Cargando…

Development and Validation of a Prognostic Model for Overall Survival in Patients with Primary Pelvis and Spine Osteosarcoma: A Population-Based Study and External Validation

Background: Primary pelvis and spine osteosarcoma (PSOS) is a specific type of osteosarcoma that is difficult to treat and has a poor prognosis. In recent years, the research on osteosarcoma has been increasing, but there have been few studies on PSOS; in particular, there have been a lack of analys...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Da, Liu, Fanrong, Li, Binbin, Xu, Jinhui, Gong, Haiyi, Yang, Minglei, Wan, Wei, Jiao, Jian, Liu, Yujie, Xiao, Jianru
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10095419/
https://www.ncbi.nlm.nih.gov/pubmed/37048606
http://dx.doi.org/10.3390/jcm12072521
_version_ 1785024079023046656
author Wang, Da
Liu, Fanrong
Li, Binbin
Xu, Jinhui
Gong, Haiyi
Yang, Minglei
Wan, Wei
Jiao, Jian
Liu, Yujie
Xiao, Jianru
author_facet Wang, Da
Liu, Fanrong
Li, Binbin
Xu, Jinhui
Gong, Haiyi
Yang, Minglei
Wan, Wei
Jiao, Jian
Liu, Yujie
Xiao, Jianru
author_sort Wang, Da
collection PubMed
description Background: Primary pelvis and spine osteosarcoma (PSOS) is a specific type of osteosarcoma that is difficult to treat and has a poor prognosis. In recent years, the research on osteosarcoma has been increasing, but there have been few studies on PSOS; in particular, there have been a lack of analyses with a large sample size. This study aimed to construct and validate a model to predict the overall survival (OS) of PSOS patients, as currently there are no tools available for assessing their prognosis. Methods: Data including demographic information, clinical characteristics, and follow-up information on patients with PSOS were collected from the Surveillance, Epidemiology, and End Results (SEER) database, as well as from the Spine Tumor Center of Changzheng Hospital. Variable selection was achieved through a backward procedure based on the Akaike Information Criterion (AIC). Prognostic factors were identified by univariate and multivariate Cox analysis. A nomogram was further constructed for the estimation of 1-, 3-, and 5-year OS. Calibration plots, the concordance index (C-index), and the receiver operating characteristic (ROC) were used to evaluate the prediction model. Results: In total, 83 PSOS patients and 90 PSOS patients were separately collected from the SEER database and Changzheng Hospital. In the SEER cohort, liver metastasis, lung metastasis, and chemotherapy were recognized as independent prognostic factors for OS (p < 0.05) and were incorporated to construct the initial nomogram. However, the initial nomogram showed poor predictive accuracy in internal and external validation. Then, we shifted our focus to the Changzheng data. Lung metastasis involving segments, Eastern Cooperative Oncology Group (ECOG) performance score, alkaline phosphatase (ALP) level, and en bloc resection were ultimately identified as independent prognostic factors for OS (p < 0.05) and were further incorporated to construct the current nomogram, of which the bias-corrected C-index was 0.834 (0.824–0.856). The areas under the ROC curves (AUCs) of the current nomogram regarding 1-, 3-, and 5-year OS probabilities were 0.93, 0.96, and 0.92, respectively. Conclusion: We have developed a predictive model with satisfactory performance and clinical practicability, enabling effective prediction of the OS of PSOS patients and aiding clinicians in decision-making.
format Online
Article
Text
id pubmed-10095419
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-100954192023-04-13 Development and Validation of a Prognostic Model for Overall Survival in Patients with Primary Pelvis and Spine Osteosarcoma: A Population-Based Study and External Validation Wang, Da Liu, Fanrong Li, Binbin Xu, Jinhui Gong, Haiyi Yang, Minglei Wan, Wei Jiao, Jian Liu, Yujie Xiao, Jianru J Clin Med Article Background: Primary pelvis and spine osteosarcoma (PSOS) is a specific type of osteosarcoma that is difficult to treat and has a poor prognosis. In recent years, the research on osteosarcoma has been increasing, but there have been few studies on PSOS; in particular, there have been a lack of analyses with a large sample size. This study aimed to construct and validate a model to predict the overall survival (OS) of PSOS patients, as currently there are no tools available for assessing their prognosis. Methods: Data including demographic information, clinical characteristics, and follow-up information on patients with PSOS were collected from the Surveillance, Epidemiology, and End Results (SEER) database, as well as from the Spine Tumor Center of Changzheng Hospital. Variable selection was achieved through a backward procedure based on the Akaike Information Criterion (AIC). Prognostic factors were identified by univariate and multivariate Cox analysis. A nomogram was further constructed for the estimation of 1-, 3-, and 5-year OS. Calibration plots, the concordance index (C-index), and the receiver operating characteristic (ROC) were used to evaluate the prediction model. Results: In total, 83 PSOS patients and 90 PSOS patients were separately collected from the SEER database and Changzheng Hospital. In the SEER cohort, liver metastasis, lung metastasis, and chemotherapy were recognized as independent prognostic factors for OS (p < 0.05) and were incorporated to construct the initial nomogram. However, the initial nomogram showed poor predictive accuracy in internal and external validation. Then, we shifted our focus to the Changzheng data. Lung metastasis involving segments, Eastern Cooperative Oncology Group (ECOG) performance score, alkaline phosphatase (ALP) level, and en bloc resection were ultimately identified as independent prognostic factors for OS (p < 0.05) and were further incorporated to construct the current nomogram, of which the bias-corrected C-index was 0.834 (0.824–0.856). The areas under the ROC curves (AUCs) of the current nomogram regarding 1-, 3-, and 5-year OS probabilities were 0.93, 0.96, and 0.92, respectively. Conclusion: We have developed a predictive model with satisfactory performance and clinical practicability, enabling effective prediction of the OS of PSOS patients and aiding clinicians in decision-making. MDPI 2023-03-27 /pmc/articles/PMC10095419/ /pubmed/37048606 http://dx.doi.org/10.3390/jcm12072521 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wang, Da
Liu, Fanrong
Li, Binbin
Xu, Jinhui
Gong, Haiyi
Yang, Minglei
Wan, Wei
Jiao, Jian
Liu, Yujie
Xiao, Jianru
Development and Validation of a Prognostic Model for Overall Survival in Patients with Primary Pelvis and Spine Osteosarcoma: A Population-Based Study and External Validation
title Development and Validation of a Prognostic Model for Overall Survival in Patients with Primary Pelvis and Spine Osteosarcoma: A Population-Based Study and External Validation
title_full Development and Validation of a Prognostic Model for Overall Survival in Patients with Primary Pelvis and Spine Osteosarcoma: A Population-Based Study and External Validation
title_fullStr Development and Validation of a Prognostic Model for Overall Survival in Patients with Primary Pelvis and Spine Osteosarcoma: A Population-Based Study and External Validation
title_full_unstemmed Development and Validation of a Prognostic Model for Overall Survival in Patients with Primary Pelvis and Spine Osteosarcoma: A Population-Based Study and External Validation
title_short Development and Validation of a Prognostic Model for Overall Survival in Patients with Primary Pelvis and Spine Osteosarcoma: A Population-Based Study and External Validation
title_sort development and validation of a prognostic model for overall survival in patients with primary pelvis and spine osteosarcoma: a population-based study and external validation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10095419/
https://www.ncbi.nlm.nih.gov/pubmed/37048606
http://dx.doi.org/10.3390/jcm12072521
work_keys_str_mv AT wangda developmentandvalidationofaprognosticmodelforoverallsurvivalinpatientswithprimarypelvisandspineosteosarcomaapopulationbasedstudyandexternalvalidation
AT liufanrong developmentandvalidationofaprognosticmodelforoverallsurvivalinpatientswithprimarypelvisandspineosteosarcomaapopulationbasedstudyandexternalvalidation
AT libinbin developmentandvalidationofaprognosticmodelforoverallsurvivalinpatientswithprimarypelvisandspineosteosarcomaapopulationbasedstudyandexternalvalidation
AT xujinhui developmentandvalidationofaprognosticmodelforoverallsurvivalinpatientswithprimarypelvisandspineosteosarcomaapopulationbasedstudyandexternalvalidation
AT gonghaiyi developmentandvalidationofaprognosticmodelforoverallsurvivalinpatientswithprimarypelvisandspineosteosarcomaapopulationbasedstudyandexternalvalidation
AT yangminglei developmentandvalidationofaprognosticmodelforoverallsurvivalinpatientswithprimarypelvisandspineosteosarcomaapopulationbasedstudyandexternalvalidation
AT wanwei developmentandvalidationofaprognosticmodelforoverallsurvivalinpatientswithprimarypelvisandspineosteosarcomaapopulationbasedstudyandexternalvalidation
AT jiaojian developmentandvalidationofaprognosticmodelforoverallsurvivalinpatientswithprimarypelvisandspineosteosarcomaapopulationbasedstudyandexternalvalidation
AT liuyujie developmentandvalidationofaprognosticmodelforoverallsurvivalinpatientswithprimarypelvisandspineosteosarcomaapopulationbasedstudyandexternalvalidation
AT xiaojianru developmentandvalidationofaprognosticmodelforoverallsurvivalinpatientswithprimarypelvisandspineosteosarcomaapopulationbasedstudyandexternalvalidation