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Establishment and validation of a long-term prognosis prediction model for patients with non-small cell lung cancer

BACKGROUND: The incidence of non-small cell lung cancer ranks second among malignant tumors, while the mortality rate ranks first. We established a prediction model for the long-term prognosis of lung cancer patients to accurately identify patients with a high risk of postoperative death and provide...

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Autores principales: Mao, Yu, Tan, Nianxi, Xu, Cuicui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10183536/
https://www.ncbi.nlm.nih.gov/pubmed/37197504
http://dx.doi.org/10.21037/jtd-23-381
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author Mao, Yu
Tan, Nianxi
Xu, Cuicui
author_facet Mao, Yu
Tan, Nianxi
Xu, Cuicui
author_sort Mao, Yu
collection PubMed
description BACKGROUND: The incidence of non-small cell lung cancer ranks second among malignant tumors, while the mortality rate ranks first. We established a prediction model for the long-term prognosis of lung cancer patients to accurately identify patients with a high risk of postoperative death and provide a theoretical basis for improving the prognosis of patients with non-small cell lung cancer. METHODS: The data of 277 non-small cell lung cancer patients who underwent radical lung cancer resection at Shanghai Fengxian District Central Hospital between January 2016 and December 2017 were retrospectively collected. The patients, who were followed up for 5 years, were divided into a deceased group (n=127) and survival group (n=150) according to whether the patients had died 5 years after surgery or not. The clinical characteristics of the two groups were observed, and the risk factors of death within 5 years of surgery in lung cancer patients were analyzed. A nomogram predictive model was then established to analyze the value of the model in predicting the death within 5 years of surgery in patients with non-small cell lung cancer. RESULTS: Multivariate logistics regression analysis showed that carcinoembryonic antigen (CEA) >193.5 ng/mL, stage III lung cancer, peritumor invasion, and vascular tumor thrombus were independent risk factors of tumor-specific death after surgery in patients with non-small cell lung cancer (P<0.05). R 4.0.3 statistical software was used to randomly divide the dataset into a training set and validation set. The sample size of the training set was 194, and the sample size of the validation set was 83. The area under the receiver operating characteristic (ROC) curve was 0.850 [95% confidence interval (CI): 0.796–0.905] in the training set, and it was 0.779 (95% CI: 0.678–0.880) in the validation set. In the validation set, the model was assessed using the Hosmer-Lemeshow goodness-of-fit test, with a chi-square value of 9.270 and a P value of 0.320. CONCLUSIONS: Our model could accurately identify high risk of death within 5 years of surgery in non-small cell lung cancer patients. Strengthening the management of high-risk patients may help improve the prognosis of these patients.
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spelling pubmed-101835362023-05-16 Establishment and validation of a long-term prognosis prediction model for patients with non-small cell lung cancer Mao, Yu Tan, Nianxi Xu, Cuicui J Thorac Dis Original Article BACKGROUND: The incidence of non-small cell lung cancer ranks second among malignant tumors, while the mortality rate ranks first. We established a prediction model for the long-term prognosis of lung cancer patients to accurately identify patients with a high risk of postoperative death and provide a theoretical basis for improving the prognosis of patients with non-small cell lung cancer. METHODS: The data of 277 non-small cell lung cancer patients who underwent radical lung cancer resection at Shanghai Fengxian District Central Hospital between January 2016 and December 2017 were retrospectively collected. The patients, who were followed up for 5 years, were divided into a deceased group (n=127) and survival group (n=150) according to whether the patients had died 5 years after surgery or not. The clinical characteristics of the two groups were observed, and the risk factors of death within 5 years of surgery in lung cancer patients were analyzed. A nomogram predictive model was then established to analyze the value of the model in predicting the death within 5 years of surgery in patients with non-small cell lung cancer. RESULTS: Multivariate logistics regression analysis showed that carcinoembryonic antigen (CEA) >193.5 ng/mL, stage III lung cancer, peritumor invasion, and vascular tumor thrombus were independent risk factors of tumor-specific death after surgery in patients with non-small cell lung cancer (P<0.05). R 4.0.3 statistical software was used to randomly divide the dataset into a training set and validation set. The sample size of the training set was 194, and the sample size of the validation set was 83. The area under the receiver operating characteristic (ROC) curve was 0.850 [95% confidence interval (CI): 0.796–0.905] in the training set, and it was 0.779 (95% CI: 0.678–0.880) in the validation set. In the validation set, the model was assessed using the Hosmer-Lemeshow goodness-of-fit test, with a chi-square value of 9.270 and a P value of 0.320. CONCLUSIONS: Our model could accurately identify high risk of death within 5 years of surgery in non-small cell lung cancer patients. Strengthening the management of high-risk patients may help improve the prognosis of these patients. AME Publishing Company 2023-04-24 2023-04-28 /pmc/articles/PMC10183536/ /pubmed/37197504 http://dx.doi.org/10.21037/jtd-23-381 Text en 2023 Journal of Thoracic Disease. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Mao, Yu
Tan, Nianxi
Xu, Cuicui
Establishment and validation of a long-term prognosis prediction model for patients with non-small cell lung cancer
title Establishment and validation of a long-term prognosis prediction model for patients with non-small cell lung cancer
title_full Establishment and validation of a long-term prognosis prediction model for patients with non-small cell lung cancer
title_fullStr Establishment and validation of a long-term prognosis prediction model for patients with non-small cell lung cancer
title_full_unstemmed Establishment and validation of a long-term prognosis prediction model for patients with non-small cell lung cancer
title_short Establishment and validation of a long-term prognosis prediction model for patients with non-small cell lung cancer
title_sort establishment and validation of a long-term prognosis prediction model for patients with non-small cell lung cancer
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10183536/
https://www.ncbi.nlm.nih.gov/pubmed/37197504
http://dx.doi.org/10.21037/jtd-23-381
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