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Risk Prediction Model for Synchronous Oligometastatic Non-Small Cell Lung Cancer: Thoracic Radiotherapy May Not Prolong Survival in High-Risk patients
BACKGROUND AND PURPOSE: On the basis of the promising clinical study results, thoracic radiotherapy (TRT) has become an integral part of treatment of synchronous oligometastatic non–small cell lung cancer (SOM-NSCLC). However, some of them experienced rapid disease progression after TRT and showed n...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9337860/ https://www.ncbi.nlm.nih.gov/pubmed/35912173 http://dx.doi.org/10.3389/fonc.2022.897329 |
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author | Meng, Chunliu Wang, Fang Tian, Jia Wei, Jia Li, Xue Ren, Kai Xu, Liming Zhao, Lujun Wang, Ping |
author_facet | Meng, Chunliu Wang, Fang Tian, Jia Wei, Jia Li, Xue Ren, Kai Xu, Liming Zhao, Lujun Wang, Ping |
author_sort | Meng, Chunliu |
collection | PubMed |
description | BACKGROUND AND PURPOSE: On the basis of the promising clinical study results, thoracic radiotherapy (TRT) has become an integral part of treatment of synchronous oligometastatic non–small cell lung cancer (SOM-NSCLC). However, some of them experienced rapid disease progression after TRT and showed no significant survival benefit. How to screen out such patients is a more concerned problem at present. In this study, we developed a risk-prediction model by screening hematological and clinical data of patients with SOM-NSCLC and identified patients who would not benefit from TRT. MATERIALS AND METHODS: We investigated patients with SOM-NSCLC between 2011 and 2019. A formula named Risk-Total was constructed using factors screened by LASSO-Cox regression analysis. Stabilized inverse probability treatment weight analysis was used to match the clinical characteristics between TRT and non-TRT groups. The primary endpoint was overall survival (OS). RESULTS: We finally included 283 patients divided into two groups: 188 cases for the training cohort and 95 for the validation cohort. Ten prognostic factors included in the Risk-Total formula were age, N stage, T stage, adrenal metastasis, liver metastasis, sensitive mutation status, local treatment status to metastatic sites, systemic inflammatory index, CEA, and Cyfra211. Patients were divided into low- and high-risk groups based on risk scores, and TRT was found to have improved the OS of low-risk patients (46.4 vs. 31.7 months, P = 0.083; 34.1 vs. 25.9 months, P = 0.078) but not that of high-risk patients (14.9 vs. 11.7 months, P = 0.663; 19.4 vs. 18.6 months, P = 0.811) in the training and validation sets, respectively. CONCLUSION: We developed a prediction model to help identify patients with SOM-NSCLC who would not benefit from TRT, and TRT could not improve the survival of high-risk patients. |
format | Online Article Text |
id | pubmed-9337860 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93378602022-07-30 Risk Prediction Model for Synchronous Oligometastatic Non-Small Cell Lung Cancer: Thoracic Radiotherapy May Not Prolong Survival in High-Risk patients Meng, Chunliu Wang, Fang Tian, Jia Wei, Jia Li, Xue Ren, Kai Xu, Liming Zhao, Lujun Wang, Ping Front Oncol Oncology BACKGROUND AND PURPOSE: On the basis of the promising clinical study results, thoracic radiotherapy (TRT) has become an integral part of treatment of synchronous oligometastatic non–small cell lung cancer (SOM-NSCLC). However, some of them experienced rapid disease progression after TRT and showed no significant survival benefit. How to screen out such patients is a more concerned problem at present. In this study, we developed a risk-prediction model by screening hematological and clinical data of patients with SOM-NSCLC and identified patients who would not benefit from TRT. MATERIALS AND METHODS: We investigated patients with SOM-NSCLC between 2011 and 2019. A formula named Risk-Total was constructed using factors screened by LASSO-Cox regression analysis. Stabilized inverse probability treatment weight analysis was used to match the clinical characteristics between TRT and non-TRT groups. The primary endpoint was overall survival (OS). RESULTS: We finally included 283 patients divided into two groups: 188 cases for the training cohort and 95 for the validation cohort. Ten prognostic factors included in the Risk-Total formula were age, N stage, T stage, adrenal metastasis, liver metastasis, sensitive mutation status, local treatment status to metastatic sites, systemic inflammatory index, CEA, and Cyfra211. Patients were divided into low- and high-risk groups based on risk scores, and TRT was found to have improved the OS of low-risk patients (46.4 vs. 31.7 months, P = 0.083; 34.1 vs. 25.9 months, P = 0.078) but not that of high-risk patients (14.9 vs. 11.7 months, P = 0.663; 19.4 vs. 18.6 months, P = 0.811) in the training and validation sets, respectively. CONCLUSION: We developed a prediction model to help identify patients with SOM-NSCLC who would not benefit from TRT, and TRT could not improve the survival of high-risk patients. Frontiers Media S.A. 2022-07-15 /pmc/articles/PMC9337860/ /pubmed/35912173 http://dx.doi.org/10.3389/fonc.2022.897329 Text en Copyright © 2022 Meng, Wang, Tian, Wei, Li, Ren, Xu, Zhao and Wang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Meng, Chunliu Wang, Fang Tian, Jia Wei, Jia Li, Xue Ren, Kai Xu, Liming Zhao, Lujun Wang, Ping Risk Prediction Model for Synchronous Oligometastatic Non-Small Cell Lung Cancer: Thoracic Radiotherapy May Not Prolong Survival in High-Risk patients |
title | Risk Prediction Model for Synchronous Oligometastatic Non-Small Cell Lung Cancer: Thoracic Radiotherapy May Not Prolong Survival in High-Risk patients |
title_full | Risk Prediction Model for Synchronous Oligometastatic Non-Small Cell Lung Cancer: Thoracic Radiotherapy May Not Prolong Survival in High-Risk patients |
title_fullStr | Risk Prediction Model for Synchronous Oligometastatic Non-Small Cell Lung Cancer: Thoracic Radiotherapy May Not Prolong Survival in High-Risk patients |
title_full_unstemmed | Risk Prediction Model for Synchronous Oligometastatic Non-Small Cell Lung Cancer: Thoracic Radiotherapy May Not Prolong Survival in High-Risk patients |
title_short | Risk Prediction Model for Synchronous Oligometastatic Non-Small Cell Lung Cancer: Thoracic Radiotherapy May Not Prolong Survival in High-Risk patients |
title_sort | risk prediction model for synchronous oligometastatic non-small cell lung cancer: thoracic radiotherapy may not prolong survival in high-risk patients |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9337860/ https://www.ncbi.nlm.nih.gov/pubmed/35912173 http://dx.doi.org/10.3389/fonc.2022.897329 |
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