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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.

Background Explore markers to predict the clinical outcomes of checkpoint inhibitors have high unmet needs. The following study investigates whether hematologic parameter such as systemic immune‐inflammation index (SII), neutrophil‐to‐lymphocyte ratio (NLR), platelet‐to‐lymphocyte ratio (PLR) is associated with nivolumab efficacy in advanced non‐small‐cell lung cancer (NSCLC). Methods Advanced/metastatic NSCLC patients treated with nivolumab monotherapy for second‐line or further‐line treatment at Jilin Cancer Hospital between March 2016 and July 2018 were enrolled in this retrospective study. The optimal cutoff values of SII, NLR, and PLR for predicting efficacy and prognosis were determined according to receiver operating characteristic (ROC) curve and the areas under the ROC curve. Progression‐free survival (PFS) and overall survival (OS) were calculated and compared using Kaplan‐Meier method and log‐rank test. Prognostic values of each variable were evaluated with univariate and multivariate Cox proportional hazard regression (PHR) analyses. Results A total of 44 patients with advanced NSCLC were included; the median age was 60 (range: 43‐74). The optimal cutoff value of SII/NLR/PLR predicted PFS and OS was 603.5, 3.07, and 144. Low SII, NLR, and PLR were associated with longer PFS (HR for SII = 0.34, 95%CI 0.15‐0.76, P = 0.006; HR for NLR = 0.46, 95%CI 0.22‐0.99, P = 0.048; HR for PLR = 0.39, 95%CI 0.17‐0.94, P = 0.025) and OS (HR for SII = 0.16, 95%CI 0.05‐0.51, P = 0.005; HR for NLR = 0.20, 95%CI 0.06‐0.62, P = 0.002; HR for PLR = 0.20, 95%CI 0.06‐0.73, P = 0.008). NLR ≤ 3.07, PLR ≤ 144, SII ≤ 603.5 were independently associated with longer PFS and OS. Conclusion The SII, NLR, and PLR are promising prognostic predictor for patients with metastatic NSCLC patients.

Background The systemic immune‐inflammation index (SII) is a recently developed indicator for systemic inflammatory response. We aimed to explore the association between SII and disease activity in patients with ankylosing spondylitis (AS). Methods This retrospective study included 136 patients with AS and 63 healthy controls. Patients were divided into two groups according to Bath Ankylosing Spondylitis Disease Activity Index (BASDAI); active group (n = 60) and remission group (n = 76). Clinical, laboratory, and demographic characteristics were recorded. Spearman's correlation analysis was used to determine correlations of SII with C‐reactive protein (CRP) level, erythrocyte sedimentation rate (ESR), and BASDAI in AS patients. Binary logistic regression analysis was used to assess risk factors for AS disease activity. Receiver operating characteristic curve analysis was used to evaluate the diagnostic value of SII and the above variables for the active group compared with the remission group. Results Systemic immune‐inflammation index levels were higher in AS patients than in healthy controls (p < 0.001). SII levels were higher in the active group than in the remission group (p < 0.001). For patients with AS, SII correlated positively with CRP (rs = 0.483, p < 0.001), ESR (rs = 0.374, p < 0.001), and BASDAI (rs = 0.667, p < 0.001). SII (OR = 1.009, 95% CI = 1.006–1.012, p < 0.001) was an independent risk factor affecting AS disease activity. The specificity and sensitivity of SII using a cutoff value of 513.2 were 83.33% and 86.84%, respectively, for the active group. Conclusion Systemic immune‐inflammation index was increased in AS. SII may be a novel indicator for monitoring AS disease activity. The systemic immune‐inflammation index (SII) is a developed indicator for systemic inflammatory response. This study showed that SII was higher in AS. This study reveals that SII may be a novel indicator for monitoring AS disease activity.

Evidence of the prognostic value of pretreatment systemic immune-inflammation index (SII) after radical cystectomy (RC) for bladder cancer is limited. This study aims to assess the association between preoperative SII and prognosis after RC for bladder cancer. In this multicenter retrospective study, we calculated preoperative SII as well as the neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) in 237 patients who underwent RC for bladder cancer between March 2009 and March 2018. Patients were classified into high SII and low SII groups by using the optimal cutoff value (438 × 109/L) based on receiver operating characteristic curve analysis for cancer-specific death. We compared cancer-specific survival (CSS) and overall survival (OS) between the two groups. To evaluate the prognostic impact of preoperative SII, we also performed Cox proportional regression analyses for CSS and OS. Of 237 patients, 127 patients were classified into the high SII group and 110 patients into the low SII group. During the follow-up period, 70 patients died of bladder cancer (30%) and 21 patients died from other causes (9%). Patients with high SII had significantly lower rates of CSS and OS than those with low SII (p < 0.01 and p < 0.01, respectively). Multivariable Cox proportional hazard analysis showed that high SII was independently associated with poor CSS (p = 0.01) and poor OS (p < 0.01). In conclusion, high SII could be an independent significant predictor of poor prognosis after RC in patients with bladder cancer.

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.

The systemic immune‐inflammation index (SII = N × P/L) based on neutrophil (N), platelet (P) and lymphocyte (L) counts is used to predict the survival of patients with malignant tumours and can fully reflect the balance between host inflammatory and immune status. This study is conducted to explore the potential prognostic significance of SII in patients with breast cancer undergoing neoadjuvant chemotherapy (NACT). A total of 262 patients with breast cancer received NACT were enrolled in this study. According to the receiver operating characteristic curve, the optimal cut‐off value of SII was divided into two groups: low SII group (<602 × 109/L) and high SII group (≥602 × 109/L). The associations between breast cancer and clinicopathological variables by SII were determined by chi‐squared test or Fisher's exact test. The Kaplan‐Meier plots and log‐rank test were used to determine clinical outcomes of disease‐free survival (DFS) and overall survival (OS). The prognostic value of SII was analysed by univariate and multivariate Cox proportional hazards regression models. The toxicity of NACT was accessed by National Cancer Institute Common Toxicity Criteria (NCICTC). According to univariate and multivariate Cox regression survival analyses, the results showed that the value of SII had prognostic significance for DFS and OS. The patients with low SII value had longer DFS and OS than those with high SII value (31.11 vs 40.76 months, HR: 1.075, 95% CI: 0.718‐1.610, P = .006; 44.47 vs 53.68 months, HR: 1.051, 95% CI: 0.707‐1.564, P = .005, respectively). The incidence of DFS and OS in breast cancer patients with low SII value was higher than that in those patients with high SII value in 3‐, 5‐ and 10‐year rates. The common toxicities after NACT were haematological and gastrointestinal reaction, and there were no differences by SII for the assessment of side effects of neoadjuvant chemotherapy. Meanwhile, the results also proved that breast cancer patients with low SII value and high Miller and Payne grade (MPG) survived longer than those breast cancer with high SII value and low MPG grade. In patients without lymph vessel invasion, these breast cancer patients with low SII value had better prognosis and lower recurrence rates than those with high SII value. Pre‐treatment SII with the advantage of reproducible, convenient and non‐invasive was a useful prognostic indicator for breast cancer patients undergoing neoadjuvant chemotherapy and is a promising biomarker for breast cancer on treatment strategy decisions.

A systemic immune-inflammation index (SII) based on neutrophil ( ), lymphocyte ( ), and platelet ( ) counts has shown a prognostic impact in several solid tumors. The aim of this study is to evaluate the prognostic role of SII in metastatic castration-resistant prostate cancer (mCRPC) patients treated with abiraterone post docetaxel. We retrospectively reviewed consecutive mCRPC patients treated with abiraterone after docetaxel in our Institutions. X-tile 3.6.1 software, cut-off values of SII, neutrophil-to-lymphocyte ratio (NLR) defined as N/L and platelets-to-lymphocyte ratio (PLR) as P/L. Overall survival (OS) and their 95% Confidence Intervals (95% CI) was estimated by the Kaplan-Meier method and compared with the log-rank test. The impact of SII, PLR, and NLR on overall survival (OS) was evaluated by Cox regression analyses and on prostate-specific antigen (PSA) response rates were evaluated by binary logistic regression. A total of 230 mCRPC patients treated abiraterone were included. SII ≥ 535, NLR ≥ 3 and PLR ≥ 210 were considered as elevated levels (high risk groups. The median OS was 17.3 months, 21.8 months in SII < 535 group and 14.7 months in SII ≥ 535 ( < 0.0001). At univariate analysis Eastern Cooperative Oncology Group (ECOG) performance status, previous enzalutamide, visceral metastases, SII, NLR, and PLR predicted OS. In multivariate analysis, ECOG performance status, previous enzalutamide, visceral metastases, SII, and NLR remained significant predictors of OS [hazard ratio (HR) = 5.08, < 0.0001; HR = 2.12, = 0.009, HR = 1.77, 95% = 0.012; HR = 1.80, = 0.002; and HR = 1.90, = 0.001, respectively], whereas, PLR showed a borderline ability only (HR = 1.41, = 0.068). SII and NLR might represent an early and easy prognostic marker in mCRPC patients treated with abiraterone. Further studies are needed to better define their impact and role in these patients.

Although hypertension is considered high intravascular pressure, impairing circadian blood pressure (BP) has been shown to potentially contribute to poor clinical outcomes. Systemic immune‐inflammation index (SII), based on platelet, neutrophil, and lymphocyte counts, has been established as a strong prognostic marker in cardiovascular disease. The role of inflammation in the pathogenesis of hypertension is a well‐known issue and inflammatory markers are associated with BP variability. We aimed to investigate whether there is a relationship between circadian BP changes and SII in newly diagnosed hypertensive patients. The study population consisted of 196 newly diagnosed hypertensive patients without LVH. In total, 76 (38%) patients had a dipper BP pattern, 60 (31%) patients had a non‐dipper BP pattern, and 60 (31%) patients had a reverse‐dipper BP pattern. SII was calculated according to Multivariate logistic regression analysis revealed SII and HDL‐C as an independent predictors of reverse‐dipper circadian pattern in newly diagnosed hypertensive patients. The cut‐off value of the SII for reverse‐dipper hypertension in a ROC curve analysis was >639.73 with 63.3% sensitivity and 84.2% specificity. Our study showed that the SII level was higher in the reverse‐dipper hypertension patient group than in the dipper and non‐dipper hypertension groups. Furthermore, SII was an independent predictor of newly diagnosed reverse‐dipper hypertensive patients. The high SII value in newly diagnosed hypertensive patients can be used as an early warning parameter to identify reverse‐dipper hypertension patients.

Type 2 diabetes mellitus (DM) is a recognized independent risk factor for both chronic coronary syndrome (CCS) and its complication, acute coronary syndrome (ACS). Patients with DM and prediabetes (preDM) face an increased ACS risk. Inflammation plays a significant role in the pathogenesis of both CCS and ACS. This study delves into novel inflammatory markers, such as the systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI, also known as SIIRI or PIV), to explore their relationship with ACS and CCS in patients that have been or have not been diagnosed with DM or preDM. This study included data of 493 patients with chest pain undergoing coronary angiography. They were categorized into four groups: 1) without DM/preDM and with CCS; 2) with both DM/preDM and CCS; 3) without DM/preDM and with ACS, 4) with both DM/preDM and ACS. Standard methods of statistical analysis were used to reveal possible differences between groups and to find the most influential ACS risk factors in groups with DM/preDM and without DM/preDM. The analysis showed no significant differences in SII, SIRI, or AISI between the respective patient groups. A logistic regression analysis generated a model incorporating SII, high-density lipoprotein, and low-density lipoprotein levels as the influential ACS risk factors for patients with DM/preDM. The model demonstrated 71.0% accuracy, 37.0% sensitivity, and 89.4% specificity. The findings suggest that the aforementioned inflammatory markers may have potential for distinguishing DM/preDM patients at higher risk of ACS at a low financial cost. However, further comprehensive and well-designed research is required to validate their clinical utility.

Background Postmenopausal osteoporosis (PMOP) is a bone metabolism disorder involving systematic inflammation activation. Blood routine examination is easily available in clinical practice and contains abundant information reflecting the systematic inflammation level. Thus, it is attractive to achieve early diagnosis of PMOP and predict osteoporotic fracture risk just based on the biomarkers in blood routine examination. Methods A multi‐centric prospective cohort study was designed and enrolled postmenopausal women from two independent institutions. All participants underwent the dual‐energy X‐ray absorptiometry (DEXA) scanning for diagnosing PMOP. Blood routine examination was conducted, and the key inflammatory biomarkers such as neutrophil‐to‐lymphocyte ratio (NLR) and systemic immune‐inflammation index (SII) were calculated. PMOP patients were followed up to observe osteoporotic fracture and identify the related risk predictors. Results A total of 92 participants out of 238 enrolled postmenopausal women were diagnosed with PMOP, with a prevalence of 38.66%. The main risk factors identified for PMOP included older age (OR = 2.06, 95% CI = 1.14‐3.72), longer menopause duration (OR = 3.14, 95% CI = 2.06‐4.79), higher NLR (OR = 2.11, 95% CI = 1.37‐3.25), and higher SII (OR = 3.02, 95% CI = 1.98‐4.61). Besides age and menopause duration, SII ≥834.89 was newly identified as a prominent risk factor for discriminating osteoporotic fracture risk in PMOP patients (HR = 3.66, 95% CI = 1.249‐10.71). Conclusion As an easy and economical biomarker calculated from blood routine examination, SII not only acts as a good risk predictor for PMOP diagnosis but also well discriminates the osteoporotic fracture risk, which deserves further investigation and application in clinical practice.