Explore the vast range of titles available.

Inflammation indicators, such as systemic inflammation response index (SIRI), systemic immune‐inflammation index (SII), neutrophil‐to‐lymphocyte ratio (NLR) and platelet‐lymphocyte ratio (PLR), are associated with poor prognosis in various solid cancers. In this study, we investigated the predictive value of these inflammation indicators in nasopharyngeal carcinoma (NPC). This retrospective study involved 559 patients with NPC and 500 patients with chronic rhinitis, and 255 NPC patients were followed up successfully. Continuous variables and qualitative variables were measured by t test and chi‐square test, respectively. The optimal cut‐off values of various inflammation indicators were determined by receiver operating characteristic (ROC) curve. Moreover, the diagnostic value for NPC was decided by the area under the curves (AUCs). The Kaplan‐Meier methods and the log‐rank test were used to analyse overall survival (OS) and disease‐free survival (DFS). The independent prognostic risk factors for survival and influencing factors of side effects after treatment were analysed by Cox and logistic regression analysis, respectively. Most haematological indexes of NPC and rhinitis were significantly different between the two groups, and PLR was optimal predictive indicators of diagnosis. In the multivariable Cox regression analysis, PLR, WBC, RDW, M stage and age were independent prognostic risk factors. Many inflammation indicators that affected various side effects were evaluated by logistic regression analysis. In conclusion, the combined inflammation indicators were superior to single haematological indicator in the diagnosis and prognosis of NPC. These inflammation indicators can be used to supply the current evaluation system of the TNM staging system to help predict the prognosis in NPC patients.

Background We conducted a large-scale epidemiological analysis to investigate the associations between systemic inflammation markers and hypertension prevalence. Our aim is to identify potential biomarkers for early detection of hypertension. Methods A cross-sectional study with 119664 individuals from the National Health and Nutrition Examination Survey was performed. We investigated the associations between three systemic inflammation markers, namely the systemic immune inflammation index (SII), system inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI), and the prevalence of hypertension. Results The prevalence rates of hypertension gradually increased with increasing logSII, logSIRI, and logAISI quartiles. In continuous analyses, each unit increase in logSII, logSIRI, and logAISI was associated with a 20.3%, 20.1%, and 23.7% increased risk of hypertension. Compared to those in the lowest quartiles, the hypertension risks for subjects in the highest logSII, logSIRI, and logAISI quartiles were 1.114-fold,1.143-fold, and 1.186-fold. The restricted cubic splines (RCS) analysis revealed a non-linear relationship between the elevation of systemic inflammation markers and hypertension prevalence. Specifically, a per standard deviation increase in any of these variables is associated with a respective 9%, 16%, and 11% increase in hypertension prevalence. Conclusion Our cross-sectional study reveals significant positive correlations between SII, SIRI, and AISI with the prevalence of hypertension.

Chronic inflammation is a common complication in peritoneal dialysis (PD) patients. The aim of this study is to investigate the capacity of aggregate index of systemic inflammation (AISI), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI) to predict all-cause mortality in PD patients. This was a single-center retrospective study. The optimal cutoff values were identified by receiver operating characteristic (ROC) curve analysis. The area under the curve (AUC) was calculated to evaluate the predictive ability of these indexes. The Kaplan-Meier curves and log-rank test were performed to estimate cumulative survival rate. Cox proportional hazards regression analyses were conducted to determine the independent prognostic power of inflammation indexes. A total of 369 incident PD patients were involved. During a median follow-up period of 32.83 months, 65 patients (24.2%) died. The ROC analysis indicated the largest value of AUC was obtained for SII (AUC = 0.644, 95% CI = 0.573-0.715, p < .001), followed in order by AISI (AUC = 0.617, 95% CI = 0.541-0.693, p = .003), and SIRI (AUC = 0.612, 95% CI = 0.535-0.688, p  = .004). The Kaplan-Meier survival curves revealed significantly lower survival rate with higher AISI (p  = .001), higher SSI (p  = .001), and higher SIRI (p  = .003). Even after adjustment for the confounding factors, higher AISI [hazard ratio (HR)=2.508, 95% confidence intervals (CI)=1.505-4.179, p < .001), SII (HR = 3.477, 95% CI = 1.785-6.775, p < .001), and SIRI (HR = 1.711, 95% CI = 1.012-2.895, p  = .045) remained as independent predictors of all-cause mortality. The higher AISI, SII, and SIRI were independent indicators of all-cause mortality in PD patients. Furthermore, they could provide comparable predictive value and assist clinicians to ameliorate PD management.

Background Systemic inflammation markers have recently been identified as being associated with cardiac disorders. However, limited research has been conducted to estimate the pre-diagnostic associations between these markers and paroxysmal atrial fibrillation (PAF). Our aim is to identify potential biomarkers for early detection of PAF. Methods 91 participants in the PAF group and 97 participants in the non-PAF group were included in this study. We investigated the correlations between three systemic inflammation markers, namely the systemic immune inflammation index (SII), system inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI), and PAF. Results The proportion of patients with PAF gradually increased with increasing logSII, logSIRI, and logAISI tertiles. Compared to those in the lowest tertiles, the PAF risks in the highest logSII and logSIRI tertiles were 3.2-fold and 2.9-fold, respectively. Conversely, there was no significant correlation observed between logAISI and PAF risk within the highest tertile of logAISI. The restricted cubic splines (RCS) analysis revealed a non-linear relationship between the elevation of systemic inflammation markers and PAF risk. Specifically, the incidence of PAF is respectively increased by 56%, 95%, and 150% for each standard deviation increase in these variables. The ROC curve analysis of logSII, logSIRI and logAISI showed that they had AUC of 0.6, 0.7 and 0.6, respectively. It also demonstrated favorable sensitivity and specificity of these systemic inflammation markers in detecting the presence of PAF. Conclusions In conclusion, our study reveals significant positive correlations between SII, SIRI, and AISI with the incidence of PAF.

Significant evidence suggests that asthma might originate from low-grade systemic inflammation. Previous studies have established a positive association between the systemic immune-inflammation index (SII) and the systemic inflammation response index (SIRI) levels and the risk of stroke. However, it remains unclear whether SII, SIRI and the prevalence of stroke are related in individuals with asthma.BackgroundSignificant evidence suggests that asthma might originate from low-grade systemic inflammation. Previous studies have established a positive association between the systemic immune-inflammation index (SII) and the systemic inflammation response index (SIRI) levels and the risk of stroke. However, it remains unclear whether SII, SIRI and the prevalence of stroke are related in individuals with asthma.The present cross-sectional study used data from the National Health and Nutrition Examination Survey (NHANES) conducted between 1999 and 2018. SII was calculated using the following formula: (platelet count × neutrophil count)/lymphocyte count. SIRI was calculated using the following formula: (neutrophil count × monocyte count)/lymphocyte count. The Spearman rank correlation coefficient was used to determine any correlation between SII, SIRI, and the baseline characteristics. Survey-weighted logistic regression was employed to calculate odds ratios (ORs) and 95% confidence intervals (CIs) to determine the association between SII, SIRI, and stroke prevalence. The predictive value of SII and SIRI for stroke prevalence was assessed through receiver operating characteristic (ROC) curve analysis, with the area under the ROC curve (AUC) being indicative of its predictive value. Additionally, clinical models including SIRI, coronary heart disease, hypertension, age, and poverty income ratio were constructed to evaluate their clinical applicability.MethodsThe present cross-sectional study used data from the National Health and Nutrition Examination Survey (NHANES) conducted between 1999 and 2018. SII was calculated using the following formula: (platelet count × neutrophil count)/lymphocyte count. SIRI was calculated using the following formula: (neutrophil count × monocyte count)/lymphocyte count. The Spearman rank correlation coefficient was used to determine any correlation between SII, SIRI, and the baseline characteristics. Survey-weighted logistic regression was employed to calculate odds ratios (ORs) and 95% confidence intervals (CIs) to determine the association between SII, SIRI, and stroke prevalence. The predictive value of SII and SIRI for stroke prevalence was assessed through receiver operating characteristic (ROC) curve analysis, with the area under the ROC curve (AUC) being indicative of its predictive value. Additionally, clinical models including SIRI, coronary heart disease, hypertension, age, and poverty income ratio were constructed to evaluate their clinical applicability.Between 1999 and 2018, 5,907 NHANES participants with asthma were identified, of which 199 participants experienced a stroke, while the remaining 5,708 participants had not. Spearman rank correlation analysis indicated that neither SII nor SIRI levels exhibited any significant correlation with the baseline characteristics of the participants (r<0.1). ROC curves were used to determine the optimal cut-off values for SII and SIRI levels to classify participants into low- and high-level groups. Higher SII and SIRI levels were associated with a higher prevalence of stroke, with ORs of 1.80 (95% CI, 1.18-2.76) and 2.23 (95% CI, 1.39-3.57), respectively. The predictive value of SIRI (AUC=0.618) for stroke prevalence was superior to that of SII (AUC=0.552). Furthermore, the clinical model demonstrated good predictive value (AUC=0.825), with a sensitivity of 67.1% and specificity of 87.7%.ResultsBetween 1999 and 2018, 5,907 NHANES participants with asthma were identified, of which 199 participants experienced a stroke, while the remaining 5,708 participants had not. Spearman rank correlation analysis indicated that neither SII nor SIRI levels exhibited any significant correlation with the baseline characteristics of the participants (r<0.1). ROC curves were used to determine the optimal cut-off values for SII and SIRI levels to classify participants into low- and high-level groups. Higher SII and SIRI levels were associated with a higher prevalence of stroke, with ORs of 1.80 (95% CI, 1.18-2.76) and 2.23 (95% CI, 1.39-3.57), respectively. The predictive value of SIRI (AUC=0.618) for stroke prevalence was superior to that of SII (AUC=0.552). Furthermore, the clinical model demonstrated good predictive value (AUC=0.825), with a sensitivity of 67.1% and specificity of 87.7%.In asthmatics, higher levels of SII and SIRI significantly increased the prevalence of stroke, with its association being more pronounced in individuals with coexisting obesity and hyperlipidaemia. SII and SIRI are relatively stable novel inflammatory markers in the asthmatic population, with SIRI having a better predictive value for stroke prevalence than SII.ConclusionIn asthmatics, higher levels of SII and SIRI significantly increased the prevalence of stroke, with its association being more pronounced in individuals with coexisting obesity and hyperlipidaemia. SII and SIRI are relatively stable novel inflammatory markers in the asthmatic population, with SIRI having a better predictive value for stroke prevalence than SII.

The associations of two novel inflammation biomarkers, systemic inflammation response index (SIRI) and systemic immune inflammation index (SII), with mortality risk in patients with chronic heart failure (CHF) are not well-characterized. This retrospective cohort study included patients with CHF in two medical centers of Chinese People's Liberation Army General Hospital, Beijing, China. The outcomes of this study included in-hospital mortality and long-term mortality. Associations of SIRI and SII with mortality were assessed using multivariable regressions and receiver operating characteristic (ROC) analyses. A total of 6232 patients with CHF were included in the present study. We documented 97 cases of in-hospital mortality and 1738 cases of long-term mortality during an average 5.01-year follow-up. Compared with patients in the lowest quartile of SIRI, those in the highest quartile exhibited 134% higher risk of in-hospital mortality (adjusted odds ratio, 2.34; 95% confidence interval [CI], 1.16-4.72) and 45% higher risk of long-term mortality (adjusted hazard ratio, 1.45; 95% CI, 1.25-1.67). Compared with patients in the lowest quartile of SII, those in the highest quartile exhibited 27% higher risk of long-term mortality (adjusted hazard ratio, 1.27; 95% CI, 1.11-1.46). In ROC analyses, SIRI showed better prognostic discrimination than C-reactive protein (area under the curve: 69.39 vs 60.91, = 0.01, for in-hospital mortality; 61.82 vs 58.67, = 0.03, for 3-year mortality), whereas SII showed similar prognostic value with C-reactive protein. SIRI and SII were significantly associated with mortality risk in patients with CHF. SIRI may provide better prognostic discrimination than C-reactive protein.

Inflammation can influence how tumors develop and is linked to patient outcomes. We studied a new marker called the Modified Neutrophil Platelet Score (MNPs), which uses blood neutrophil and platelet counts. This research aimed to verify if MNPs and other clinical markers help doctors better predict disease severity after surgery for people with colorectal cancer. We reviewed records from 503 patients with colorectal cancer. All patients had curative surgery at the Second Affiliated Hospital of Harbin Medical University (2016-2018). We collected their blood test results one week before surgery, including neutrophil, platelet, lymphocyte, and monocyte counts, plus CEA and CA199 levels. Using Kaplan-Meier analysis, we examined how MNPs relates to patients' overall survival (OS) and recurrence-free survival (RFS). We performed univariate and multivariate Cox regression analyses. To compare MNPs with other inflammation markers, we calculated time-dependent ROC curves, C-index, and Brier scores. Overall Survival (OS): Patients with lower MNPs (score 0) lived longer. Compared to score 0 patients, those with score 1 had shorter survival (HR = 3.180, 95% CI 2.028-4.988, p < 0.001), and score 2 patients lived significantly shorter lives (HR = 7.430, 95% CI 4.672-11.816, p < 0.001). Recurrence-Free Survival (RFS): Patients with lower MNPs (score 0) stayed cancer-free longer. Score 1 patients had higher recurrence risk than score 0 patients (HR = 3.790, 95% CI 2.065-6.954, p < 0.001), while score 2 patients faced the highest recurrence risk (HR = 10.023, 95% CI 5.428-18.510, p < 0.001). Multivariate analysis confirmed MNPs independently predicts OS and RFS outcomes. Time-dependent ROC curves, C-index, and Brier scores showed MNPs predicts patient outcomes more accurately than other inflammation markers. MNPs can help doctors predict outcomes for people with colorectal cancer. Patients with lower MNPs tend to live longer and stay cancer-free longer after surgery.

Systemic inflammation response index (SIRI=N×M/L), based on neutrophil (N), monocyte (M), and lymphocyte (L) counts, is used to predict the survival of patients with malignant tumors and can fully evaluate the balance between host immune and inflammatory condition. The present study is aimed to evaluate the potential prognostic significance of SIRI in patients with breast cancer undergoing neoadjuvant chemotherapy. A total of 262 breast cancer patients treated with neoadjuvant chemotherapy were enrolled in this retrospective study. The optimal cutoff value of SIRI by receiver operating characteristic curve stratified patients into low SIRI (<0.85×10 /L) group and high SIRI (≥0.85×10 /L) group. The associations between breast cancer and clinicopathological variables by SIRI were determined by chi-square test or Fisher's exact test. Kaplan-Meier plots and log-rank test were used to evaluate the clinical outcomes of disease-free survival (DFS) and overall survival (OS). Univariate and multivariate Cox proportional hazards regression models were used to analyze the prognostic value of SIRI. The toxicity of neoadjuvant chemotherapy was evaluated by the National Cancer Institute Common Toxicity Criteria (NCICTC). The results were shown that SIRI had prognostic significance by optimal cutoff value of 0.85×10 /L on DFS and OS in univariate and multivariate Cox regression survival analyses. Compared with patients who had high SIRI, patients with low SIRI had longer DFS and OS (41.27 vs 30.45 months, HR: 1.694, 95% CI: 1.128-2.543, P=0.011; 52.86 vs 45.75 months, HR: 1.288, 95% CI: 0.781-3.124, P=0.002, respectively). The patients with low SIRI had better 3-, 5-, and 10-year rates of DFS and OS than those with high SIRI. The common toxicities after neoadjuvant chemotherapy were hematologic and gastrointestinal reaction, and the SIRI had no significance on toxicities of all enrolled patients, excepted diarrhea. In patients without neural invasion, those with low SIRI had better prognosis and lower recurrence rates than those with high SIRI. Pretreatment SIRI with the advantage of repeatable, convenient, and non-invasive is a useful prognostic indicator for breast cancer patients who received neoadjuvant chemotherapy and is a promising biomarker for breast cancer on treatment strategy decisions.

Our study focuses on the relationship between inflammatory biomarkers and hypertension among sedentary adults in the United States, using data from the National Health and Nutrition Examination Survey (NHANES) from 2009 to 2018. We categorized 24,614 participants into two groups based on their daily sedentary time: 9607 individuals in the sedentary group (≥7 h) and 15,007 in the non‐sedentary group (<7 h). We found that the sedentary group had a significantly higher prevalence of hypertension than the non‐sedentary group. Using weighted multiple logistic regression and smoothing curves, we assessed the correlation between inflammatory biomarkers and hypertension among the sedentary adults. The odds ratios for hypertension were 1.92 for the monocyte to high‐density lipoprotein ratio (MHR), 1.15 for the systemic inflammation response index (SIRI), and 1.19 for the natural logarithm of the systemic immune‐inflammation index (lnSII), all showing nonlinear associations. Furthermore, a significant positive correlation was found between sedentary time and inflammatory biomarkers (MHR, SIRI, and lnSII). Our findings suggest that prolonged sedentary behavior in the US significantly increases hypertension risk, likely due to marked increases in inflammation markers.

Purpose The aim of this study was to investigate the level of peripheral blood systemic immune indexes in pseudoexfoliation syndrome (PXS) patients and to compare the results with healthy controls. Methods This study included 143 healthy controls (group 1) and 100 patients (group 2). Peripheral blood samples were collected from all participants. Neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), monocyte to lymphocyte ratio (MLR), systemic immune inflammation index (SIII), systemic inflammation response index (SIRI), systemic inflammation modulation index (SIMI) and aggregate systemic inflammation index (AISI) were calculated. Results According to complete blood count, leukocyte, monocyte and platelet counts showed a statistically significant difference between the two groups ( p  < 0.001 for all). Systemic immune indexes (NLR, PLR, SIII, SIRI, SIMI and AISI) in group 2 were statistically significantly higher compared to group 1 (PLR for p  = 0.011, others p  < 0.001). Conclusion In conclusion, systemic immune indexes (NLR, MLR, PLR, SIII, SIRI, AISI and SIMI) were elevated in PXS patients compared to healthy controls. These indexes may serve as an easy, simple and cost-effective tool to assess the degree of systemic inflammation in patients, playing an important role in recognizing the underlying mechanisms of diseases and thus potentially guiding treatment.