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

Abstract

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 569×10 9 /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. Lu et al. SII Predict Survival of TSCCConclusion: 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.

A competing risk nomogram for predicting cancer‐specific death of patients with buccal mucosa cancer

“…This discrepancy may be due to the socioeconomic differences between black people and other races in specific areas (Weng & Korte, 2012). The results showed that higher pathological stage (grade) and M1 stage were independent risk factors for BMC patients, which is consistent with the results of scholars in OSCC and TSCC research (Li et al., 2017; Lu et al., 2020; Wang et al., 2018). However, the two factors were eliminated in the process of using BIC to optimize the model and avoid over‐fitting.…”

“…A nomogram is a convenient and advanced method for estimating clinical events using multiple known variables and is widely applied in the prognostic prediction of most cancer types (Balachandran, Gonen, Smith, & DeMatteo, 2015; Iasonos, Schrag, Raj, & Panageas, 2008; Lu et al., 2020). But, most nomograms are based on the traditional Kaplan–Meier approach and Cox proportional hazard model, ignoring the occurrence of competitive events, thereby misjudged the prognosis of patients.…”

Nomogram Based on Systemic Immune Inflammation Index and Prognostic Nutrition Index Predicts Recurrence of Hepatocellular Carcinoma After Surgery

“…Therefore, SII was a convenient, low-cost, and effective inflammatory indicator to predict the prognosis of tumors. Previous studies have only reported the use of SII in nomograms for gastric and tongue cancer ( 22 , 23 ). Here, we report for the first time that nomograms based on SII can effectively predict postoperative HCC recurrence.…”

Score for predicting overall survival in pancreatic adenocarcinoma patients with positive lymph nodes after surgery: a novel nomogram-based risk assessment

“…The use of a nomogram, a novel statistical prediction model, can accurately estimate individual survival and guide plans for follow-up by integrating multiple factors (14). Furthermore, several studies have indicated the favorable results of nomogram (15) and its utility in various cancers (16)(17)(18)(19). To date, an effective nomogram for PLN-PaCs has never been developed.…”