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A nomogram to predict prognosis of patients with lung adenosquamous carcinoma: a population-based study
BACKGROUND: Adenosquamous carcinoma (ASC) of the lung is an infrequent variant of lung cancer. This study aimed to identify independent risk factors and to develop a predictive model for the prognosis of ASC patients. METHODS: Patient data were extracted from the Surveillance, Epidemiology, and End...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7330383/ https://www.ncbi.nlm.nih.gov/pubmed/32642134 http://dx.doi.org/10.21037/jtd.2020.03.115 |
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author | Liang, Jiaqi Sui, Qihai Zheng, Yuansheng Bi, Guoshu Chen, Zhencong Li, Ming Huang, Yiwei Lu, Tao Zhan, Cheng Guo, Weigang |
author_facet | Liang, Jiaqi Sui, Qihai Zheng, Yuansheng Bi, Guoshu Chen, Zhencong Li, Ming Huang, Yiwei Lu, Tao Zhan, Cheng Guo, Weigang |
author_sort | Liang, Jiaqi |
collection | PubMed |
description | BACKGROUND: Adenosquamous carcinoma (ASC) of the lung is an infrequent variant of lung cancer. This study aimed to identify independent risk factors and to develop a predictive model for the prognosis of ASC patients. METHODS: Patient data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database (2004 to 2016) and database in our department (2010 to 2014). Overall survival (OS) was evaluated by the Kaplan-Meier method. Significant prognostic factors were identified by univariate analysis (UVA) and multivariate analysis (MVA) using the Cox proportional hazards regression. Competing risk model analyses were performed using cancer-specific survival outcomes. A nomogram was developed to predict patient 3-year and 5-year OS and was validated using data from the two databases. RESULTS: A total of 4,600 patients with ASC were included and divided into a training cohort (n=3,202) and two validation cohorts (n=1,372, n=26). Patients with ASC had significantly older age, lower grades of tumor differentiation or incidences of nodal, and distant invasions than adenocarcinoma and squamous cell carcinoma (SCC) of the lung (P<0.001), while the median survival time of ASC patients was intermediate [21.0 (19.3–22.7) months]. Age, sex, primary site of tumor, histological grade, T stage, N stage, M stage of the tumor, as well as surgery to the primary tumor site and chemotherapy were identified as independent factors for ASC (P<0.001). A reliable nomogram was established with a group of validation plots and concordance indices (C-indices) (internal: 0.755±0.010; external: 0.748±0.049 and 0.721±0.045). CONCLUSIONS: Age, sex, primary site of tumor, histological grade, T stage, N stage, M stage of the tumor, as well as surgery to the primary site of tumors and chemotherapy were independent risk factors for ASC patients. A validated nomogram was constructed to predict the prognosis based on the patient clinical characteristics. |
format | Online Article Text |
id | pubmed-7330383 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-73303832020-07-07 A nomogram to predict prognosis of patients with lung adenosquamous carcinoma: a population-based study Liang, Jiaqi Sui, Qihai Zheng, Yuansheng Bi, Guoshu Chen, Zhencong Li, Ming Huang, Yiwei Lu, Tao Zhan, Cheng Guo, Weigang J Thorac Dis Original Article BACKGROUND: Adenosquamous carcinoma (ASC) of the lung is an infrequent variant of lung cancer. This study aimed to identify independent risk factors and to develop a predictive model for the prognosis of ASC patients. METHODS: Patient data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database (2004 to 2016) and database in our department (2010 to 2014). Overall survival (OS) was evaluated by the Kaplan-Meier method. Significant prognostic factors were identified by univariate analysis (UVA) and multivariate analysis (MVA) using the Cox proportional hazards regression. Competing risk model analyses were performed using cancer-specific survival outcomes. A nomogram was developed to predict patient 3-year and 5-year OS and was validated using data from the two databases. RESULTS: A total of 4,600 patients with ASC were included and divided into a training cohort (n=3,202) and two validation cohorts (n=1,372, n=26). Patients with ASC had significantly older age, lower grades of tumor differentiation or incidences of nodal, and distant invasions than adenocarcinoma and squamous cell carcinoma (SCC) of the lung (P<0.001), while the median survival time of ASC patients was intermediate [21.0 (19.3–22.7) months]. Age, sex, primary site of tumor, histological grade, T stage, N stage, M stage of the tumor, as well as surgery to the primary tumor site and chemotherapy were identified as independent factors for ASC (P<0.001). A reliable nomogram was established with a group of validation plots and concordance indices (C-indices) (internal: 0.755±0.010; external: 0.748±0.049 and 0.721±0.045). CONCLUSIONS: Age, sex, primary site of tumor, histological grade, T stage, N stage, M stage of the tumor, as well as surgery to the primary site of tumors and chemotherapy were independent risk factors for ASC patients. A validated nomogram was constructed to predict the prognosis based on the patient clinical characteristics. AME Publishing Company 2020-05 /pmc/articles/PMC7330383/ /pubmed/32642134 http://dx.doi.org/10.21037/jtd.2020.03.115 Text en 2020 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 Liang, Jiaqi Sui, Qihai Zheng, Yuansheng Bi, Guoshu Chen, Zhencong Li, Ming Huang, Yiwei Lu, Tao Zhan, Cheng Guo, Weigang A nomogram to predict prognosis of patients with lung adenosquamous carcinoma: a population-based study |
title | A nomogram to predict prognosis of patients with lung adenosquamous carcinoma: a population-based study |
title_full | A nomogram to predict prognosis of patients with lung adenosquamous carcinoma: a population-based study |
title_fullStr | A nomogram to predict prognosis of patients with lung adenosquamous carcinoma: a population-based study |
title_full_unstemmed | A nomogram to predict prognosis of patients with lung adenosquamous carcinoma: a population-based study |
title_short | A nomogram to predict prognosis of patients with lung adenosquamous carcinoma: a population-based study |
title_sort | nomogram to predict prognosis of patients with lung adenosquamous carcinoma: a population-based study |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7330383/ https://www.ncbi.nlm.nih.gov/pubmed/32642134 http://dx.doi.org/10.21037/jtd.2020.03.115 |
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