The Impacts of Systemic Immune-Inflammation Index on Clinical Outcomes in Gallbladder Carcinoma

Background: Systemic immune-inflammation index (SII) is considered to be a prognostic marker in several cancers. However, the prognostic value of baseline pre-operative SII in gallbladder carcinoma (GBC) has not been evaluated. This study aimed to determine the prognostic significance of SII and generate a predictive nomogram. Methods: We retrospectively studied 142 GBC patients who underwent surgical resection at the Peking Union Medical College Hospital between 2003 and 2017. SII, neutrophil-to-lymphocyte ratio (NLR), and lymphocyte-to-monocyte ratio (LMR) were evaluated for their prognostic values. A multivariate Cox proportional hazards model was used for the recognition of significant factors. Then, the cohort was randomly divided into the training and the validation set. A nomogram was constructed using SII and other selected indicators in the training set. C-index, calibration plots, and decision curve analysis were performed to assess the nomogram's clinical utility in both the training and the validation set. Results: The predictive accuracy of SII (Harrell's concordance index [C-index]: 0.624), NLR (C-index: 0.626), and LMR (C-index: 0.622) was evaluated. The multivariate Cox model showed that SII was a superior independent predictor than NLR and LMR. SII level (≥600) (hazard ratio [HR]: 1.694, 95% confidence interval [CI]: 1.069-2.684, p = 0.024), carbohydrate antigen (CA) 19-9 level (≥37 U/ml) (HR: 2.407, 95% CI: 1.472-3.933, p < 0.001), and TNM stage (p = 0.026) were selected to construct a nomogram for predicting overall survival (OS). The predictive ability of this model was assessed by C-index (0.755 in the training set, 0.754 in the validation set). Good performance was demonstrated by the calibration plot. A high net benefit was proven by decision curve analysis (DCA). Conclusion: SII is an independent prognostic indicator in GBC patients after surgical resection, and the nomogram based on it is a useful tool for predicting OS.