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Construction and Validation of Prognosis Nomogram for Metastatic Lung Squamous Cell Carcinoma: A Population-Based Study
Purpose: This study aimed to establish a nomogram to predict overall survival in lung squamous cell carcinoma patients with metastasis for clinical decision-making. Methods: We investigated lung squamous cell carcinoma patients diagnosed with stage M1 in the Surveillance, Epidemiology, and Final Res...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9558863/ https://www.ncbi.nlm.nih.gov/pubmed/36217877 http://dx.doi.org/10.1177/15330338221132035 |
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author | Liu, Yuting Sun, Min Xiong, Ying Gu, Xinyue Zhang, Kai Liu, Li |
author_facet | Liu, Yuting Sun, Min Xiong, Ying Gu, Xinyue Zhang, Kai Liu, Li |
author_sort | Liu, Yuting |
collection | PubMed |
description | Purpose: This study aimed to establish a nomogram to predict overall survival in lung squamous cell carcinoma patients with metastasis for clinical decision-making. Methods: We investigated lung squamous cell carcinoma patients diagnosed with stage M1 in the Surveillance, Epidemiology, and Final Results database between 2010 and 2015. They were divided into training cohort and validation cohort. In the training cohort, statistically significant prognostic factors were identified using univariate and multivariate Cox regression analysis, and an individualized nomogram model was developed. The model was evaluated by C-index, area under the curve, calibration plot, decision curve analysis, and risk group stratification. Results: In total, 9910 patients were included in our study, including 6937 in the training cohort and 2937 in the validation cohort. Factors containing age, T stage, N stage, bone metastasis, brain metastasis, liver metastasis, surgery, chemotherapy, and radiotherapy were independent prognostic factors for overall survival and were used in the construction of the nomogram. The C-index in the training cohort and validation cohort were 0.711 (95% confidenc interval: 0.705-0.717) and 0.707 (95% confidenc interval: 0.697-0.717), respectively. The time-dependent area under the curve of both groups was higher than 0.7 within 5 years. Calibration plots indicated that the nomogram-predicted survival was consistent with the recorded 6-month, 1-year, and 2-year prognoses. Furthermore, decision curve analysis revealed that the nomogram was clinically useful and had a better discriminative ability to recognize patients at high risk than the TNM criteria-based tumor staging. And then we developed an overall survival risk classification system based on the nomogram total points for each patient, which divided all patients into a high-risk group and a low-risk group. Finally, we implemented this nomogram in a free online tool. Conclusion: We constructed a nomogram and a corresponding risk classification system predicting the overall survival of lung squamous cell carcinoma patients with metastasis. These tools can assist in patients’ counseling and guide treatment decision-making. |
format | Online Article Text |
id | pubmed-9558863 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-95588632022-10-14 Construction and Validation of Prognosis Nomogram for Metastatic Lung Squamous Cell Carcinoma: A Population-Based Study Liu, Yuting Sun, Min Xiong, Ying Gu, Xinyue Zhang, Kai Liu, Li Technol Cancer Res Treat Screening, diagnosis, and treatment of lung cancer Purpose: This study aimed to establish a nomogram to predict overall survival in lung squamous cell carcinoma patients with metastasis for clinical decision-making. Methods: We investigated lung squamous cell carcinoma patients diagnosed with stage M1 in the Surveillance, Epidemiology, and Final Results database between 2010 and 2015. They were divided into training cohort and validation cohort. In the training cohort, statistically significant prognostic factors were identified using univariate and multivariate Cox regression analysis, and an individualized nomogram model was developed. The model was evaluated by C-index, area under the curve, calibration plot, decision curve analysis, and risk group stratification. Results: In total, 9910 patients were included in our study, including 6937 in the training cohort and 2937 in the validation cohort. Factors containing age, T stage, N stage, bone metastasis, brain metastasis, liver metastasis, surgery, chemotherapy, and radiotherapy were independent prognostic factors for overall survival and were used in the construction of the nomogram. The C-index in the training cohort and validation cohort were 0.711 (95% confidenc interval: 0.705-0.717) and 0.707 (95% confidenc interval: 0.697-0.717), respectively. The time-dependent area under the curve of both groups was higher than 0.7 within 5 years. Calibration plots indicated that the nomogram-predicted survival was consistent with the recorded 6-month, 1-year, and 2-year prognoses. Furthermore, decision curve analysis revealed that the nomogram was clinically useful and had a better discriminative ability to recognize patients at high risk than the TNM criteria-based tumor staging. And then we developed an overall survival risk classification system based on the nomogram total points for each patient, which divided all patients into a high-risk group and a low-risk group. Finally, we implemented this nomogram in a free online tool. Conclusion: We constructed a nomogram and a corresponding risk classification system predicting the overall survival of lung squamous cell carcinoma patients with metastasis. These tools can assist in patients’ counseling and guide treatment decision-making. SAGE Publications 2022-10-11 /pmc/articles/PMC9558863/ /pubmed/36217877 http://dx.doi.org/10.1177/15330338221132035 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Screening, diagnosis, and treatment of lung cancer Liu, Yuting Sun, Min Xiong, Ying Gu, Xinyue Zhang, Kai Liu, Li Construction and Validation of Prognosis Nomogram for Metastatic Lung Squamous Cell Carcinoma: A Population-Based Study |
title | Construction and Validation of Prognosis Nomogram for Metastatic Lung
Squamous Cell Carcinoma: A Population-Based Study |
title_full | Construction and Validation of Prognosis Nomogram for Metastatic Lung
Squamous Cell Carcinoma: A Population-Based Study |
title_fullStr | Construction and Validation of Prognosis Nomogram for Metastatic Lung
Squamous Cell Carcinoma: A Population-Based Study |
title_full_unstemmed | Construction and Validation of Prognosis Nomogram for Metastatic Lung
Squamous Cell Carcinoma: A Population-Based Study |
title_short | Construction and Validation of Prognosis Nomogram for Metastatic Lung
Squamous Cell Carcinoma: A Population-Based Study |
title_sort | construction and validation of prognosis nomogram for metastatic lung
squamous cell carcinoma: a population-based study |
topic | Screening, diagnosis, and treatment of lung cancer |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9558863/ https://www.ncbi.nlm.nih.gov/pubmed/36217877 http://dx.doi.org/10.1177/15330338221132035 |
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