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  • Title: A nomogram based on preoperative inflammatory markers predicting the overall survival of pancreatic ductal adenocarcinoma.
    Author: Xu J, Shi KQ, Chen BC, Huang ZP, Lu FY, Zhou MT.
    Journal: J Gastroenterol Hepatol; 2017 Jul; 32(7):1394-1402. PubMed ID: 27973703.
    Abstract:
    BACKGROUND AND AIMS: Developing a preoperative prediction model for estimating the risk of pancreatic ductal adenocarcinoma (PDAC) patients before pancreaticoduodenectomy is a difficult task. The purpose of current study was to develop a prognostic nomogram based on inflammatory markers for PDAC patients. METHODS: Cox regression analysis was performed to calculate the overall survival (OS) and assess the prognostic factors based on 265 PDAC patients undergone surgery. The nomogram was built to estimate the probability of 1-year, 3-year, and 5-year OS. The predictive accuracy of nomogram was determined by concordance index, calibration curve, and time dependent receiver operating characteristics. RESULTS: In multivariable Cox analysis, vascular invasion, Tumor Grade, TNM stage, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and albumin/globulin ratio were significantly associated with OS, which were all assembled into nomogram. The calibration curves for probability of survival showed optimal agreement between nomogram prediction and actual observation. The concordance index for 1-year, 3-year and 5-year OS prediction were 0.860 (95% confidence intervals (CI): 0.837-0.885), 0.837 (95%CI: 0.819-0.856), and 0.809 (95%CI: 0.787-0.829), respectively. The area under time dependent receiver operating characteristics curve of 1-year, 3-year, and 5-year OS prediction were 0.938 (95%CI: 0.886-0.989), 0.844 (95%CI: 0.782-0.906), and 0.884 (95%CI: 0.792-0.976), suggesting high discriminative ability of nomogram. It allowed significant distinction survival outcomes by grouping the patients evenly into three subgroups after sorting by total points. CONCLUSIONS: Based on clinicopathology characteristics and inflammatory markers, we developed a nomogram providing an individualized risk estimate for PDAC patients.
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