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Development and validation of a prognostic predictive model of pulmonary spindle cell carcinoma from the surveillance, epidemiology and end results database
BACKGROUND: Pulmonary spindle cell carcinoma (PSCC) is a rare type of non-small cell lung cancer (NSCLC). The prognostic influent factors and therapeutic methods of PSCC are unclear, for there are only some case reports or small samples’ analysis. This study aims to find prognosis related factors of...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9459631/ https://www.ncbi.nlm.nih.gov/pubmed/36093529 http://dx.doi.org/10.21037/tcr-22-427 |
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author | Li, Wei Zhang, Minghang Fu, Siyun Hao, Xuefeng Song, Liwei Wang, Jinghui Liu, Bin Xu, Shaofa |
author_facet | Li, Wei Zhang, Minghang Fu, Siyun Hao, Xuefeng Song, Liwei Wang, Jinghui Liu, Bin Xu, Shaofa |
author_sort | Li, Wei |
collection | PubMed |
description | BACKGROUND: Pulmonary spindle cell carcinoma (PSCC) is a rare type of non-small cell lung cancer (NSCLC). The prognostic influent factors and therapeutic methods of PSCC are unclear, for there are only some case reports or small samples’ analysis. This study aims to find prognosis related factors of PSCC, develop and validate a nomogram to predict their survival probability. METHODS: The Surveillance, Epidemiology, and End Results (SEER) 18 Registries database (2000–2018) was searched to study PSCC. According to diagnosed time, data was divided into primary cohort (2000–2015) and validation cohort (2016–2018), both followed until December 31 2018. Chosen by Least Absolute Shrinkage and Selection Operator (LASSO) regression, age, sex, stage, surgery, chemotherapy, N, size and history of malignancy were taken out as predictive variables. The primary cohort was used to develop a nomogram to predict 1-, 3- and 5-year overall survival (OS) probability, and be validated by the validation cohort using concordance index (C-index) and calibration curves. Both cohorts were used to conduct a Cox regression to find the influential factors on OS of PSCC. RESULTS: The nomogram shows a good concordance and discrimination on the prediction of OS, both internal (n=457 and C-index is 0.79) and external validation (n=100 and C-index is 0.76). The median survival time of PSCC is 4 months, with 20.1% OS possibility in 5 years. Multivariate analysis identified patients of older age [hazard ratio (HR), 1.02; 95% confidence interval (CI): 1.01–1.04], larger size of neoplasm (HR, 1.01; 95% CI: 1.01–1.01), M1 (HR, 2.96; 95% CI: 2.17–4.04), N2 (HR, 2.55; 95% CI: 1.81–3.59) or N3 (HR, 2.99; 95% CI: 1.58–5.66), regional stages (HR, 2.11; 95% CI: 1.29–3.44) and distant stages (HR, 6.17; 95% CI: 3.83–9.94) had a lower OS possibility, while surgery (HR, 0.39; 95% CI: 0.28–0.53) and history of malignancy (HR, 0.68; 95% CI: 0.48–0.98) was protective factors for PSCC. PSCC survived longer with surgery performed instead of chemotherapy or radiotherapy. CONCLUSIONS: Patients of PSCC have a poor prognosis, and using the nomogram developed by this study can predict their 1-, 3- and 5-year OS probability. Surgery is a better choice for PSCC and more studies are necessary to find potential treatment like targeted therapy, programmed death-1 (PD-1) and programmed death ligand 1 (PD-L1). |
format | Online Article Text |
id | pubmed-9459631 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-94596312022-09-10 Development and validation of a prognostic predictive model of pulmonary spindle cell carcinoma from the surveillance, epidemiology and end results database Li, Wei Zhang, Minghang Fu, Siyun Hao, Xuefeng Song, Liwei Wang, Jinghui Liu, Bin Xu, Shaofa Transl Cancer Res Original Article BACKGROUND: Pulmonary spindle cell carcinoma (PSCC) is a rare type of non-small cell lung cancer (NSCLC). The prognostic influent factors and therapeutic methods of PSCC are unclear, for there are only some case reports or small samples’ analysis. This study aims to find prognosis related factors of PSCC, develop and validate a nomogram to predict their survival probability. METHODS: The Surveillance, Epidemiology, and End Results (SEER) 18 Registries database (2000–2018) was searched to study PSCC. According to diagnosed time, data was divided into primary cohort (2000–2015) and validation cohort (2016–2018), both followed until December 31 2018. Chosen by Least Absolute Shrinkage and Selection Operator (LASSO) regression, age, sex, stage, surgery, chemotherapy, N, size and history of malignancy were taken out as predictive variables. The primary cohort was used to develop a nomogram to predict 1-, 3- and 5-year overall survival (OS) probability, and be validated by the validation cohort using concordance index (C-index) and calibration curves. Both cohorts were used to conduct a Cox regression to find the influential factors on OS of PSCC. RESULTS: The nomogram shows a good concordance and discrimination on the prediction of OS, both internal (n=457 and C-index is 0.79) and external validation (n=100 and C-index is 0.76). The median survival time of PSCC is 4 months, with 20.1% OS possibility in 5 years. Multivariate analysis identified patients of older age [hazard ratio (HR), 1.02; 95% confidence interval (CI): 1.01–1.04], larger size of neoplasm (HR, 1.01; 95% CI: 1.01–1.01), M1 (HR, 2.96; 95% CI: 2.17–4.04), N2 (HR, 2.55; 95% CI: 1.81–3.59) or N3 (HR, 2.99; 95% CI: 1.58–5.66), regional stages (HR, 2.11; 95% CI: 1.29–3.44) and distant stages (HR, 6.17; 95% CI: 3.83–9.94) had a lower OS possibility, while surgery (HR, 0.39; 95% CI: 0.28–0.53) and history of malignancy (HR, 0.68; 95% CI: 0.48–0.98) was protective factors for PSCC. PSCC survived longer with surgery performed instead of chemotherapy or radiotherapy. CONCLUSIONS: Patients of PSCC have a poor prognosis, and using the nomogram developed by this study can predict their 1-, 3- and 5-year OS probability. Surgery is a better choice for PSCC and more studies are necessary to find potential treatment like targeted therapy, programmed death-1 (PD-1) and programmed death ligand 1 (PD-L1). AME Publishing Company 2022-08 /pmc/articles/PMC9459631/ /pubmed/36093529 http://dx.doi.org/10.21037/tcr-22-427 Text en 2022 Translational Cancer Research. 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 Li, Wei Zhang, Minghang Fu, Siyun Hao, Xuefeng Song, Liwei Wang, Jinghui Liu, Bin Xu, Shaofa Development and validation of a prognostic predictive model of pulmonary spindle cell carcinoma from the surveillance, epidemiology and end results database |
title | Development and validation of a prognostic predictive model of pulmonary spindle cell carcinoma from the surveillance, epidemiology and end results database |
title_full | Development and validation of a prognostic predictive model of pulmonary spindle cell carcinoma from the surveillance, epidemiology and end results database |
title_fullStr | Development and validation of a prognostic predictive model of pulmonary spindle cell carcinoma from the surveillance, epidemiology and end results database |
title_full_unstemmed | Development and validation of a prognostic predictive model of pulmonary spindle cell carcinoma from the surveillance, epidemiology and end results database |
title_short | Development and validation of a prognostic predictive model of pulmonary spindle cell carcinoma from the surveillance, epidemiology and end results database |
title_sort | development and validation of a prognostic predictive model of pulmonary spindle cell carcinoma from the surveillance, epidemiology and end results database |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9459631/ https://www.ncbi.nlm.nih.gov/pubmed/36093529 http://dx.doi.org/10.21037/tcr-22-427 |
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