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Prognostic Factors and a Nomogram Predicting Overall Survival in Patients with Limb Chondrosarcomas: A Population-Based Study
INTRODUCTION: We aimed to develop and validate a nomogram for predicting the overall survival of patients with limb chondrosarcomas. METHODS: The Surveillance, Epidemiology, and End Results (SEER) program database was used to identify patients diagnosed with chondrosarcomas, from which data was extr...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8147544/ https://www.ncbi.nlm.nih.gov/pubmed/34055971 http://dx.doi.org/10.1155/2021/4510423 |
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author | Wu, Xinjie Wang, Yanlei Sun, Wei Tan, Mingsheng |
author_facet | Wu, Xinjie Wang, Yanlei Sun, Wei Tan, Mingsheng |
author_sort | Wu, Xinjie |
collection | PubMed |
description | INTRODUCTION: We aimed to develop and validate a nomogram for predicting the overall survival of patients with limb chondrosarcomas. METHODS: The Surveillance, Epidemiology, and End Results (SEER) program database was used to identify patients diagnosed with chondrosarcomas, from which data was extracted from 18 registries in the United States between 1973 and 2016. A total of 813 patients were selected from the database. Univariate and multivariate analyses were performed using Cox proportional hazards regression models on the training group to identify independent prognostic factors and construct a nomogram to predict the 3- and 5-year survival probability of patients with limb chondrosarcomas. The predictive values were compared using concordance indexes (C-indexes) and calibration plots. RESULTS: All 813 patients were randomly divided into a training group (n = 572) and a validation group (n = 241). After univariate and multivariate Cox regression, a nomogram was constructed based on a new model containing the predictive variables of age, site, grade, tumor size, histology, stage, and use of surgery, radiotherapy, or chemotherapy. The prediction model provided excellent C-indexes (0.86 and 0.77 in the training and validation groups, respectively). The good discrimination and calibration of the nomograms were demonstrated for both the training and validation groups. CONCLUSIONS: The nomograms precisely and individually predict the overall survival of patients with limb chondrosarcomas and could assist personalized prognostic evaluation and individualized clinical decision-making. |
format | Online Article Text |
id | pubmed-8147544 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-81475442021-05-27 Prognostic Factors and a Nomogram Predicting Overall Survival in Patients with Limb Chondrosarcomas: A Population-Based Study Wu, Xinjie Wang, Yanlei Sun, Wei Tan, Mingsheng Biomed Res Int Research Article INTRODUCTION: We aimed to develop and validate a nomogram for predicting the overall survival of patients with limb chondrosarcomas. METHODS: The Surveillance, Epidemiology, and End Results (SEER) program database was used to identify patients diagnosed with chondrosarcomas, from which data was extracted from 18 registries in the United States between 1973 and 2016. A total of 813 patients were selected from the database. Univariate and multivariate analyses were performed using Cox proportional hazards regression models on the training group to identify independent prognostic factors and construct a nomogram to predict the 3- and 5-year survival probability of patients with limb chondrosarcomas. The predictive values were compared using concordance indexes (C-indexes) and calibration plots. RESULTS: All 813 patients were randomly divided into a training group (n = 572) and a validation group (n = 241). After univariate and multivariate Cox regression, a nomogram was constructed based on a new model containing the predictive variables of age, site, grade, tumor size, histology, stage, and use of surgery, radiotherapy, or chemotherapy. The prediction model provided excellent C-indexes (0.86 and 0.77 in the training and validation groups, respectively). The good discrimination and calibration of the nomograms were demonstrated for both the training and validation groups. CONCLUSIONS: The nomograms precisely and individually predict the overall survival of patients with limb chondrosarcomas and could assist personalized prognostic evaluation and individualized clinical decision-making. Hindawi 2021-05-15 /pmc/articles/PMC8147544/ /pubmed/34055971 http://dx.doi.org/10.1155/2021/4510423 Text en Copyright © 2021 Xinjie Wu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Wu, Xinjie Wang, Yanlei Sun, Wei Tan, Mingsheng Prognostic Factors and a Nomogram Predicting Overall Survival in Patients with Limb Chondrosarcomas: A Population-Based Study |
title | Prognostic Factors and a Nomogram Predicting Overall Survival in Patients with Limb Chondrosarcomas: A Population-Based Study |
title_full | Prognostic Factors and a Nomogram Predicting Overall Survival in Patients with Limb Chondrosarcomas: A Population-Based Study |
title_fullStr | Prognostic Factors and a Nomogram Predicting Overall Survival in Patients with Limb Chondrosarcomas: A Population-Based Study |
title_full_unstemmed | Prognostic Factors and a Nomogram Predicting Overall Survival in Patients with Limb Chondrosarcomas: A Population-Based Study |
title_short | Prognostic Factors and a Nomogram Predicting Overall Survival in Patients with Limb Chondrosarcomas: A Population-Based Study |
title_sort | prognostic factors and a nomogram predicting overall survival in patients with limb chondrosarcomas: a population-based study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8147544/ https://www.ncbi.nlm.nih.gov/pubmed/34055971 http://dx.doi.org/10.1155/2021/4510423 |
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