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Clinical characteristics and prognosis of non-small cell lung cancer patients with liver metastasis: A population-based study
BACKGROUND: The presence of liver metastasis (LM) is an independent prognostic factor for shorter survival in non-small cell lung cancer (NSCLC) patients. The median overall survival of patients with involvement of the liver is less than 5 mo. At present, identifying prognostic factors and construct...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9631152/ https://www.ncbi.nlm.nih.gov/pubmed/36338221 http://dx.doi.org/10.12998/wjcc.v10.i30.10882 |
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author | Wang, Jun-Feng Lu, Hong-Di Wang, Ying Zhang, Rui Li, Xiang Wang, Sheng |
author_facet | Wang, Jun-Feng Lu, Hong-Di Wang, Ying Zhang, Rui Li, Xiang Wang, Sheng |
author_sort | Wang, Jun-Feng |
collection | PubMed |
description | BACKGROUND: The presence of liver metastasis (LM) is an independent prognostic factor for shorter survival in non-small cell lung cancer (NSCLC) patients. The median overall survival of patients with involvement of the liver is less than 5 mo. At present, identifying prognostic factors and constructing survival prediction nomogram for NSCLC patients with LM (NSCLC-LM) are highly desirable. AIM: To build a forecasting model to predict the survival time of NSCLC-LM patients. METHODS: Data on NSCLC-LM patients were collected from the Surveillance, Epidemiology, and End Results database between 2010 and 2018. Joinpoint analysis was used to estimate the incidence trend of NSCLC-LM. Kaplan-Meier curves were constructed to assess survival time. Cox regression was applied to select the independent prognostic predictors of cancer-specific survival (CSS). A nomogram was established and its prognostic performance was evaluated. RESULTS: The age-adjusted incidence of NSCLC-LM increased from 22.7 per 1000000 in 2010 to 25.2 in 2013, and then declined to 22.1 in 2018. According to the multivariable Cox regression analysis of the training set, age, marital status, sex, race, histological type, T stage, metastatic pattern, and whether the patient received chemotherapy or not were identified as independent prognostic factors for CSS (P < 0.05) and were further used to construct a nomogram. The C-indices of the training and validation sets were 0.726 and 0.722, respectively. The results of decision curve analyses (DCAs) and calibration curves showed that the nomogram was well-discriminated and had great clinical utility. CONCLUSION: We designed a nomogram model and further constructed a novel risk classification system based on easily accessible clinical factors which demonstrated excellent performance to predict the individual CSS of NSCLC-LM patients. |
format | Online Article Text |
id | pubmed-9631152 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-96311522022-11-04 Clinical characteristics and prognosis of non-small cell lung cancer patients with liver metastasis: A population-based study Wang, Jun-Feng Lu, Hong-Di Wang, Ying Zhang, Rui Li, Xiang Wang, Sheng World J Clin Cases Retrospective Cohort Study BACKGROUND: The presence of liver metastasis (LM) is an independent prognostic factor for shorter survival in non-small cell lung cancer (NSCLC) patients. The median overall survival of patients with involvement of the liver is less than 5 mo. At present, identifying prognostic factors and constructing survival prediction nomogram for NSCLC patients with LM (NSCLC-LM) are highly desirable. AIM: To build a forecasting model to predict the survival time of NSCLC-LM patients. METHODS: Data on NSCLC-LM patients were collected from the Surveillance, Epidemiology, and End Results database between 2010 and 2018. Joinpoint analysis was used to estimate the incidence trend of NSCLC-LM. Kaplan-Meier curves were constructed to assess survival time. Cox regression was applied to select the independent prognostic predictors of cancer-specific survival (CSS). A nomogram was established and its prognostic performance was evaluated. RESULTS: The age-adjusted incidence of NSCLC-LM increased from 22.7 per 1000000 in 2010 to 25.2 in 2013, and then declined to 22.1 in 2018. According to the multivariable Cox regression analysis of the training set, age, marital status, sex, race, histological type, T stage, metastatic pattern, and whether the patient received chemotherapy or not were identified as independent prognostic factors for CSS (P < 0.05) and were further used to construct a nomogram. The C-indices of the training and validation sets were 0.726 and 0.722, respectively. The results of decision curve analyses (DCAs) and calibration curves showed that the nomogram was well-discriminated and had great clinical utility. CONCLUSION: We designed a nomogram model and further constructed a novel risk classification system based on easily accessible clinical factors which demonstrated excellent performance to predict the individual CSS of NSCLC-LM patients. Baishideng Publishing Group Inc 2022-10-26 2022-10-26 /pmc/articles/PMC9631152/ /pubmed/36338221 http://dx.doi.org/10.12998/wjcc.v10.i30.10882 Text en ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/ |
spellingShingle | Retrospective Cohort Study Wang, Jun-Feng Lu, Hong-Di Wang, Ying Zhang, Rui Li, Xiang Wang, Sheng Clinical characteristics and prognosis of non-small cell lung cancer patients with liver metastasis: A population-based study |
title | Clinical characteristics and prognosis of non-small cell lung cancer patients with liver metastasis: A population-based study |
title_full | Clinical characteristics and prognosis of non-small cell lung cancer patients with liver metastasis: A population-based study |
title_fullStr | Clinical characteristics and prognosis of non-small cell lung cancer patients with liver metastasis: A population-based study |
title_full_unstemmed | Clinical characteristics and prognosis of non-small cell lung cancer patients with liver metastasis: A population-based study |
title_short | Clinical characteristics and prognosis of non-small cell lung cancer patients with liver metastasis: A population-based study |
title_sort | clinical characteristics and prognosis of non-small cell lung cancer patients with liver metastasis: a population-based study |
topic | Retrospective Cohort Study |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9631152/ https://www.ncbi.nlm.nih.gov/pubmed/36338221 http://dx.doi.org/10.12998/wjcc.v10.i30.10882 |
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