Cargando…
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...
Autores principales: | , , , , , , , , , , , , , , |
---|---|
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 |
_version_ | 1784772717505937408 |
---|---|
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. |
format | Online Article Text |
id | pubmed-9400324 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT liwenle atoolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT dongshengtao atoolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT linyuewei atoolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT wuhuitao atoolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT chenmengfei atoolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT qinchuan atoolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT likelin atoolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT zhangjunyan atoolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT tangzhiri atoolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT wanghaosheng atoolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT huokang atoolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT xiexiangtao atoolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT huzhaohui atoolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT kuangsirui atoolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT yinchengliang atoolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT liwenle toolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT dongshengtao toolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT linyuewei toolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT wuhuitao toolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT chenmengfei toolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT qinchuan toolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT likelin toolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT zhangjunyan toolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT tangzhiri toolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT wanghaosheng toolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT huokang toolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT xiexiangtao toolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT huzhaohui toolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT kuangsirui toolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy AT yinchengliang toolforpredictingoverallsurvivalinpatientswithewingsarcomaamulticenterretrospectivestudy |