Cargando…

A Web-Based Prediction Model for Overall Survival of Elderly Patients With Malignant Bone Tumors: A Population-Based Study

Background: Malignant bone tumors (MBT) are one of the causes of death in elderly patients. The purpose of our study is to establish a nomogram to predict the overall survival (OS) of elderly patients with MBT. Methods: The clinicopathological data of all elderly patients with MBT from 2004 to 2018...

Descripción completa

Detalles Bibliográficos
Autores principales: Tang, Jie, Wang, JinKui, Pan, Xiudan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8787310/
https://www.ncbi.nlm.nih.gov/pubmed/35087789
http://dx.doi.org/10.3389/fpubh.2021.812395
_version_ 1784639334174949376
author Tang, Jie
Wang, JinKui
Pan, Xiudan
author_facet Tang, Jie
Wang, JinKui
Pan, Xiudan
author_sort Tang, Jie
collection PubMed
description Background: Malignant bone tumors (MBT) are one of the causes of death in elderly patients. The purpose of our study is to establish a nomogram to predict the overall survival (OS) of elderly patients with MBT. Methods: The clinicopathological data of all elderly patients with MBT from 2004 to 2018 were downloaded from the SEER database. They were randomly assigned to the training set (70%) and validation set (30%). Univariate and multivariate Cox regression analysis was used to identify independent risk factors for elderly patients with MBT. A nomogram was built based on these risk factors to predict the 1-, 3-, and 5-year OS of elderly patients with MBT. Then, used the consistency index (C-index), calibration curve, and the area under the receiver operating curve (AUC) to evaluate the accuracy and discrimination of the prediction model was. Decision curve analysis (DCA) was used to assess the clinical potential application value of the nomogram. Based on the scores on the nomogram, patients were divided into high- and low-risk groups. The Kaplan-Meier (K-M) curve was used to test the difference in survival between the two patients. Results: A total of 1,641 patients were included, and they were randomly assigned to the training set (N = 1,156) and the validation set (N = 485). The univariate and multivariate analysis of the training set suggested that age, sex, race, primary site, histologic type, grade, stage, M stage, surgery, and tumor size were independent risk factors for elderly patients with MBT. The C-index of the training set and the validation set were 0.779 [0.759–0.799] and 0.801 [0.772–0.830], respectively. The AUC of the training and validation sets also showed similar results. The calibration curves of the training and validation sets indicated that the observed and predicted values were highly consistent. DCA suggested that the nomogram had potential clinical value compared with traditional TNM staging. Conclusion: We had established a new nomogram to predict the 1-, 3-, 5-year OS of elderly patients with MBT. This predictive model can help doctors and patients develop treatment plans and follow-up strategies.
format Online
Article
Text
id pubmed-8787310
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-87873102022-01-26 A Web-Based Prediction Model for Overall Survival of Elderly Patients With Malignant Bone Tumors: A Population-Based Study Tang, Jie Wang, JinKui Pan, Xiudan Front Public Health Public Health Background: Malignant bone tumors (MBT) are one of the causes of death in elderly patients. The purpose of our study is to establish a nomogram to predict the overall survival (OS) of elderly patients with MBT. Methods: The clinicopathological data of all elderly patients with MBT from 2004 to 2018 were downloaded from the SEER database. They were randomly assigned to the training set (70%) and validation set (30%). Univariate and multivariate Cox regression analysis was used to identify independent risk factors for elderly patients with MBT. A nomogram was built based on these risk factors to predict the 1-, 3-, and 5-year OS of elderly patients with MBT. Then, used the consistency index (C-index), calibration curve, and the area under the receiver operating curve (AUC) to evaluate the accuracy and discrimination of the prediction model was. Decision curve analysis (DCA) was used to assess the clinical potential application value of the nomogram. Based on the scores on the nomogram, patients were divided into high- and low-risk groups. The Kaplan-Meier (K-M) curve was used to test the difference in survival between the two patients. Results: A total of 1,641 patients were included, and they were randomly assigned to the training set (N = 1,156) and the validation set (N = 485). The univariate and multivariate analysis of the training set suggested that age, sex, race, primary site, histologic type, grade, stage, M stage, surgery, and tumor size were independent risk factors for elderly patients with MBT. The C-index of the training set and the validation set were 0.779 [0.759–0.799] and 0.801 [0.772–0.830], respectively. The AUC of the training and validation sets also showed similar results. The calibration curves of the training and validation sets indicated that the observed and predicted values were highly consistent. DCA suggested that the nomogram had potential clinical value compared with traditional TNM staging. Conclusion: We had established a new nomogram to predict the 1-, 3-, 5-year OS of elderly patients with MBT. This predictive model can help doctors and patients develop treatment plans and follow-up strategies. Frontiers Media S.A. 2022-01-11 /pmc/articles/PMC8787310/ /pubmed/35087789 http://dx.doi.org/10.3389/fpubh.2021.812395 Text en Copyright © 2022 Tang, Wang and Pan. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Tang, Jie
Wang, JinKui
Pan, Xiudan
A Web-Based Prediction Model for Overall Survival of Elderly Patients With Malignant Bone Tumors: A Population-Based Study
title A Web-Based Prediction Model for Overall Survival of Elderly Patients With Malignant Bone Tumors: A Population-Based Study
title_full A Web-Based Prediction Model for Overall Survival of Elderly Patients With Malignant Bone Tumors: A Population-Based Study
title_fullStr A Web-Based Prediction Model for Overall Survival of Elderly Patients With Malignant Bone Tumors: A Population-Based Study
title_full_unstemmed A Web-Based Prediction Model for Overall Survival of Elderly Patients With Malignant Bone Tumors: A Population-Based Study
title_short A Web-Based Prediction Model for Overall Survival of Elderly Patients With Malignant Bone Tumors: A Population-Based Study
title_sort web-based prediction model for overall survival of elderly patients with malignant bone tumors: a population-based study
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8787310/
https://www.ncbi.nlm.nih.gov/pubmed/35087789
http://dx.doi.org/10.3389/fpubh.2021.812395
work_keys_str_mv AT tangjie awebbasedpredictionmodelforoverallsurvivalofelderlypatientswithmalignantbonetumorsapopulationbasedstudy
AT wangjinkui awebbasedpredictionmodelforoverallsurvivalofelderlypatientswithmalignantbonetumorsapopulationbasedstudy
AT panxiudan awebbasedpredictionmodelforoverallsurvivalofelderlypatientswithmalignantbonetumorsapopulationbasedstudy
AT tangjie webbasedpredictionmodelforoverallsurvivalofelderlypatientswithmalignantbonetumorsapopulationbasedstudy
AT wangjinkui webbasedpredictionmodelforoverallsurvivalofelderlypatientswithmalignantbonetumorsapopulationbasedstudy
AT panxiudan webbasedpredictionmodelforoverallsurvivalofelderlypatientswithmalignantbonetumorsapopulationbasedstudy