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Gender-specific nomogram models to predict the prognosis of male and female lung adenocarcinoma patients: a population-based analysis
BACKGROUND: Epidemiological and clinical prognosis differences between male and female lung adenocarcinoma (LUAD) patients have been frequently reported. To improve prognosis determinations, gender-specific nomogram models should be developed and validated to predict the prognosis of patients with L...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8667099/ https://www.ncbi.nlm.nih.gov/pubmed/34988163 http://dx.doi.org/10.21037/atm-21-5367 |
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author | Wen, Hui Lin, Xuefeng Sun, Daqiang |
author_facet | Wen, Hui Lin, Xuefeng Sun, Daqiang |
author_sort | Wen, Hui |
collection | PubMed |
description | BACKGROUND: Epidemiological and clinical prognosis differences between male and female lung adenocarcinoma (LUAD) patients have been frequently reported. To improve prognosis determinations, gender-specific nomogram models should be developed and validated to predict the prognosis of patients with LUAD. METHODS: Using the Surveillance, Epidemiology, and End Results (SEER) database, LUAD patients diagnosed between 2010 and 2015 were used as SEER training and internal validation testing sets. Patients in Tianjin Chest Hospital with postoperative pathological diagnosis of LUAD from January 1, 2015 to October 1, 2016 were considered as Chinese external testing sets. Using the Kaplan-Meier method and log-rank tests, we compared all the included male and female LUAD patients’ overall survival (OS) and lung cancer-specific survival (LCSS) rates. The female and male patients from SEER database were randomly divided into training and internal validation groups at a 7:3 ratio. Variables (P<0.05) in the multivariable LCSS Cox regression analysis were independent prognostic predictors of the nomogram models. Harrell’s concordance index (C-index), calibration curves, decision curve analysis (DCA) curves, receiver operating characteristic (ROC) curves, and the area under the curves (AUCs) were used to test the calibration and accuracy of the gender-specific nomogram models. RESULTS: A total of 32,654 LUAD patients (17,372 females and 15,282 males) were identified. Ten variables [age, marital status, tumor site, differentiation grade, derived American Joint Committee on Cancer (AJCC) stage, tumor size, historic stage, surgery, derived AJCC N stage and chemotherapy] were statistically significant in the multivariate LCSS Cox regression analysis, and visualized through the nomogram models. The female and male training nomogram C-indexes were 0.827 and 0.811, respectively. The 3- and 5-year AUCs of the LCSS were 0.881 and 0.872 in the female training set, respectively, and 0.879 and 0.881 in the male training set, respectively. The DCA results indicated that these nomogram models were excellent predictors of LUAD prognosis and can be used to supplement the prognostication of tumor, node, and metastasis (TNM) stage. CONCLUSIONS: Given the different incidence and prognosis of LUAD between men and women, we developed gender-specific nomogram models with good discrimination and calibration capacity to predict 3- and 5-year LUAD-specific survival. |
format | Online Article Text |
id | pubmed-8667099 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-86670992022-01-04 Gender-specific nomogram models to predict the prognosis of male and female lung adenocarcinoma patients: a population-based analysis Wen, Hui Lin, Xuefeng Sun, Daqiang Ann Transl Med Original Article BACKGROUND: Epidemiological and clinical prognosis differences between male and female lung adenocarcinoma (LUAD) patients have been frequently reported. To improve prognosis determinations, gender-specific nomogram models should be developed and validated to predict the prognosis of patients with LUAD. METHODS: Using the Surveillance, Epidemiology, and End Results (SEER) database, LUAD patients diagnosed between 2010 and 2015 were used as SEER training and internal validation testing sets. Patients in Tianjin Chest Hospital with postoperative pathological diagnosis of LUAD from January 1, 2015 to October 1, 2016 were considered as Chinese external testing sets. Using the Kaplan-Meier method and log-rank tests, we compared all the included male and female LUAD patients’ overall survival (OS) and lung cancer-specific survival (LCSS) rates. The female and male patients from SEER database were randomly divided into training and internal validation groups at a 7:3 ratio. Variables (P<0.05) in the multivariable LCSS Cox regression analysis were independent prognostic predictors of the nomogram models. Harrell’s concordance index (C-index), calibration curves, decision curve analysis (DCA) curves, receiver operating characteristic (ROC) curves, and the area under the curves (AUCs) were used to test the calibration and accuracy of the gender-specific nomogram models. RESULTS: A total of 32,654 LUAD patients (17,372 females and 15,282 males) were identified. Ten variables [age, marital status, tumor site, differentiation grade, derived American Joint Committee on Cancer (AJCC) stage, tumor size, historic stage, surgery, derived AJCC N stage and chemotherapy] were statistically significant in the multivariate LCSS Cox regression analysis, and visualized through the nomogram models. The female and male training nomogram C-indexes were 0.827 and 0.811, respectively. The 3- and 5-year AUCs of the LCSS were 0.881 and 0.872 in the female training set, respectively, and 0.879 and 0.881 in the male training set, respectively. The DCA results indicated that these nomogram models were excellent predictors of LUAD prognosis and can be used to supplement the prognostication of tumor, node, and metastasis (TNM) stage. CONCLUSIONS: Given the different incidence and prognosis of LUAD between men and women, we developed gender-specific nomogram models with good discrimination and calibration capacity to predict 3- and 5-year LUAD-specific survival. AME Publishing Company 2021-11 /pmc/articles/PMC8667099/ /pubmed/34988163 http://dx.doi.org/10.21037/atm-21-5367 Text en 2021 Annals of Translational Medicine. 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 Wen, Hui Lin, Xuefeng Sun, Daqiang Gender-specific nomogram models to predict the prognosis of male and female lung adenocarcinoma patients: a population-based analysis |
title | Gender-specific nomogram models to predict the prognosis of male and female lung adenocarcinoma patients: a population-based analysis |
title_full | Gender-specific nomogram models to predict the prognosis of male and female lung adenocarcinoma patients: a population-based analysis |
title_fullStr | Gender-specific nomogram models to predict the prognosis of male and female lung adenocarcinoma patients: a population-based analysis |
title_full_unstemmed | Gender-specific nomogram models to predict the prognosis of male and female lung adenocarcinoma patients: a population-based analysis |
title_short | Gender-specific nomogram models to predict the prognosis of male and female lung adenocarcinoma patients: a population-based analysis |
title_sort | gender-specific nomogram models to predict the prognosis of male and female lung adenocarcinoma patients: a population-based analysis |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8667099/ https://www.ncbi.nlm.nih.gov/pubmed/34988163 http://dx.doi.org/10.21037/atm-21-5367 |
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