23 November 2017 : Clinical Research
Prognostic Significance of Preoperative Neutrophil-to-Lymphocyte Ratio in Surgically Resectable Pancreatic Neuroendocrine Tumors
Bo Zhou1BCDEFG, Canyang Zhan2BCG, Jingjing Wu1EF, Jianhua Liu1EF, Jie Zhou3BCD, Shusen Zheng1AE*DOI: 10.12659/MSM.907182
Med Sci Monit 2017; 23:5574-5588
Abstract
BACKGROUND: The aim of this study was to evaluate the predictive and prognostic value of the preoperative neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in pancreatic neuroendocrine tumor (PNET) patients undergoing potentially curative resection.
MATERIAL AND METHODS: A retrospective review of 172 patients with PNETs was conducted. Kaplan-Meier curves and multivariate Cox proportional models were used to calculate overall survival (OS) and disease-free survival (DFS). The predictive performance of the NLR was compared with other inflammation-based scores and conventional stratification systems using receiver operating characteristic (ROC) curve analysis.
RESULTS: Elevated NLR and PLR were both associated with advanced AJCC stage and high grade. In the univariate analysis, elevated NLR and PLR were both significantly associated with decreased OS and DFS. In the multivariate analysis, the preoperative NLR, but not the PLR, was an independent risk factor for OS (HR=4.471, 95% CI 1.531–13.054, p=0.006) and DFS (HR=2.531, 95% CI 1.202–5.329, p=0.015). The discriminatory capability of the NLR was superior to that of other inflammation-based scores in OS prediction. Furthermore, the predictive range was expanded by incorporating the NLR into the conventional stratification systems, including the AJCC stage and WHO classification systems.
CONCLUSIONS: As an independent prognostic factor, an elevated preoperative NLR is superior to the PLR with respect to predicting clinical outcomes in PNET patients undergoing potentially curative resection. The incorporation of the NLR into the existing conventional stratification systems improved the predictive accuracy.
Keywords: Multivariate Analysis, Neutrophils
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