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Construction and validation of nomograms for non-metastatic Ewing sarcoma: A prognostic factor analysis based on the SEER database

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...

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Autores principales: Huang, Runzhi, Han, Dong, Shi, Chengcheng, Yan, Penghui, Hu, Peng, Zhu, Xiaolong, Yin, Huabin, Meng, Tong, Huang, Zongqiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8456482/
https://www.ncbi.nlm.nih.gov/pubmed/34594418
http://dx.doi.org/10.3892/ol.2021.13038
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author Huang, Runzhi
Han, Dong
Shi, Chengcheng
Yan, Penghui
Hu, Peng
Zhu, Xiaolong
Yin, Huabin
Meng, Tong
Huang, Zongqiang
author_facet Huang, Runzhi
Han, Dong
Shi, Chengcheng
Yan, Penghui
Hu, Peng
Zhu, Xiaolong
Yin, Huabin
Meng, Tong
Huang, Zongqiang
author_sort Huang, Runzhi
collection PubMed
description 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.
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spelling pubmed-84564822021-09-29 Construction and validation of nomograms for non-metastatic Ewing sarcoma: A prognostic factor analysis based on the SEER database Huang, Runzhi Han, Dong Shi, Chengcheng Yan, Penghui Hu, Peng Zhu, Xiaolong Yin, Huabin Meng, Tong Huang, Zongqiang Oncol Lett Articles 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. D.A. Spandidos 2021-11 2021-09-13 /pmc/articles/PMC8456482/ /pubmed/34594418 http://dx.doi.org/10.3892/ol.2021.13038 Text en Copyright: © Huang et al. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Huang, Runzhi
Han, Dong
Shi, Chengcheng
Yan, Penghui
Hu, Peng
Zhu, Xiaolong
Yin, Huabin
Meng, Tong
Huang, Zongqiang
Construction and validation of nomograms for non-metastatic Ewing sarcoma: A prognostic factor analysis based on the SEER database
title Construction and validation of nomograms for non-metastatic Ewing sarcoma: A prognostic factor analysis based on the SEER database
title_full Construction and validation of nomograms for non-metastatic Ewing sarcoma: A prognostic factor analysis based on the SEER database
title_fullStr Construction and validation of nomograms for non-metastatic Ewing sarcoma: A prognostic factor analysis based on the SEER database
title_full_unstemmed Construction and validation of nomograms for non-metastatic Ewing sarcoma: A prognostic factor analysis based on the SEER database
title_short Construction and validation of nomograms for non-metastatic Ewing sarcoma: A prognostic factor analysis based on the SEER database
title_sort construction and validation of nomograms for non-metastatic ewing sarcoma: a prognostic factor analysis based on the seer database
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8456482/
https://www.ncbi.nlm.nih.gov/pubmed/34594418
http://dx.doi.org/10.3892/ol.2021.13038
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