A Prognostic Model Using Inflammation- and Nutrition-Based Scores in Patients With Metastatic Gastric Adenocarcinoma Treated With Chemotherapy. Issue 17 (April 2016) - Hsieh, Meng-Che
Abstract : Abstract: The outcomes of patients with metastatic gastric cancer (mGC) are poor. Recent studies have identified the prognostic impact of inflammatory response and nutritional status on survival for patients with gastric cancer. This study aims to create a prognostic model using inflammatory- and nutrition-based scores to predict survival in patients with mGC treated with chemotherapy. After institutional review board approval, patients who had mGC and were treated with chemotherapy from 2007 to 2012 at Kaohsiung Chang Gung Memorial Hospital were retrospectively reviewed. Significantly predictive factors were identified by multivariate Cox regression analyses. Based on these variables, a prognostic model using inflammatory- and nutrition-based scores was constructed to predict survival. Kaplan-Meier curves were plotted to estimate overall survival. The c-statistic values with 95% confidence interval (CI) were also calculated to access their predicting performances. Our study consisted of 256 patients with a median age of 60 years and a median follow-up visit of 18.5 months. Multivariate analyses showed that neutrophil to lymphocyte ratio (NLR), modified Glasgow prognostic score (mGPS), and Patient-Generated Subjective Global Assessment (PG-SGA) were independently related to survival. After computing these scores, patients were classified into favorable-, intermediate-, and poor-risk groups. The median overall survival were 27.6 versus 13.2 versus 8.2 months in favorable, intermediate, and poor-risk groups, respectively. The 2-year survival rate was 52% versus 16% versus 3% in favorable-, intermediate-, and poor-risk groups, respectively. ( P < 0.001). The c-statistic value of our model at 2 years is 0.8 (95% CI, 0.75–0.86). NLR, mGPS, and PG-SGA were independently related to survival. Our prognostic model using inflammatory- and nutrition-based scores could provide prognostic information to patients and physicians.