A nomogram to predict prognostic values of various inflammatory biomarkers in patients with esophageal squamous cell carcinoma

American Journal of Cancer Research

Jin-Shi Liu¹ 

关键词: Esophageal cancer;    squamous cell carcinoma;    prognostic factor;    cancer-specific survival;    nomogram;   

DOI  :  

学科分类：肿瘤学

来源: e-Century Publishing Corporation

【 摘 要 】

Background: Inflammation plays an important role in cancer progression and prognosis. However, the prognostic values of inflammatory biomarkers in esophageal cancer (EC) were not established. In the present study, therefore, we initially used a nomogram to predict prognostic values of various inflammatory biomarkers in patients with esophageal squamous cell carcinoma (ESCC). Methods: A total of 326 ESCC patients were included in this retrospective study. Glasgow prognostic score (GPS), neutrophil lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR) and lymphocyte monocyte ratio (LMR) were analyzed in the current study. Kaplan-Meier method was used to calculate the cancer-specific survival (CSS). Cox regression analysis was also performed to evaluate the prognostic factors. A nomogram was established to predict the prognosis for CSS. Results: Patients were divided into 3 groups according to GPS (GPS 0, 1 and 2) and 2 groups according to NLR (≤3.45 and >3.45), PLR (≤166.5 and >166.5) and LMR (≤2.30 and >2.30). The 5-year CSS in patients with GPS 0, 1 and 2 were 49.2%, 26.8% and 11.9%, respectively (P<0.001). In addition, patients with NLR (>3.45), PLR (>166.5) and LMR (≤2.30) were significantly associated with decreased CSS, respectively (P<0.001). Multivariate analysis revealed that GPS (P<0.001), PLR (P=0.002) and LMR (P=0.002) were independent prognostic factors in patients with ESCC. In addition, a nomogram was established according to all significantly independent factors for CSS. The Harrell’s c-index for CSS prediction was 0.72. Conclusion: GPS, PLR and LMR were potential prognostic biomarkers in patients with ESCC. The nomogram based on CSS could be used as an accurately prognostic prediction for patients with ESCC.

【 授权许可】

CC BY-NC