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Survival Analysis and Prediction Model for Pulmonary Sarcomatoid Carcinoma Based on SEER Database

OBJECTIVE: This study aimed to investigate the incidence of the pulmonary sarcomatoid carcinoma (PSC), to compare the clinical characteristics and overall survival (OS) of patients with PSC and those with other non-small-cell lung cancer (oNSCLC), so as to analyze the factors affecting the OS of pat...

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Autores principales: Chen, Mingjing, Yang, Qiao, Xu, Zihan, Luo, Bangyu, Li, Feng, Yu, Yongxin, Sun, Jianguo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8201495/
https://www.ncbi.nlm.nih.gov/pubmed/34136380
http://dx.doi.org/10.3389/fonc.2021.630885
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author Chen, Mingjing
Yang, Qiao
Xu, Zihan
Luo, Bangyu
Li, Feng
Yu, Yongxin
Sun, Jianguo
author_facet Chen, Mingjing
Yang, Qiao
Xu, Zihan
Luo, Bangyu
Li, Feng
Yu, Yongxin
Sun, Jianguo
author_sort Chen, Mingjing
collection PubMed
description OBJECTIVE: This study aimed to investigate the incidence of the pulmonary sarcomatoid carcinoma (PSC), to compare the clinical characteristics and overall survival (OS) of patients with PSC and those with other non-small-cell lung cancer (oNSCLC), so as to analyze the factors affecting the OS of patients with PSC and construct a nomogram prediction model. METHODS: Data of patients with PSC and those with oNSCLC diagnosed between 2004 and 2015 from the Surveillance, Epidemiology, and End Results database were collected. The age-adjusted incidence of PSC was calculated. The characteristics of patients with PSC and those with oNSCLC were compared, then the patients were matched 1:2 for further survival analysis. Patients with PSC were randomly divided into training set and testing set with a ratio of 7:3. The Cox proportional hazards model was used to identify the covariates associated with the OS. Significant covariates were used to construct the nomogram, and the C-index was calculated to measure the discrimination ability. The accuracy of the nomogram was compared with the tumor–node–metastasis (TNM) clinical stage, and the corresponding area under the curve was achieved. RESULTS: A total of 1049 patients with PSC were enrolled, the incidence of PSC was slowly decreased from 0.120/100,000 in 2004 to 0.092/100,000 in 2015. Before PSM, 793 PSC patients and 191356 oNSCLC patients were identified, the proportion of male, younger patients (<65 years), grade IV, TNM clinical stage IV was higher in the PSC. The patients with PSC had significantly poorer OS compared with those with oNSCLC. After PSM, PSC still had an extremely inferior prognosis. Age, sex, TNM clinical stage, chemotherapy, radiotherapy, and surgery were independent factors for OS. Next, a nomogram was established based on these factors, and the C-indexs were 0.775 and 0.790 for the training and testing set, respectively. Moreover, the nomogram model indicated a more comprehensive and accurate prediction than the TNM clinical stage. CONCLUSIONS: The incidence of PSC was slowly decreased. PSC had a significantly poor prognosis compared with oNSCLC. The nomogram constructed in this study accurately predicted the prognosis of PSC, performed better than the TNM clinical stage.
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spelling pubmed-82014952021-06-15 Survival Analysis and Prediction Model for Pulmonary Sarcomatoid Carcinoma Based on SEER Database Chen, Mingjing Yang, Qiao Xu, Zihan Luo, Bangyu Li, Feng Yu, Yongxin Sun, Jianguo Front Oncol Oncology OBJECTIVE: This study aimed to investigate the incidence of the pulmonary sarcomatoid carcinoma (PSC), to compare the clinical characteristics and overall survival (OS) of patients with PSC and those with other non-small-cell lung cancer (oNSCLC), so as to analyze the factors affecting the OS of patients with PSC and construct a nomogram prediction model. METHODS: Data of patients with PSC and those with oNSCLC diagnosed between 2004 and 2015 from the Surveillance, Epidemiology, and End Results database were collected. The age-adjusted incidence of PSC was calculated. The characteristics of patients with PSC and those with oNSCLC were compared, then the patients were matched 1:2 for further survival analysis. Patients with PSC were randomly divided into training set and testing set with a ratio of 7:3. The Cox proportional hazards model was used to identify the covariates associated with the OS. Significant covariates were used to construct the nomogram, and the C-index was calculated to measure the discrimination ability. The accuracy of the nomogram was compared with the tumor–node–metastasis (TNM) clinical stage, and the corresponding area under the curve was achieved. RESULTS: A total of 1049 patients with PSC were enrolled, the incidence of PSC was slowly decreased from 0.120/100,000 in 2004 to 0.092/100,000 in 2015. Before PSM, 793 PSC patients and 191356 oNSCLC patients were identified, the proportion of male, younger patients (<65 years), grade IV, TNM clinical stage IV was higher in the PSC. The patients with PSC had significantly poorer OS compared with those with oNSCLC. After PSM, PSC still had an extremely inferior prognosis. Age, sex, TNM clinical stage, chemotherapy, radiotherapy, and surgery were independent factors for OS. Next, a nomogram was established based on these factors, and the C-indexs were 0.775 and 0.790 for the training and testing set, respectively. Moreover, the nomogram model indicated a more comprehensive and accurate prediction than the TNM clinical stage. CONCLUSIONS: The incidence of PSC was slowly decreased. PSC had a significantly poor prognosis compared with oNSCLC. The nomogram constructed in this study accurately predicted the prognosis of PSC, performed better than the TNM clinical stage. Frontiers Media S.A. 2021-05-31 /pmc/articles/PMC8201495/ /pubmed/34136380 http://dx.doi.org/10.3389/fonc.2021.630885 Text en Copyright © 2021 Chen, Yang, Xu, Luo, Li, Yu and Sun 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 Oncology
Chen, Mingjing
Yang, Qiao
Xu, Zihan
Luo, Bangyu
Li, Feng
Yu, Yongxin
Sun, Jianguo
Survival Analysis and Prediction Model for Pulmonary Sarcomatoid Carcinoma Based on SEER Database
title Survival Analysis and Prediction Model for Pulmonary Sarcomatoid Carcinoma Based on SEER Database
title_full Survival Analysis and Prediction Model for Pulmonary Sarcomatoid Carcinoma Based on SEER Database
title_fullStr Survival Analysis and Prediction Model for Pulmonary Sarcomatoid Carcinoma Based on SEER Database
title_full_unstemmed Survival Analysis and Prediction Model for Pulmonary Sarcomatoid Carcinoma Based on SEER Database
title_short Survival Analysis and Prediction Model for Pulmonary Sarcomatoid Carcinoma Based on SEER Database
title_sort survival analysis and prediction model for pulmonary sarcomatoid carcinoma based on seer database
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8201495/
https://www.ncbi.nlm.nih.gov/pubmed/34136380
http://dx.doi.org/10.3389/fonc.2021.630885
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