Abstract
Ewing sarcoma is the second most common osseous disease in children and adolescents. It presents with a poor prognosis due to the high degree of malignancy and distant metastasis. In order to predict the disease prognosis and investigate a suitable therapeutic strategy for Ewing sarcoma, the present study aimed to describe the clinical characteristics, and to construct and validate nomograms for patients with non-metastatic Ewing sarcoma. A total of 627 cases of non-metastatic Ewing sarcoma were retrospectively collected from the Surveillance, Epidemiology, and End Results database between 2005 and 2014. Survival analysis and a machine learning model were used to identify independent prognostic variables and establish nomograms to estimate overall survival (OS) and cause-specific survival (CSS). The nomograms were bootstrap internally validated and externally validated using non-metastatic Ewing sarcoma cases from the First Affiliated Hospital of Zhengzhou University. The accuracy was also assessed by comparing with current American Joint Committee on Cancer (AJCC) staging systems. The total series consisted of 627 patients with non-metastatic Ewing sarcoma with a mean age of 20.14 years. Age, tumor extension, sex, International Classification of Diseases for Oncology, 3rd Edition histology, surgery and chemotherapy were identified as independent risk factors for OS and CSS. The aforementioned outcomes were incorporated to construct the nomograms, and the concordance indices (C-indices) for internal validation of OS and CSS prediction were 0.791 and 0.813, which were higher than those for AJCC sixth edition (OS, 0.531; CSS, 0.534) and seventh edition (OS, 0.547; CSS, 0.561), while the C-indices for external validation of OS and CSS prediction were 0.834 and 0.825, respectively. In conclusion, age, sex, tumor extension and surgery were independent prognostic factors for both OS and CSS. In addition, with regard to OS, the Ewing sarcoma subtype was a poor factor and chemotherapy was a favorable one. Nomograms based on reduced Cox models attained a satisfactory accuracy in predicting the survival of patients with non-metastatic Ewing sarcoma and could assist clinicians in evaluating survival more accurately.