Clinical Significance of Glucose to Lymphocyte Ratio (GLR) as a Prognostic Marker for Patients With Pancreatic Cancer
Ailing Zhong, Chien‐shan Cheng, Jinyan Kai, Renquan Lu, Lin Guo
Abstract
Glucose metabolism and systemic inflammation have been associated with cancer aggressiveness and patient prognosis in various malignancies. In the present study, we aimed to evaluated the prognostic significance of pretreatment GLR(glucose to lymphocyte ratio) and systemic immune inflammation in patients with pancreatic cancer. We studied 360 patients with pathologically diagnosed pancreatic adenocarcinoma that was clinically unresectable. Baseline clinicopathological characteristics and laboratory investigations including fasting blood glucose, platelet count, lymphocyte count, neutrophil count, carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA199) and follow-up data were collected for further analysis. The patients were randomly divided into a training cohort (n=238) and a validation cohort (n=122). Univariate and multivariate Cox proportional hazard regression analyses were performed to identify the prognostic value of GLR, systemic immune-inflammation markers and tumor biomarkers. A nomogram model was developed based on the identified prognostic factors, and we used the C-index to evaluate the accuracy of the Cox regression model prediction. Multivariate analysis revealed that GLR [hazard ratio (HR): 2.597; 95% confidence interval (CI): 1.728-3.904)] and CA199 (HR: 2.484; 95% CI: 1.295-4.765) are independent predictors of poor overall survival in the training cohort and were incorporated into the nomogram for OS as independent factors. Moreover, the C-index analyses demonstrated that the C-indexes in the training cohort and the validation cohort were 0.674 and 0.671, respectively. The nomogram model predicts overall survival relatively accurately. We found that the baseline GLR is an independent prognostic factor for patients with pancreatic cancer, and the proposed nomogram can be used as an effective tool for predicting the outcomes of prognosis of patients with pancreatic cancer.