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Risk factors for metastasis and poor prognosis of Ewing sarcoma: a population based study
BACKGROUND: This study is to determine the risk factors for metastasis of Ewing sarcoma (ES) patients in SEER database. Then explore clinicopathological factors associated with poor prognosis. Furthermore, develop the nomogram to predict the probability of overall survival and cancer-specific surviv...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7055127/ https://www.ncbi.nlm.nih.gov/pubmed/32131863 http://dx.doi.org/10.1186/s13018-020-01607-8 |
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author | Shi, Jiaqi Yang, Jianing Ma, Xin Wang, Xu |
author_facet | Shi, Jiaqi Yang, Jianing Ma, Xin Wang, Xu |
author_sort | Shi, Jiaqi |
collection | PubMed |
description | BACKGROUND: This study is to determine the risk factors for metastasis of Ewing sarcoma (ES) patients in SEER database. Then explore clinicopathological factors associated with poor prognosis. Furthermore, develop the nomogram to predict the probability of overall survival and cancer-specific survival METHODS: Thus, we collected clinicopathological data of ES patients in SEER database, and then used chi-square test and logistic regression to determine risk factors associated to metastasis. We also did survival analysis including Kaplan-Meier curve and Cox proportional hazard model to explore the risk factors associated to overall survival and cancer-specific survival, and then developed the nomogram to visualize and quantify the probability of survival. RESULTS: After statistics, we find that patients with older ages (11–20 years old: OR = 1.517, 95% confidence interval [CI] 1.033–2.228, p = 0.034; 21–30 years old: OR = 1.659. 95%CI 1.054–2.610, p = 0.029), larger tumor size (> 8 cm: OR = 1.914, 95%CI 1.251–2.928, p = 0.003), and pelvic lesions (OR = 2.492, 95%CI 1.829–3.395, p < 0.001) had a higher risk of metastasis. ROC curves showed higher AUC (0.65) of combined model which incorporate these three factors to predict the presence of metastasis at diagnosis. In survival analysis, patients with older ages (11–20 years: HR = 1.549, 95%CI 1.144–2.099, p = 0.005; 21–30 years: HR = 1.808, 95%CI 1.278–2.556, p = 0.001; 31–49 years: HR = 3.481, 95%CI 2.379–5.094, p < 0.001; ≥ 50 years: HR = 4.307, 95%CI 2.648–7.006, p < 0.001) , larger tumor size (5–8 cm: HR = 1.386, 95%CI 1.005–1.991, p = 0.046; > 8 cm: HR = 1.877, 95%CI 1.376–2.561, p < 0.001), black race (HR = 2.104, 95%CI 1.296–3.416, p = 0.003), and wider extension (regional: HR = 1.373, 95%CI 1.033–1.823, p = 0.029; metastatic: HR = 3.259, 95%CI 2.425–4.379, p < 0.001) were associated with worse prognosis. Chemotherapy was associated with better prognosis (HR = 0.466, 95%CI 0.290–0.685, p < 0.001). The nomogram which developed by training set and aimed to predict OS and CSS showed good consistency with actual observed outcomes internally and externally. CONCLUSION: In conclusion, tumor size and primary site were associated with distant metastasis at diagnosis. Age, tumor size, primary site, tumor extent, and chemotherapy were associated with overall survival and cancer-specific survival. Nomogram could predict the probability of OS and CSS and showed good consistency with actual observed outcomes internally and externally. |
format | Online Article Text |
id | pubmed-7055127 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-70551272020-03-10 Risk factors for metastasis and poor prognosis of Ewing sarcoma: a population based study Shi, Jiaqi Yang, Jianing Ma, Xin Wang, Xu J Orthop Surg Res Research Article BACKGROUND: This study is to determine the risk factors for metastasis of Ewing sarcoma (ES) patients in SEER database. Then explore clinicopathological factors associated with poor prognosis. Furthermore, develop the nomogram to predict the probability of overall survival and cancer-specific survival METHODS: Thus, we collected clinicopathological data of ES patients in SEER database, and then used chi-square test and logistic regression to determine risk factors associated to metastasis. We also did survival analysis including Kaplan-Meier curve and Cox proportional hazard model to explore the risk factors associated to overall survival and cancer-specific survival, and then developed the nomogram to visualize and quantify the probability of survival. RESULTS: After statistics, we find that patients with older ages (11–20 years old: OR = 1.517, 95% confidence interval [CI] 1.033–2.228, p = 0.034; 21–30 years old: OR = 1.659. 95%CI 1.054–2.610, p = 0.029), larger tumor size (> 8 cm: OR = 1.914, 95%CI 1.251–2.928, p = 0.003), and pelvic lesions (OR = 2.492, 95%CI 1.829–3.395, p < 0.001) had a higher risk of metastasis. ROC curves showed higher AUC (0.65) of combined model which incorporate these three factors to predict the presence of metastasis at diagnosis. In survival analysis, patients with older ages (11–20 years: HR = 1.549, 95%CI 1.144–2.099, p = 0.005; 21–30 years: HR = 1.808, 95%CI 1.278–2.556, p = 0.001; 31–49 years: HR = 3.481, 95%CI 2.379–5.094, p < 0.001; ≥ 50 years: HR = 4.307, 95%CI 2.648–7.006, p < 0.001) , larger tumor size (5–8 cm: HR = 1.386, 95%CI 1.005–1.991, p = 0.046; > 8 cm: HR = 1.877, 95%CI 1.376–2.561, p < 0.001), black race (HR = 2.104, 95%CI 1.296–3.416, p = 0.003), and wider extension (regional: HR = 1.373, 95%CI 1.033–1.823, p = 0.029; metastatic: HR = 3.259, 95%CI 2.425–4.379, p < 0.001) were associated with worse prognosis. Chemotherapy was associated with better prognosis (HR = 0.466, 95%CI 0.290–0.685, p < 0.001). The nomogram which developed by training set and aimed to predict OS and CSS showed good consistency with actual observed outcomes internally and externally. CONCLUSION: In conclusion, tumor size and primary site were associated with distant metastasis at diagnosis. Age, tumor size, primary site, tumor extent, and chemotherapy were associated with overall survival and cancer-specific survival. Nomogram could predict the probability of OS and CSS and showed good consistency with actual observed outcomes internally and externally. BioMed Central 2020-03-04 /pmc/articles/PMC7055127/ /pubmed/32131863 http://dx.doi.org/10.1186/s13018-020-01607-8 Text en © The Author(s) 2020 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Shi, Jiaqi Yang, Jianing Ma, Xin Wang, Xu Risk factors for metastasis and poor prognosis of Ewing sarcoma: a population based study |
title | Risk factors for metastasis and poor prognosis of Ewing sarcoma: a population based study |
title_full | Risk factors for metastasis and poor prognosis of Ewing sarcoma: a population based study |
title_fullStr | Risk factors for metastasis and poor prognosis of Ewing sarcoma: a population based study |
title_full_unstemmed | Risk factors for metastasis and poor prognosis of Ewing sarcoma: a population based study |
title_short | Risk factors for metastasis and poor prognosis of Ewing sarcoma: a population based study |
title_sort | risk factors for metastasis and poor prognosis of ewing sarcoma: a population based study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7055127/ https://www.ncbi.nlm.nih.gov/pubmed/32131863 http://dx.doi.org/10.1186/s13018-020-01607-8 |
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