Nomogram Based on Systemic Immune-Inflammation Index to Predict Survival of Tongue Cancer Patients Who Underwent Cervical Dissection.

Aim: The aim of this study was to evaluate the prognostic significance of the preoperative systemic immune-inflammation index (SII) and to establish a nomogram for prediction of survival of tongue squamous cell carcinoma (TSCC) patients who underwent primary surgery and cervical dissection. Methods: 120 patients diagnosed with TSCC who underwent primary tumor and neck dissection without preoperative treatment were included to develop the nomogram. This model was externally validated in an independent data cohort of 50 TSCC patients. X-tile software was used to identify the optimal cut-off value. Prognostic factors were identified by Univariate and multivariate analyses. A nomogram based on the multivariate analysis results was built to predict the survival rate and calibration curves and concordance index (C-index) were used to determine predictive and discriminatory capacity. Results: The optimal cut-off value was 569×109/L for SII. In the training cohort, a high preoperative SII (>569) was significantly related to tumor size, histological grade, depth of invasion, lymph node density (LND). A Kaplan-Meier survival analysis showed that patients with a lower SII had a significantly better 5-year overall survival (OS) and disease-free survival (DFS) than patients with high SII (80.8% vs. 43.5% and 72.7% vs. 36.2%, respectively, P<0.001). Univariate analyses of training cohort revealed that age, clinical stage, depth of invasion, LND, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and SII were significant prognostic factors for OS. Moreover, the receiver operating characteristics (ROC) curve showed that SII was superior to NLR and PLR for predicting clinical outcomes. However, multivariate analysis found that age, LND, and SII were independent risk factors for OS. The C-index of the nomograms based on independent prognostic factors was 0.716 for OS and 0.723 for DFS. The C-indexes for external validation of OS and DFS were 0.852 and 0.754, respectively. The calibration curves showed good agreement between predicted and actual observations of OS and DFS. Conclusion: SII can serve as a novel independent prognostic factor for OS and DFS of patients with TSCC. The prognostic nomogram based on SII is a reliable model for predicting survival of patients with TSCC after surgery.

Lu Z ，Yan W ，Liang J ，Yu M ，Liu J ，Hao J ，Wan Q ，Liu J ，Luo C ，Chen Y ... -  《Frontiers in Oncology》

[Establishment and verification of a prognostic nomogram for survival of tongue squamous cell carcinoma patients who underwent cervical dissection].

Su J ，Wang X ，Sun Z 《-》

[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 ... -  《-》

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 ... -  《-》

Development and validation of a nomogram based on multiple preoperative immunoinflammatory indexes for survival prediction in patients with stage IA-IB endometrial cancer.

To evaluate the preoperative systemic immune-inflammation index (SII), advanced lung cancer inflammation index (ALI), neutrophil to lymphocyte ratio (NLR), and prognostic nutritional index (PNI) capacity to predict the prognosis of stage IA-IB endometrial carcinoma (EC) patients after operation, and establish a nomogram model to guide clinical practice. A total of 387 patients with EC (R0 resection, stage IA-IB) were assessed. Clinical information and the SII, NLR, ALI, and PNI values were obtained. The low and high ratio groups were separated using the receiver operating characteristic curve (ROC). Pearson's χ2-test or Fisher's exact test was used to determine their relationship with clinical variables. To determine the independent prognostic factors, Cox regression was utilized to do the univariate and multivariate survival analyses. The Kaplan-Meier method was used to draw the survival curve in our survival analysis. Depending upon the independent prognostic factors, the nomogram for Overall survival (OS) and Disease-free survival (DFS) nomogram was developed, and its discrimination ability was validated by the consistency index (C-index) and calibration curve. Cox regression analysis revealed that FIGO staging, Ki-67 expression level, PNI, and ALI are independent prognostic factors for both OS and DFS. Then a novel predictive nomogram was developed, and its C-index value for OS and DFS was 0.829 and 0.814, respectively. The calibration curves demonstrated consistency amid the predicted prognosis using the developed nomogram and the actual observed outcomes. The ALI and PNI could serve as readily available prognostic indicators for OS and DFS prediction in stage IA-IB EC patients. The nomogram developed owned superior power for OS and DFS prediction in stage IA-IB EC patients, and it would assist clinical oncologists in accurately predicting the individual's OS and DFS.

Zhang N ，Liu H ，Yang J ，Zhong F ... -  《American Journal of Translational Research》