The Relationship Between Preoperative Systemic Immune Inflammation Index and Prognostic Nutritional Index and the Prognosis of Patients With Alveolar Hydatid Disease.

To explore the relationship between the preoperative immune inflammation index (SII) and the prognostic nutritional index (PNI) and the overall survival rate (OS) of patients with alveolar hydatid disease. The clinical data of patients with hepatic alveolar echinococcosis treated by surgery in the Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hospital of Qinghai University from January 2015 to January 2019 were analyzed retrospectively, and the SII, PNI, PLR and NLR were calculated. Spearman correlation analysis was utilized to analyze the correlation among SII, PNI, PLR and NLR. Receiver operating characteristic curve (ROC) was utilized to determine the best intercept values of SII, PNI, PLR and NLR, and Chi-square test was used to evaluate the relationship between SII, PNI and various clinicopathological features in patients with hepatic alveolar echinococcosis. The kaplan-Meier method was used to draw survival curves and analyze the relationship between them and the total survival time of patients. A cox regression model was used to analyze the relationship between SII, PNI and the prognosis of patients with hepatic alveolar echinococcosis. Finally, ROC curve was used to estimate the predictive efficacy of SII, PNI and COSII-PNI for the prognosis of patients with hepatic alveolar echinococcosis. A total of 242 patients were included, including 96 males and 146 females, aged 11.0-67.0 (36.6 ± 11.7) years. The values of SII, PNI, PLR and NLR are calculated, and the best truncation values of SII, PNI, PLR and NLR are given in ROC curve. The kaplan-Meier survival curve was used to analyze the relationship between SII, PNI, PLR, NLR and the overall survival time of patients with hepatic alveolar echinococcosis. The results showed that the median follow-up time was 45 months (95%CI: 39.484-50.516), and the average survival time was 49 months (95%CI: 47.300-51.931), which was low p<0.001); The 5-year OS rate of low PNI was significantly lower than that of high PNI group (37.7% vs 71.6%; p<0.001); The 5-year OS rate in low PLR group was significantly higher than that in high PLR group (70.4% vs 24.3%; p<0.001); The 5-year OS rate in low NLR group was significantly higher than that in high NLR group (67.2% vs 28.8%; p<0.001). Cox unifoliate analysis showed that SII, PNI, PLR and NLR were important prognostic factors related to OS. Cox multivariate analysis showed that SII(HR=4.678, 95% CI: 2.581-8.480, P<0.001) and PNI(HR=0.530, 95%CI: 0.305-0.920, P<0.05) were identified as independent risk indicators of OS, while NL was identified as independent risk indicators of OS ROC curve analysis showed that AUC of SII, PNI, PLR, NLR and COSII-PNI were 0.670(95%CI: 0.601-0.738), 0.638(95%CI: 0.561-0.716) and 0.618(95% CI: 0.541-0.694), respectively COSII-PNI is superior to SII and PNI in evaluating prognosis (P < 0.05). SII and PNI can be regarded as independent risk factors reflecting the prognosis of patients with hepatic alveolar echinococcosis. The lower SII and the higher PNI before operation, the better the prognosis of patients, and the combined application of SII and PNI before operation can improve the accuracy of prediction.

Ren B ，Chen X ，Lei P ，Hou L ，Wang H ，Zhou Y ，Ren L ，Fan H ，Wang Z ，Yuan J ... -  《Frontiers in Immunology》

The prognostic value of preoperative laboratory data indicators in patients with esophageal carcinoma: An observational study.

Preoperative laboratory data indicators significantly affect the prognosis of a variety of tumors. Nevertheless, the combined effect of systemic immune-inflammation index (SII) and prognostic nutritional index (PNI) on overall survival (OS) in patients with esophageal carcinoma remains unclear. Thus, we examined these associations among patients with postoperative staged T3N0M0 esophageal carcinoma. The data of 246 patients with postoperative staged T3N0M0 esophageal carcinoma from January 1, 2010, to December 31, 2022, were retrospectively analyzed. OS was measured from the date of pathological diagnosis until either death or the last follow-up. The Kaplan-Meier method and multivariate Cox regression model were used to analyze the relationship between neutrophil-to-lymphocyte ratio (NLR), Platelet-to-lymphocyte ratio (PLR), Platelet-to-lymphocyte ratio (LMR), SII, PNI, and OS. The predictive value of SII and PNI as a combined index was analyzed by the receiver operating characteristic curve (ROC). A total of 246 patients aged 65.5 ± 7.4 years were included in this study and 181 (73.6%) were male. The univariate analysis revealed that differentiation, vessel involvement, postoperative treatment, NLR, SII, PLR, LMR, PNI were predictors of OS (P < .05). After adjusted for potential confounds, multivariate Cox regression analysis showed that the differentiation, SII, PNI, and postoperative treatment were independent prognostic factors correlated with OS in patients with postoperative staged T3N0M0 esophageal carcinoma (P < .05). SII and PNI, as a combined indicator, have a higher predictive value for OS. The NLR, SII, PLR, LMR, and PNI could all be used as independent predictors of OS in patients with postoperative staged T3N0M0 esophageal carcinoma. The combination of SII and PNI can significantly improve the accuracy of prediction.

Ma H ，Liu Y ，Ye H ，Gao F ，Li Z ，Qin S ... -  《-》

[Relationship between preoperative inflammatory indexes and prognosis of patients with rectal cancer and establishment of prognostic nomogram prediction model].

Zhang L ，Shi FY ，Qin Q ，Liu GX ，Zhang HW ，Yan J ，Tan M ，Wang LZ ，Xue D ，Hu CH ，Zhang Z ，She JJ ... -  《-》

Systemic immune-inflammation index predicting chemoradiation resistance and poor outcome in patients with stage III non-small cell lung cancer.

Tong YS ，Tan J ，Zhou XL ，Song YQ ，Song YJ ... -  《Journal of Translational Medicine》

The predictive value of a preoperative systemic immune-inflammation index and prognostic nutritional index in patients with esophageal squamous cell carcinoma.

Growing evidence indicates that systemic inflammation response and malnutrition status are correlated with survival in certain types of solid tumors. The aim of this study is to evaluate the association between the systemic immune-inflammation index (SII) and prognostic nutritional index (PNI) and overall survival (OS) in patients with esophageal squamous cell carcinoma (ESCC) after esophagectomy. A consecutive series of 655 patients with resected ESCC who underwent esophagectomy were enrolled in the retrospective study. The preoperative SII was defined as platelet × neutrophil/lymphocyte counts. The PNI was calculated as albumin concentration (g/L) + 5 × total lymphocyte count (109 /L). The optimal cut-off values of SII, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and PNI were determined by receiver operating characteristic analysis. Survival analysis was performed using the Kaplan-Meier method with a log-rank test, followed by a multivariate Cox proportional hazards model. A high SII was significantly related to tumor size, histological type, invasion depth, and TNM stage (p < 0.05). A low PNI was significantly associated with age, tumor size, invasion depth, lymph node metastasis, and TNM stage (p < 0.05). Univariate analysis revealed that age, smoking history, tumor size, invasion depth, lymph node metastasis, SII, NLR, PLR, and PNI were predictors of OS (p < 0.05). Multivariate analysis identified age (p = 0.041), tumor size (p = 0.016), invasion depth (p < 0.001), lymph node metastasis (p < 0.001), SII (p = 0.033), and PNI (p = 0.022) as independent prognostic factors correlated with OS. There was a significant inverse relationship between the SII and PNI (r = 0.309; p < 0.001). The predictive value increased when the SII and PNI were considered in combination. Our results demonstrate that the preoperative high SII and low PNI are powerful indicators of aggressive biology and poor prognosis for patients with ESCC. The combination of SII and PNI can enhance the accuracy of prognosis.

Zhang H ，Shang X ，Ren P ，Gong L ，Ahmed A ，Ma Z ，Ma R ，Wu X ，Xiao X ，Jiang H ，Tang P ，Yu Z ... -  《-》