Abstract
OBJECTIVE: The aim of this study was to investigate the prognostic value of preoperative sarcopenia and systemic inflammation for patients with resectable gastric cancer (GC) and develop a novel and powerful prognostic score based on these factors. MATERIALS AND METHODS: Patients with GC who underwent radical gastrectomy between December 2009 and December 2013 were included. A multivariate Cox regression analysis was performed to identify the prognostic factors. A novel prognostic score (SLMR) was developed based on preoperative sarcopenia and the lymphocyte-monocyte ratio (LMR), and its prognostic value was evaluated. RESULTS: In total, 1,167 patients with resectable GC were included in the study. On multivariate analysis, preoperative sarcopenia and the LMR were shown to be independent prognostic factors (both p < .001). A low LMR was an independent predictor from sarcopenia (p < .001). Based on preoperative sarcopenia and the LMR, we established the SLMR. An elevated SLMR was associated with older age, higher ASA scores, larger tumor size, advanced stages, and vascular invasion (all p < .05). Multivariate analysis revealed that the SLMR was a significant independent predictor (p < .001). We incorporated the SLMR into a prognostic model that included tumor size and TNM stage and generated a nomogram, which accurately predicted 3- and 5-year survival for GC patients. CONCLUSION: Preoperative systemic inflammation is significantly associated with sarcopenia. The LMR combined with sarcopenia could enhance prognostication for patients with GC who underwent radical gastrectomy. IMPLICATIONS FOR PRACTICE: Increasing evidence shows that sarcopenia and systemic inflammation are closely associated with the prognosis of malignant tumors, and it is essential for clinicians to understand the relationship and combined prognostic effects of these factors for gastric cancer (GC). Based on a large data set, this study found that preoperative systemic inflammation was significantly associated with sarcopenia in GC, and combining these two predictors could effectively predict the prognosis and complement the prognostic value of the TNM staging system. These findings may lead to the development of new therapeutic avenues to improve cancer outcomes.