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Development and validation of web-based dynamic nomograms predictive of disease-free and overall survival in patients who underwent pneumonectomy for primary lung cancer

BACKGROUND: The tumour-node-metastasis (TNM) staging system is insufficient to precisely distinguish the long-term survival of patients who underwent pneumonectomy for primary lung cancer. Therefore, this study sought to identify determinants of disease-free (DFS) and overall survival (OS) for incor...

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Autores principales: Yu, Xiangyang, Wang, Feng, Yang, Longjun, Ma, Kai, Guo, Xiaotong, Wang, Lixu, Du, Longde, Yu, Xin, Lin, Shengcheng, Xiao, Hua, Sui, Zhilin, Zhang, Lanjun, Yu, Zhentao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10448881/
https://www.ncbi.nlm.nih.gov/pubmed/37637160
http://dx.doi.org/10.7717/peerj.15938
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author Yu, Xiangyang
Wang, Feng
Yang, Longjun
Ma, Kai
Guo, Xiaotong
Wang, Lixu
Du, Longde
Yu, Xin
Lin, Shengcheng
Xiao, Hua
Sui, Zhilin
Zhang, Lanjun
Yu, Zhentao
author_facet Yu, Xiangyang
Wang, Feng
Yang, Longjun
Ma, Kai
Guo, Xiaotong
Wang, Lixu
Du, Longde
Yu, Xin
Lin, Shengcheng
Xiao, Hua
Sui, Zhilin
Zhang, Lanjun
Yu, Zhentao
author_sort Yu, Xiangyang
collection PubMed
description BACKGROUND: The tumour-node-metastasis (TNM) staging system is insufficient to precisely distinguish the long-term survival of patients who underwent pneumonectomy for primary lung cancer. Therefore, this study sought to identify determinants of disease-free (DFS) and overall survival (OS) for incorporation into web-based dynamic nomograms. METHODS: The clinicopathological variables, surgical methods and follow-up information of 1,261 consecutive patients who underwent pneumonectomy for primary lung cancer between January 2008 and December 2018 at Sun Yat-sen University Cancer Center were collected. Nomograms for predicting DFS and OS were built based on the significantly independent predictors identified in the training cohort (n = 1,009) and then were tested on the validation cohort (n = 252). The concordance index (C-index) and time-independent area under the receiver-operator characteristic curve (AUC) assessed the nomogram’s discrimination accuracy. Decision curve analysis (DCA) was applied to evaluate the clinical utility. RESULTS: During a median follow-up time of 40.5 months, disease recurrence and death were observed in 446 (35.4%) and 665 (52.7%) patients in the whole cohort, respectively. In the training cohort, a higher C-reactive protein to albumin ratio, intrapericardial pulmonary artery ligation, lymph node metastasis, and adjuvant therapy were significantly correlated with a higher risk for disease recurrence; similarly, the independent predictors for worse OS were intrapericardial pulmonary artery and vein ligation, higher T stage, lymph node metastasis, and no adjuvant therapy. In the validation cohort, the integrated DFS and OS nomograms showed well-fitted calibration curves and yielded good discrimination powers with C-index of 0.667 (95% confidence intervals CIs [0.610–0.724]) and 0.697 (95% CIs [0.649–0.745]), respectively. Moreover, the AUCs for 1-year, 3-year, and 5-year DFS were 0.655, 0.726, and 0.735, respectively, and those for 3-year, 5-year, and 10-year OS were 0.741, 0.765, and 0.709, respectively. DCA demonstrated that our nomograms could bring more net benefit than the TNM staging system. CONCLUSIONS: Although pneumonectomy for primary lung cancer has brought encouraging long-term outcomes, the constructed prediction models could assist in precisely identifying patients at high risk and developing personalized treatment strategies to further improve survival.
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spelling pubmed-104488812023-08-25 Development and validation of web-based dynamic nomograms predictive of disease-free and overall survival in patients who underwent pneumonectomy for primary lung cancer Yu, Xiangyang Wang, Feng Yang, Longjun Ma, Kai Guo, Xiaotong Wang, Lixu Du, Longde Yu, Xin Lin, Shengcheng Xiao, Hua Sui, Zhilin Zhang, Lanjun Yu, Zhentao PeerJ Oncology BACKGROUND: The tumour-node-metastasis (TNM) staging system is insufficient to precisely distinguish the long-term survival of patients who underwent pneumonectomy for primary lung cancer. Therefore, this study sought to identify determinants of disease-free (DFS) and overall survival (OS) for incorporation into web-based dynamic nomograms. METHODS: The clinicopathological variables, surgical methods and follow-up information of 1,261 consecutive patients who underwent pneumonectomy for primary lung cancer between January 2008 and December 2018 at Sun Yat-sen University Cancer Center were collected. Nomograms for predicting DFS and OS were built based on the significantly independent predictors identified in the training cohort (n = 1,009) and then were tested on the validation cohort (n = 252). The concordance index (C-index) and time-independent area under the receiver-operator characteristic curve (AUC) assessed the nomogram’s discrimination accuracy. Decision curve analysis (DCA) was applied to evaluate the clinical utility. RESULTS: During a median follow-up time of 40.5 months, disease recurrence and death were observed in 446 (35.4%) and 665 (52.7%) patients in the whole cohort, respectively. In the training cohort, a higher C-reactive protein to albumin ratio, intrapericardial pulmonary artery ligation, lymph node metastasis, and adjuvant therapy were significantly correlated with a higher risk for disease recurrence; similarly, the independent predictors for worse OS were intrapericardial pulmonary artery and vein ligation, higher T stage, lymph node metastasis, and no adjuvant therapy. In the validation cohort, the integrated DFS and OS nomograms showed well-fitted calibration curves and yielded good discrimination powers with C-index of 0.667 (95% confidence intervals CIs [0.610–0.724]) and 0.697 (95% CIs [0.649–0.745]), respectively. Moreover, the AUCs for 1-year, 3-year, and 5-year DFS were 0.655, 0.726, and 0.735, respectively, and those for 3-year, 5-year, and 10-year OS were 0.741, 0.765, and 0.709, respectively. DCA demonstrated that our nomograms could bring more net benefit than the TNM staging system. CONCLUSIONS: Although pneumonectomy for primary lung cancer has brought encouraging long-term outcomes, the constructed prediction models could assist in precisely identifying patients at high risk and developing personalized treatment strategies to further improve survival. PeerJ Inc. 2023-08-21 /pmc/articles/PMC10448881/ /pubmed/37637160 http://dx.doi.org/10.7717/peerj.15938 Text en © 2023 Yu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Oncology
Yu, Xiangyang
Wang, Feng
Yang, Longjun
Ma, Kai
Guo, Xiaotong
Wang, Lixu
Du, Longde
Yu, Xin
Lin, Shengcheng
Xiao, Hua
Sui, Zhilin
Zhang, Lanjun
Yu, Zhentao
Development and validation of web-based dynamic nomograms predictive of disease-free and overall survival in patients who underwent pneumonectomy for primary lung cancer
title Development and validation of web-based dynamic nomograms predictive of disease-free and overall survival in patients who underwent pneumonectomy for primary lung cancer
title_full Development and validation of web-based dynamic nomograms predictive of disease-free and overall survival in patients who underwent pneumonectomy for primary lung cancer
title_fullStr Development and validation of web-based dynamic nomograms predictive of disease-free and overall survival in patients who underwent pneumonectomy for primary lung cancer
title_full_unstemmed Development and validation of web-based dynamic nomograms predictive of disease-free and overall survival in patients who underwent pneumonectomy for primary lung cancer
title_short Development and validation of web-based dynamic nomograms predictive of disease-free and overall survival in patients who underwent pneumonectomy for primary lung cancer
title_sort development and validation of web-based dynamic nomograms predictive of disease-free and overall survival in patients who underwent pneumonectomy for primary lung cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10448881/
https://www.ncbi.nlm.nih.gov/pubmed/37637160
http://dx.doi.org/10.7717/peerj.15938
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