considered a predictor of survival outcome in several solid tumors, including gastric cancer (GC). However, there is no study focusing on the prognostic value of SII in the early stage of GC. This study aims to compare prognostic prediction capabilities of several inflammatory indices, nutritional indices, and tumor markers to further verify the superior prognostic value of SII in stage I–II GC patients after surgery.MethodsIn this study, 548 patients (358 in the training group and 190 in the validation group) with stage I–II GC after radical surgery were retrospectively analyzed. The peripheral blood indices of interest were SII, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), advanced lung cancer inflammation index (ALI), systemic inflammation score (SIS), prognostic nutritional index (PNI), body mass index (BMI), albumin, carcinoembryonic antigen (CEA), cancer antigen 125 (CA125), carbohydrate-associated antigen 19-9 (CA19-9), and alpha-fetoprotein (AFP). The time-dependent receiver operating characteristic (t-ROC) curves and the area under the curve (AUC) were used to determine the optimal cutoff value and prognostic ability of each parameter. Kaplan–Meier curves and multivariable Cox regression models were used to evaluate independent prognostic factors. The nomogram was constructed based on the result of bidirectional stepwise regression model.ResultsThe optimal cutoff value of SII was 508.3. The 5-year overall survival rate of the low SII (SII-L) group was significantly higher than that of the high SII (SII-H) group (92% vs. 80%, P < 0.001), especially in the elderly and stage II patients (91% vs. 73%, P = 0.001; 86% vs. 67%, P = 0.003, respectively). The significant prognostic values of SII were consistent in most subgroups. In multivariate analysis, SII and CA19-9 were the only two independent prognostic hematology indices. The AUC value of SII (0.624) was greater than that of CA19-9 (0.528) and other prognostic parameters. Adding SII to the conventional model improved the predictive ability of 5-year overall survival as shown by the significantly increased net reclassification improvement (NRI) and integrated discrimination improvement (IDI) (P = 0.033, P = 0.053, respectively) and modestly improved consistency index (C-index) (increased by 1.6%). External validation of SII-based nomogram demonstrated favorable predictive performance and discrimination. In addition, interactive web dynamic nomogram was published to facilitate clinical use.ConclusionSII is a simple but powerful index with a high predictive value to predict survival outcome in patients with stage I–II GC after radical operation. The SII-based nomogram can provide intuitive and accurate prognosis prediction of individual patients.

The Utility of Systemic Immune-Inflammation Index for Predicting Contrast-Induced Nephropathy in Patients with ST-Segment Elevation Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention

Objective: The systemic immune-inflammation index (SII), derived from counts of neutrophils, platelets, and lymphocytes, has been developed to predict clinical outcomes in several cancers and cardiovascular diseases. The aim of this study was to evaluate the utility of SII to predict contrast-induced nephropathy (CIN) in patients with ST-segment elevation myocardial infarction (STEMI) who underwent primary percutaneous coronary intervention (PCI). Methods: A total of 632 patients with STEMI who underwent primary PCI were retrospectively included. The patients were divided into two groups based on the presence or absence of CIN. Baseline demographic, laboratory, and clinic characteristics were evaluated between the two groups. Logistic regression analysis was used to identify independent predictors of CIN. Results: The receiver operating characteristic curve analysis demonstrated that the optimal cutoff value of SII for predicting CIN was 1,282 with a sensitivity of 76.1% and specificity of 86.7% (AUC: 0.834; 95% CI: 0.803–0.863; p < 0.001). Multivariate analysis performed in two models (SII; as separate continuous and categorical variables) showed age, estimated glomerular filtration rate (eGFR), diabetes, left ventricular ejection fraction (LVEF), Killip class ≥2, use of an intravenous diuretic, troponin I, and SII as independent predictors of CIN in model 1. In model 2, age, eGFR, diabetes, LVEF, Killip class ≥2, use of an intravenous diuretic, troponin I, and a value of SII >1,282 (p < 0.001, OR 6.205, 95% CI: 2.301–12.552) remained as independent predictors of CIN. Conclusion: SII may be a useful and reliable indicator to predict the development of CIN in patients with STEMI undergoing primary PCI than NLR and PLR.

Pretreatment systemic immune-inflammation index predicts survival for non-metastatic nasopharyngeal carcinoma: two independent institutional studies

ObjectiveThis study aimed to evaluate the prognostic value of the pretreatment systemic immune-inflammation index (SII) in non-metastatic nasopharyngeal carcinoma (NPC). MethodsWe retrospectively analyzed the data of 839 patients with non-metastatic NPC recruited from two independent institutions. The training-set cohort and the external validation-set cohort was comprised of 459 and 380 patients from each institution, respectively. The optimal cut-off value of SII was determined, and a prognostic risk stratification model was developed based on the training cohort and further assessed in the validation cohort. The propensity score matching (PSM) method was applied to minimize the confounding effects of unbalanced covariables. ResultsThe optimal cut-off value of the SII in the training cohort was 686, which was confirmed using the validation cohort. Multivariate analysis showed that both before and after PSM, SII values > 686 were independently associated with worse progression-free survival (PFS) ratio in both cohorts (before PSM, P = 0.008 and P = 0.008; after PSM, P = 0.008 and P = 0.007, respectively). Based on the analysis of independent prognostic factors of SII and N stage, we developed a categorical risk stratification model, which achieved significant discrimination among risk indexes associated with PFS and distant metastasis-free survival (DMFS) in the training cohort. There was no significant difference in PFS between RT alone and combined therapies within the low- and intermediate-risk groups (5-year PFS, 77.5% vs. 75.3%, P = 0.275). Patients in the high-risk group who received concurrent chemoradiotherapy experienced superior PFS compared with those who received other therapies (5-year PFS, 64.9% vs. 40.3%, P = 0.003). ConclusionPretreatment SII predicts PFS of patients with non-metastatic NPC. Prognostic risk stratification incorporating SII is instructive for selecting individualized treatment.

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

BackgroundThe preoperative systemic immune-inflammation index (SII) is correlated with prognosis in several malignancies. The aim of this study was to investigate the prognosis value of SII in patients with resected breast cancer.Materials and MethodsA total of 784 breast cancer patients who underwent surgical resection were consecutively investigated. The optimal cutoff value of SII was evaluated using the receiver operating characteristic (ROC) curve. The collection of SII with clinicopathological characteristic and prognosis was further evaluated.ResultsThe optimal cutoff value for SII in the prediction of survival was 514 according to ROC curve analysis. A high SII was significantly correlated with younger age (P = 0.037), PR status (P < 0.001), and HER2 status (P = 0.035). Univariate analysis revealed that SII (P < 0.001), T-stage (P < 0.001), lymph node involvement post-surgery (P = 0.024), and histological grade (P < 0.001) were significantly related to DFS, and SII (P < 0.001), T-stage (P = 0.003), lymph node involvement post-surgery (P = 0.006), and histological grade (P < 0.001) were significantly associated with OS. In multivariate analysis, a high SII was an independent worse prognostic factor for DFS (HR, 4.530; 95% CI, 3.279-6.258; P < 0.001) and OS (HR, 3.825; 95% CI, 2.594-5.640; P < 0.001) in all the enrolled patients. Furthermore, subgroup analysis of molecular subtype revealed that SII was significantly associated with prognosis in all subtypes.ConclusionPreoperative SII is a simple and useful prognostic factor for predicting long-term outcomes for breast cancer patients undergoing surgery.

Increased Systemic Immune-Inflammation Index Is Associated With Delayed Cerebral Ischemia in Aneurysmal Subarachnoid Hemorrhage Patients.

Background: Systemic immune-inflammation index (SII) is a novel biomarker that reflects the state of a patient's inflammatory and immune status. This study aimed to determine the clinical significance of SII as a predictor of delayed cerebral ischemia (DCI) in patients with aneurysmal subarachnoid hemorrhage (SAH).Methods: Retrospective data were collected from aneurysmal SAH patients who had been admitted to our hospital between January 2015 and October 2019. Both univariate and multivariate analyses were performed to investigate whether SII was an independent predictor of DCI. In addition, the receiver operating characteristic (ROC) curve and area under the curve (AUC) were also evaluated.Results: There were 333 patients with aneurysmal SAH included in this study. Multivariate logistic analysis revealed that a modified Fisher grade 3 and 4 score [odds ratio (OR) = 7.851, 95% confidence interval (CI): 2.312–26.661, P = 0.001] and elevated SII (OR = 1.001, 95% CI: 1.001–1.002, P < 0.001) were independent risk factors for DCI. ROC curves showed that SII could predict DCI with an AUC of 0.860 (95% CI: 0.818–0.896, P < 0.001). The optimal cut-off value for SII to predict DCI was 1,424, and an SII ≥ 1,424 could predict DCI with a sensitivity of 93.1% and a specificity of 68.1%. Patients with higher SII value on admission tended to have higher incidence of acute hydrocephalus and DCI, greater modified Fisher and Hunt-Hess scales, and poorer outcomes.Conclusions: SII is an independent predictor of DCI in patients with aneurysmal SAH. The SII system can be implemented in a routine clinical setting to help clinicians diagnose patients with high risk of DCI.

Association of systemic immune-inflammation index with protein-energy wasting and prognosis in patients on maintenance hemodialysis

Objective: To explore the association of systemic immune-inflammation index (SII) with protein-energy wasting (PEW) and prognosis in maintenance hemodialysis (MHD) patients. Methods: A multicenter cohort study was conducted in 11 hemodialysis centers of Guizhou province from July to September 2019. The patients were divided into the PEW group and non-PEW group. After 12 months of follow-up, death was the endpoint event. Multivariate logistic regression analysis was used to assess the independent risk factors of PEW in MHD patients. The receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive value of SII for PEW, and the optimal cut-off value of SII was calculated. The Kaplan-Meier method was used to draw the survival curve, and log-rank test was employed to compare the difference of survival rate between the two groups. Results: A total of 859 patients were included [540 males and 319 females, aged (54±15) years], and there were 220 cases (25.6%) and 639 cases (74.4%) in PEW and non-PEW groups, respectively. SII was higher in the PEW group than that of the non-PEW group [600 (440, 915) vs 475 (353, 633), P<0.01]. Multivariate logistic regression analysis showed that SII was an independent predictor for PEW (OR=1.001, 95%CI: 1.000-1.002, P=0.02). ROC curve analysis showed that the area under the curve for SII to predict PEW in MHD patients was 0.725 (95%CI: 0.683-0.766), with the sensitivity and specificity of 69% and 70%, respectively. All patients were followed up for 12 months, and 45 died (with a mortality rate of 5.24%). Patients were divided into SII>520 group and SII≤520 group according to the optimal cut-off value, and subsequent Kaplan-Meier survival analysis showed that the 1-year cumulative survival rate of the SII>520 group (92.3%) was lower than that of SII≤520 group (97.1%) (χ2log-rank=9.707, P=0.002). Further subgroup analysis revealed that, in PEW patients with MHD, the 1-year cumulative survival rate of the SII>520 group (88.5%) was also lower than that of SII≤520 group (92.3%) (χ2log-rank=7.226, P=0.007). Conclusion: SII is an independent risk factor for PEW in MHD patients, and the higher the SII level, the lower the long-term survival rate and the prognosis.

The prognostic value of inflammation markers in postoperative gliomas with or without adjuvant treatments.

Recent studies have shown that some inflammatory markers are associated with the prognosis of solid tumors. This study aims to evaluate the prognosis of glioma patients with or without adjuvant treatment using the systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), and platelet-lymphocyte ratio (PLR).All patients who were diagnosed with gliomas at the first and second affiliated hospital of Guangxi Medical University between 2011 and 2020 were included in this study. The optimal cutoff value of SII, NLR, and PLR was determined by X-tile software program. We stratified patients into several groups and evaluated the progression-free survival (PFS) and overall survival (OS) of SII, NLR, and PLR during the period of pre-surgical, con-chemoradiotherapy, and post-treatments. Multivariate Cox regression analyses were performed to detect the relationships between OS, PFS, and prognostic variables.A total of 67 gliomas patients were enrolled in the study. The cutoff values of SII, NLR, and PLR were 781.5 × 109/L, 2.9 × 109/L, and 123.2 × 109/L, respectively. Patients who are pre-SII < 781.5 × 109/L had better PFS (P = .027), but no difference in OS. In addition, patients who had low pre-NLR (<2.9 × 109/L) meant better OS and PFS. PLR after adjuvant treatments (post-PLR) was significantly higher than pre-PLR (P = .035). Multivariate analyses revealed that pre-SII, pre-NLR were independent prognostic factors for OS (pre-SII: HR 1.002, 95% CI: 1.000–1.005, P = .030 and pre-PLR: HR 0.983, 95% CI: 0.973–0.994, P = .001), while pre-PLR was an independent factor for PFS (HR 0.989, 95% CI: 0.979–1.000, P = .041).High pre-SII or high pre-NLR could be prognostic markers to identify glioma patients who had a poor prognosis.

Prognostic value of the systemic immune-inflammation index in non-muscle invasive bladder cancer

PurposeWe assessed the prognostic value of systemic immune-inflammation index (SII) to refine risk stratification of the heterogeneous spectrum of patients with non-muscle-invasive bladder cancer (NMIBC)MethodsIn this multi-institutional cohort, preoperative blood-based SII was retrospectively assessed in 1117 patients with NMIBC who underwent transurethral resection of bladder (TURB) between 1996 and 2007. The optimal cut-off value of SII was determined as 580 using the best Youden index. Cox regression analyses were performed. The concordance index (C-index) and decision curve analysis (DCA) were used to assess the discrimination of the predictive models.ResultsOverall, 309 (28%) patients had high SII. On multivariable analyses, high SII was significantly associated with worse PFS (hazard ratio [HR] 1.84; 95% confidence interval [CI] 1.23–2.77; P = 0.003) and CSS (HR 2.53; 95% CI 1.42–4.48; P = 0.001). Subgroup analyses, according to the European Association of Urology guidelines, demonstrated the main prognostic impact of high SII, with regards to PFS (HR 3.39; 95%CI 1.57–7.31; P = 0.002) and CSS (HR 4.93; 95% CI 1.70–14.3; P = 0.005), in patients with intermediate-risk group; addition of SII to the standard predictive model improved its discrimination ability both on C-index (6% and 12%, respectively) and DCA. In exploratory intergroup analyses of patients with intermediate-risk, the improved discrimination ability was retained the prediction of PFS and CSS.ConclusionPreoperative SII seems to identify NMIBC patients who have a worse disease and prognosis. Such easily available and cheap standard biomarkers may help refine the decision-making process regarding adjuvant treatment in patients with intermediate-risk NMIBC.