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Identification of a clinical web-based nomogram to predict overall survival in elderly retroperitoneal sarcoma patients: A population-based study

The purpose of this study was to develop a web-based nomogram and risk stratification system to predict overall survival (OS) in elderly patients with retroperitoneal sarcoma (RPS). Elderly patients diagnosed with RPS between 2004 and 2015 were identified in the Surveillance, Epidemiology, and End R...

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Autores principales: Zheng, Honghong, Wei, Junqiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9524972/
https://www.ncbi.nlm.nih.gov/pubmed/36181117
http://dx.doi.org/10.1097/MD.0000000000030618
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author Zheng, Honghong
Wei, Junqiang
author_facet Zheng, Honghong
Wei, Junqiang
author_sort Zheng, Honghong
collection PubMed
description The purpose of this study was to develop a web-based nomogram and risk stratification system to predict overall survival (OS) in elderly patients with retroperitoneal sarcoma (RPS). Elderly patients diagnosed with RPS between 2004 and 2015 were identified in the Surveillance, Epidemiology, and End Results (SEER) database. We used univariate and multivariate Cox analysis to identify independent prognostic factors. We plotted the nomogram for predicting the OS of elderly RPS patients at 1, 3, and 5 years by integrating independent prognostic factors. The nomograms were subsequently validated by receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). By calculating the Nomogram score for each patient, we build a risk stratification model to evaluate the survival benefit of elderly RPS patients. A total of 722 elderly RPS patients were included in our study. The nomogram includes 5 clinicopathological variables as independent prognostic factors: age, histological subtype, grade, metastasis status, and surgery. Through the validation, we found that the nomogram has excellent prediction performance. Then web-based nomograms were established. We performed a web-based nomogram and a risk stratification model to assess the prognosis of elderly RPS patients, which are essential for prognostic clustering and decision-making about treatment.
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spelling pubmed-95249722022-10-03 Identification of a clinical web-based nomogram to predict overall survival in elderly retroperitoneal sarcoma patients: A population-based study Zheng, Honghong Wei, Junqiang Medicine (Baltimore) Research Article The purpose of this study was to develop a web-based nomogram and risk stratification system to predict overall survival (OS) in elderly patients with retroperitoneal sarcoma (RPS). Elderly patients diagnosed with RPS between 2004 and 2015 were identified in the Surveillance, Epidemiology, and End Results (SEER) database. We used univariate and multivariate Cox analysis to identify independent prognostic factors. We plotted the nomogram for predicting the OS of elderly RPS patients at 1, 3, and 5 years by integrating independent prognostic factors. The nomograms were subsequently validated by receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). By calculating the Nomogram score for each patient, we build a risk stratification model to evaluate the survival benefit of elderly RPS patients. A total of 722 elderly RPS patients were included in our study. The nomogram includes 5 clinicopathological variables as independent prognostic factors: age, histological subtype, grade, metastasis status, and surgery. Through the validation, we found that the nomogram has excellent prediction performance. Then web-based nomograms were established. We performed a web-based nomogram and a risk stratification model to assess the prognosis of elderly RPS patients, which are essential for prognostic clustering and decision-making about treatment. Lippincott Williams & Wilkins 2022-09-30 /pmc/articles/PMC9524972/ /pubmed/36181117 http://dx.doi.org/10.1097/MD.0000000000030618 Text en Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC) (https://creativecommons.org/licenses/by-nc/4.0/) , where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal.
spellingShingle Research Article
Zheng, Honghong
Wei, Junqiang
Identification of a clinical web-based nomogram to predict overall survival in elderly retroperitoneal sarcoma patients: A population-based study
title Identification of a clinical web-based nomogram to predict overall survival in elderly retroperitoneal sarcoma patients: A population-based study
title_full Identification of a clinical web-based nomogram to predict overall survival in elderly retroperitoneal sarcoma patients: A population-based study
title_fullStr Identification of a clinical web-based nomogram to predict overall survival in elderly retroperitoneal sarcoma patients: A population-based study
title_full_unstemmed Identification of a clinical web-based nomogram to predict overall survival in elderly retroperitoneal sarcoma patients: A population-based study
title_short Identification of a clinical web-based nomogram to predict overall survival in elderly retroperitoneal sarcoma patients: A population-based study
title_sort identification of a clinical web-based nomogram to predict overall survival in elderly retroperitoneal sarcoma patients: a population-based study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9524972/
https://www.ncbi.nlm.nih.gov/pubmed/36181117
http://dx.doi.org/10.1097/MD.0000000000030618
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