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A tool for predicting overall survival in patients with Ewing sarcoma: a multicenter retrospective study

OBJECTIVE: The aim of this study was to establish and validate a clinical prediction model for assessing the risk of metastasis and patient survival in Ewing's sarcoma (ES). METHODS: Patients diagnosed with ES from the Surveillance, Epidemiology and End Results (SEER) database for the period 20...

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Autores principales: Li, Wenle, Dong, Shengtao, Lin, Yuewei, Wu, Huitao, Chen, Mengfei, Qin, Chuan, Li, Kelin, Zhang, JunYan, Tang, Zhi-Ri, Wang, Haosheng, Huo, Kang, Xie, Xiangtao, Hu, Zhaohui, Kuang, Sirui, Yin, Chengliang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9400324/
https://www.ncbi.nlm.nih.gov/pubmed/35999524
http://dx.doi.org/10.1186/s12885-022-09796-7
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author Li, Wenle
Dong, Shengtao
Lin, Yuewei
Wu, Huitao
Chen, Mengfei
Qin, Chuan
Li, Kelin
Zhang, JunYan
Tang, Zhi-Ri
Wang, Haosheng
Huo, Kang
Xie, Xiangtao
Hu, Zhaohui
Kuang, Sirui
Yin, Chengliang
author_facet Li, Wenle
Dong, Shengtao
Lin, Yuewei
Wu, Huitao
Chen, Mengfei
Qin, Chuan
Li, Kelin
Zhang, JunYan
Tang, Zhi-Ri
Wang, Haosheng
Huo, Kang
Xie, Xiangtao
Hu, Zhaohui
Kuang, Sirui
Yin, Chengliang
author_sort Li, Wenle
collection PubMed
description OBJECTIVE: The aim of this study was to establish and validate a clinical prediction model for assessing the risk of metastasis and patient survival in Ewing's sarcoma (ES). METHODS: Patients diagnosed with ES from the Surveillance, Epidemiology and End Results (SEER) database for the period 2010-2016 were extracted, and the data after exclusion of vacant terms was used as the training set (n=767). Prediction models predicting patients' overall survival (OS) at 1 and 3 years were created by cox regression analysis and visualized using Nomogram and web calculator. Multicenter data from four medical institutions were used as the validation set (n=51), and the model consistency was verified using calibration plots, and receiver operating characteristic (ROC) verified the predictive ability of the model. Finally, a clinical decision curve was used to demonstrate the clinical utility of the model. RESULTS: The results of multivariate cox regression showed that age, , bone metastasis, tumor size, and chemotherapy were independent prognostic factors of ES patients. Internal and external validation results: calibration plots showed that the model had a good agreement for patient survival at 1 and 3 years; ROC showed that it possessed a good predictive ability and clinical decision curve proved that it possessed good clinical utility. CONCLUSIONS: The tool built in this paper to predict 1- and 3-year survival in ES patients (https://drwenleli0910.shinyapps.io/EwingApp/) has a good identification and predictive power. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-09796-7.
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spelling pubmed-94003242022-08-25 A tool for predicting overall survival in patients with Ewing sarcoma: a multicenter retrospective study Li, Wenle Dong, Shengtao Lin, Yuewei Wu, Huitao Chen, Mengfei Qin, Chuan Li, Kelin Zhang, JunYan Tang, Zhi-Ri Wang, Haosheng Huo, Kang Xie, Xiangtao Hu, Zhaohui Kuang, Sirui Yin, Chengliang BMC Cancer Research OBJECTIVE: The aim of this study was to establish and validate a clinical prediction model for assessing the risk of metastasis and patient survival in Ewing's sarcoma (ES). METHODS: Patients diagnosed with ES from the Surveillance, Epidemiology and End Results (SEER) database for the period 2010-2016 were extracted, and the data after exclusion of vacant terms was used as the training set (n=767). Prediction models predicting patients' overall survival (OS) at 1 and 3 years were created by cox regression analysis and visualized using Nomogram and web calculator. Multicenter data from four medical institutions were used as the validation set (n=51), and the model consistency was verified using calibration plots, and receiver operating characteristic (ROC) verified the predictive ability of the model. Finally, a clinical decision curve was used to demonstrate the clinical utility of the model. RESULTS: The results of multivariate cox regression showed that age, , bone metastasis, tumor size, and chemotherapy were independent prognostic factors of ES patients. Internal and external validation results: calibration plots showed that the model had a good agreement for patient survival at 1 and 3 years; ROC showed that it possessed a good predictive ability and clinical decision curve proved that it possessed good clinical utility. CONCLUSIONS: The tool built in this paper to predict 1- and 3-year survival in ES patients (https://drwenleli0910.shinyapps.io/EwingApp/) has a good identification and predictive power. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-09796-7. BioMed Central 2022-08-23 /pmc/articles/PMC9400324/ /pubmed/35999524 http://dx.doi.org/10.1186/s12885-022-09796-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Li, Wenle
Dong, Shengtao
Lin, Yuewei
Wu, Huitao
Chen, Mengfei
Qin, Chuan
Li, Kelin
Zhang, JunYan
Tang, Zhi-Ri
Wang, Haosheng
Huo, Kang
Xie, Xiangtao
Hu, Zhaohui
Kuang, Sirui
Yin, Chengliang
A tool for predicting overall survival in patients with Ewing sarcoma: a multicenter retrospective study
title A tool for predicting overall survival in patients with Ewing sarcoma: a multicenter retrospective study
title_full A tool for predicting overall survival in patients with Ewing sarcoma: a multicenter retrospective study
title_fullStr A tool for predicting overall survival in patients with Ewing sarcoma: a multicenter retrospective study
title_full_unstemmed A tool for predicting overall survival in patients with Ewing sarcoma: a multicenter retrospective study
title_short A tool for predicting overall survival in patients with Ewing sarcoma: a multicenter retrospective study
title_sort tool for predicting overall survival in patients with ewing sarcoma: a multicenter retrospective study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9400324/
https://www.ncbi.nlm.nih.gov/pubmed/35999524
http://dx.doi.org/10.1186/s12885-022-09796-7
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