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Establishment of a Nomogram-Based Model for Predicting the Prognostic Value of Inflammatory Biomarkers and Preoperative D-Dimer Level in Spinal Ewing's Sarcoma Family Tumors: A Retrospective Study of 83 Patients.

Kehan Xu,Yan Lou,Rui Sun,Yujie Liu,Bo Li,Jialin Li,Quan Huang,W. Wan,Jianru Xiao

Published 2019 in World Neurosurgery

ABSTRACT

BACKGROUND Ewing's sarcoma family tumors (ESFTs) are the second most common malignancy in children and adolescents. The purpose of the present retrospective study was to evaluate the prognostic role of inflammatory biomarkers and preoperative D-dimer levels in patients with spinal ESFTs. METHODS The neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, lymphocyte/monocyte ratio, albumin/globulin ratio, C-reactive protein/albumin ratio (CAR), preoperative D-dimer level, and clinical parameters were evaluated and analyzed. Univariate and multivariate analyses for disease-free survival (DFS) and overall survival (OS) were performed using the log-rank test and Cox regression analysis, respectively. The DFS and OS rates were calculated using the Kaplan-Meier method. Nomograms were established to predict DFS and OS quantitatively. RESULTS The optimal cutoff values for D-dimer, neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, lymphocyte/monocyte ratio, CAR, and albumin/globulin ratio were 0.3, 3.2, 168, 2.2, 1.5, and 1.4, respectively. The patients were stratified into 2 groups according to the cutoff values. Multivariate analysis revealed that age, resection mode, and D-dimer level were favorable prognostic factors for DFS and OS (P < 0.05). Metastasis and CAR <1.5 were significantly associated with OS (P < 0.05). Nomograms with all significant factors were established to predict DFS and OS. CONCLUSIONS Our results have indicated that the preoperative D-dimer level is an effective prognostic factor with discriminatory ability for DFS and OS, superior to other indicators. Also, CAR was favorable prognostic factor for OS. Nomograms of DFS and OS can be recommended as practical models to evaluate the prognosis for patients with spinal ESFTs.

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