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Nomograms for predicting survival outcomes in patients with primary tracheal tumors: a large population-based analysis

BACKGROUND: The aim of this study was to develop and validate reliable nomograms to predict individual overall survival (OS) and cancer-specific survival (CSS) for patients with primary tracheal tumors and further estimate the role of postoperative radiotherapy (PORT) for these entities. PATIENTS AN...

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Autores principales: Wen, Junmiao, Liu, Di, Xu, Xinyan, Chen, Donglai, Chen, Yongbing, Sun, Liang, Chen, Jiayan, Fan, Min
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6294060/
https://www.ncbi.nlm.nih.gov/pubmed/30588090
http://dx.doi.org/10.2147/CMAR.S186546
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author Wen, Junmiao
Liu, Di
Xu, Xinyan
Chen, Donglai
Chen, Yongbing
Sun, Liang
Chen, Jiayan
Fan, Min
author_facet Wen, Junmiao
Liu, Di
Xu, Xinyan
Chen, Donglai
Chen, Yongbing
Sun, Liang
Chen, Jiayan
Fan, Min
author_sort Wen, Junmiao
collection PubMed
description BACKGROUND: The aim of this study was to develop and validate reliable nomograms to predict individual overall survival (OS) and cancer-specific survival (CSS) for patients with primary tracheal tumors and further estimate the role of postoperative radiotherapy (PORT) for these entities. PATIENTS AND METHODS: A total of 405 eligible patients diagnosed between 1988 and 2015 were selected from the Surveillance, Epidemiology, and End Results database. All of them were randomly divided into training (n=303) and validation (n=102) sets. For the purpose of establishing nomograms, the Akaike information criterion was employed to select significant prognostic factors in multivariate Cox regression models. Both internal and external validations of the nomograms were evaluated by Harrell’s concordance index (C-index) and calibration plots. Propensity score matching (PSM) method was performed to reduce the influence of selection bias between the PORT group and the non-PORT group. RESULTS: Two nomograms shared common variables including age at diagnosis, histology, N and M stages, tumor size, and treatment types, while gender was only incorporated in the CSS nomogram. The C-indices of OS and CSS nomograms were 0.817 and 0.813, displaying considerable predictive accuracy. The calibration curves indicated consistency between the nomograms and the actual observations. When the nomograms were applied to the validation set, the results remained reconcilable. Moreover, the nomograms showed superiority over the Bhattacharyya’s staging system with regard to the C-indices. After PSM, PORT was not associated with significantly better OS or CSS. Only squamous cell carcinoma (SCC) patients in the PORT group had improved OS compared to non-PORT group. CONCLUSION: The first two nomograms for predicting survival in patients with primary tracheal tumors were proposed in the present study. PORT seems to improve the prognosis of SCC patients, which needs further exploration.
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spelling pubmed-62940602018-12-26 Nomograms for predicting survival outcomes in patients with primary tracheal tumors: a large population-based analysis Wen, Junmiao Liu, Di Xu, Xinyan Chen, Donglai Chen, Yongbing Sun, Liang Chen, Jiayan Fan, Min Cancer Manag Res Original Research BACKGROUND: The aim of this study was to develop and validate reliable nomograms to predict individual overall survival (OS) and cancer-specific survival (CSS) for patients with primary tracheal tumors and further estimate the role of postoperative radiotherapy (PORT) for these entities. PATIENTS AND METHODS: A total of 405 eligible patients diagnosed between 1988 and 2015 were selected from the Surveillance, Epidemiology, and End Results database. All of them were randomly divided into training (n=303) and validation (n=102) sets. For the purpose of establishing nomograms, the Akaike information criterion was employed to select significant prognostic factors in multivariate Cox regression models. Both internal and external validations of the nomograms were evaluated by Harrell’s concordance index (C-index) and calibration plots. Propensity score matching (PSM) method was performed to reduce the influence of selection bias between the PORT group and the non-PORT group. RESULTS: Two nomograms shared common variables including age at diagnosis, histology, N and M stages, tumor size, and treatment types, while gender was only incorporated in the CSS nomogram. The C-indices of OS and CSS nomograms were 0.817 and 0.813, displaying considerable predictive accuracy. The calibration curves indicated consistency between the nomograms and the actual observations. When the nomograms were applied to the validation set, the results remained reconcilable. Moreover, the nomograms showed superiority over the Bhattacharyya’s staging system with regard to the C-indices. After PSM, PORT was not associated with significantly better OS or CSS. Only squamous cell carcinoma (SCC) patients in the PORT group had improved OS compared to non-PORT group. CONCLUSION: The first two nomograms for predicting survival in patients with primary tracheal tumors were proposed in the present study. PORT seems to improve the prognosis of SCC patients, which needs further exploration. Dove Medical Press 2018-12-11 /pmc/articles/PMC6294060/ /pubmed/30588090 http://dx.doi.org/10.2147/CMAR.S186546 Text en © 2018 Wen et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.
spellingShingle Original Research
Wen, Junmiao
Liu, Di
Xu, Xinyan
Chen, Donglai
Chen, Yongbing
Sun, Liang
Chen, Jiayan
Fan, Min
Nomograms for predicting survival outcomes in patients with primary tracheal tumors: a large population-based analysis
title Nomograms for predicting survival outcomes in patients with primary tracheal tumors: a large population-based analysis
title_full Nomograms for predicting survival outcomes in patients with primary tracheal tumors: a large population-based analysis
title_fullStr Nomograms for predicting survival outcomes in patients with primary tracheal tumors: a large population-based analysis
title_full_unstemmed Nomograms for predicting survival outcomes in patients with primary tracheal tumors: a large population-based analysis
title_short Nomograms for predicting survival outcomes in patients with primary tracheal tumors: a large population-based analysis
title_sort nomograms for predicting survival outcomes in patients with primary tracheal tumors: a large population-based analysis
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6294060/
https://www.ncbi.nlm.nih.gov/pubmed/30588090
http://dx.doi.org/10.2147/CMAR.S186546
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