Prognostic value of pre-operative inflammatory response biomarkers in gastric cancer patients and the construction of a predictive model

Abstract

Background: Inflammation plays an integral role in carcinogenesis and tumor progression. Inflammatory response biomarkers have shown to be promising prognostic factors for improving the predictive accuracy in various cancers. The aim of this study is to investigate the prognostic significance of pre-operative neutrophil to lymphocyte ratio (NLR), derived neutrophil to lymphocyte ratio (dNLR), platelet to lymphocyte ratio (PLR) and lymphocyte to monocyte ratio (LMR) in gastric cancer (GC). Methods: 389 patients who had undergone gastrectomy were enrolled from 2007 to 2009 in this study. NLR, dNLR, PLR and LMR were calculated from peripheral blood cell count taken at pre-operation. Receiver operating curve (ROC) was used to determine the optimal cut-off levels for these biomarkers. A predictive model or nomogram was established to predict prognosis for cancer-specific survival (CSS) and disease-free survival (DFS), and the predictive accuracy of the nomogram was determined by concordance index (c-index). Results: The median follow-up period was 24months ranging from 3months to 60months. The optimal cut-off levels were 2.36 for NLR, 1.85 for dNLR, 132 for PLR and 4.95 for LMR by ROC curves analysis. Elevated NLR, dNLR and PLR were significantly associated with worse overall survival (OS), CSS and DFS, however, elevated LMR showed an adverse effect on worse OS, CSS and DFS. Multivariate analysis revealed that elevated dNLR was an independent factor for worse OS, and NLR was superior to dNLR, PLR and LMR in terms of hazard ratio (HR=1.53, 95% CI=1.11-2.11, P=0.010), which was shown to be independent prognostic indicators for both CSS and DFS. Moreover, the nomogram could more accurately predict CSS (c-index: 0.89) and DFS (c-index: 0.84) in surgical GC patients. Conclusions: Pre-operative NLR and dNLR may serve as potential prognostic biomarkers in patients with GC who underwent surgical resection. The proposed nomograms can be used for the prediction of CSS and DFS in patients with GC who have undergone gastrectomy.