Cargando…

Development and validation of a prognostic nomogram for early stage non-small cell lung cancer: a study based on the SEER database and a Chinese cohort

OBJECTIVE: This study aimed to construct a nomogram to effectively predict the overall survival (OS) of patients with early-stage non-small-cell lung cancer (NSCLC). METHODS: For the training and internal validation cohorts, a total of 26,941 patients with stage I and II NSCLC were obtained from the...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhou, Liang, Zhang, Yahui, Chen, Wenyu, Niu, Niu, Zhao, Junjie, Qi, Weibo, Xu, Yufen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9476583/
https://www.ncbi.nlm.nih.gov/pubmed/36104656
http://dx.doi.org/10.1186/s12885-022-10067-8
_version_ 1784790170576355328
author Zhou, Liang
Zhang, Yahui
Chen, Wenyu
Niu, Niu
Zhao, Junjie
Qi, Weibo
Xu, Yufen
author_facet Zhou, Liang
Zhang, Yahui
Chen, Wenyu
Niu, Niu
Zhao, Junjie
Qi, Weibo
Xu, Yufen
author_sort Zhou, Liang
collection PubMed
description OBJECTIVE: This study aimed to construct a nomogram to effectively predict the overall survival (OS) of patients with early-stage non-small-cell lung cancer (NSCLC). METHODS: For the training and internal validation cohorts, a total of 26,941 patients with stage I and II NSCLC were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. A nomogram was constructed based on the risk factors affecting prognosis using a Cox proportional hazards regression model. And 505 patients were recruited from Jiaxing First Hospital for external validation. The discrimination and calibration of the nomogram were evaluated by C-index and calibration curves. RESULTS: A Nomogram was created after identifying independent prognostic factors using univariate and multifactorial factor analysis. The C-index of this nomogram was 0.726 (95% CI, 0.718–0.735) and 0.721 (95% CI, 0.709–0.734) in the training cohort and the internal validation cohort, respectively, and 0.758 (95% CI, 0.691–0.825) in the external validation cohort, which indicates that the model has good discrimination. Calibration curves for 1-, 3-, and 5-year OS probabilities showed good agreement between predicted and actual survival. In addition, DCA analysis showed that the net benefit of the new model was significantly higher than that of the TNM staging system. CONCLUSION: We developed and validated a survival prediction model for patients with non-small cell lung cancer in the early stages. This new nomogram is superior to the traditional TNM staging system and can guide clinicians to make the best clinical decisions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-10067-8.
format Online
Article
Text
id pubmed-9476583
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-94765832022-09-16 Development and validation of a prognostic nomogram for early stage non-small cell lung cancer: a study based on the SEER database and a Chinese cohort Zhou, Liang Zhang, Yahui Chen, Wenyu Niu, Niu Zhao, Junjie Qi, Weibo Xu, Yufen BMC Cancer Research OBJECTIVE: This study aimed to construct a nomogram to effectively predict the overall survival (OS) of patients with early-stage non-small-cell lung cancer (NSCLC). METHODS: For the training and internal validation cohorts, a total of 26,941 patients with stage I and II NSCLC were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. A nomogram was constructed based on the risk factors affecting prognosis using a Cox proportional hazards regression model. And 505 patients were recruited from Jiaxing First Hospital for external validation. The discrimination and calibration of the nomogram were evaluated by C-index and calibration curves. RESULTS: A Nomogram was created after identifying independent prognostic factors using univariate and multifactorial factor analysis. The C-index of this nomogram was 0.726 (95% CI, 0.718–0.735) and 0.721 (95% CI, 0.709–0.734) in the training cohort and the internal validation cohort, respectively, and 0.758 (95% CI, 0.691–0.825) in the external validation cohort, which indicates that the model has good discrimination. Calibration curves for 1-, 3-, and 5-year OS probabilities showed good agreement between predicted and actual survival. In addition, DCA analysis showed that the net benefit of the new model was significantly higher than that of the TNM staging system. CONCLUSION: We developed and validated a survival prediction model for patients with non-small cell lung cancer in the early stages. This new nomogram is superior to the traditional TNM staging system and can guide clinicians to make the best clinical decisions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-10067-8. BioMed Central 2022-09-14 /pmc/articles/PMC9476583/ /pubmed/36104656 http://dx.doi.org/10.1186/s12885-022-10067-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Zhou, Liang
Zhang, Yahui
Chen, Wenyu
Niu, Niu
Zhao, Junjie
Qi, Weibo
Xu, Yufen
Development and validation of a prognostic nomogram for early stage non-small cell lung cancer: a study based on the SEER database and a Chinese cohort
title Development and validation of a prognostic nomogram for early stage non-small cell lung cancer: a study based on the SEER database and a Chinese cohort
title_full Development and validation of a prognostic nomogram for early stage non-small cell lung cancer: a study based on the SEER database and a Chinese cohort
title_fullStr Development and validation of a prognostic nomogram for early stage non-small cell lung cancer: a study based on the SEER database and a Chinese cohort
title_full_unstemmed Development and validation of a prognostic nomogram for early stage non-small cell lung cancer: a study based on the SEER database and a Chinese cohort
title_short Development and validation of a prognostic nomogram for early stage non-small cell lung cancer: a study based on the SEER database and a Chinese cohort
title_sort development and validation of a prognostic nomogram for early stage non-small cell lung cancer: a study based on the seer database and a chinese cohort
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9476583/
https://www.ncbi.nlm.nih.gov/pubmed/36104656
http://dx.doi.org/10.1186/s12885-022-10067-8
work_keys_str_mv AT zhouliang developmentandvalidationofaprognosticnomogramforearlystagenonsmallcelllungcancerastudybasedontheseerdatabaseandachinesecohort
AT zhangyahui developmentandvalidationofaprognosticnomogramforearlystagenonsmallcelllungcancerastudybasedontheseerdatabaseandachinesecohort
AT chenwenyu developmentandvalidationofaprognosticnomogramforearlystagenonsmallcelllungcancerastudybasedontheseerdatabaseandachinesecohort
AT niuniu developmentandvalidationofaprognosticnomogramforearlystagenonsmallcelllungcancerastudybasedontheseerdatabaseandachinesecohort
AT zhaojunjie developmentandvalidationofaprognosticnomogramforearlystagenonsmallcelllungcancerastudybasedontheseerdatabaseandachinesecohort
AT qiweibo developmentandvalidationofaprognosticnomogramforearlystagenonsmallcelllungcancerastudybasedontheseerdatabaseandachinesecohort
AT xuyufen developmentandvalidationofaprognosticnomogramforearlystagenonsmallcelllungcancerastudybasedontheseerdatabaseandachinesecohort