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A novel LASSO‐derived prognostic model predicting survival for non‐small cell lung cancer patients with M1a diseases
INTRODUCTION: The current American Joint Committee on Cancer (AJCC) M1a staging of non‐small cell lung cancer (NSCLC) encompasses a wide disease spectrum, showing diverse prognosis. METHODS: Patients who diagnosed in an earlier period formed the training cohort, and those who diagnosed thereafter fo...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Blackwell Publishing Ltd
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8921928/ https://www.ncbi.nlm.nih.gov/pubmed/35128839 http://dx.doi.org/10.1002/cam4.4560 |
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author | Chen, Hongchao Huang, Chen Ge, Huiqing Chen, Qianshun Chen, Jing Li, Yuqiang Chen, Haiyong Luo, Shiyin Zhao, Lilan Xu, Xunyu |
author_facet | Chen, Hongchao Huang, Chen Ge, Huiqing Chen, Qianshun Chen, Jing Li, Yuqiang Chen, Haiyong Luo, Shiyin Zhao, Lilan Xu, Xunyu |
author_sort | Chen, Hongchao |
collection | PubMed |
description | INTRODUCTION: The current American Joint Committee on Cancer (AJCC) M1a staging of non‐small cell lung cancer (NSCLC) encompasses a wide disease spectrum, showing diverse prognosis. METHODS: Patients who diagnosed in an earlier period formed the training cohort, and those who diagnosed thereafter formed the validation cohort. Kaplan–Meier analysis was performed for the training cohort by dividing the M1a stage into three subgroups: (I) malignant pleural effusion (MPE) or malignant pericardial effusion (MPCE); (II) separate tumor nodules in contralateral lung (STCL); and (III) pleural tumor nodules on the ipsilateral lung (PTIL). Gender, age, histologic, N stage, grade, surgery for primary site, lymphadenectomy, M1a groups, and chemotherapy were selected as independent prognostic factors using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. And a nomogram was constructed using Cox hazard regression analysis. Accuracy and clinical practicability were separately tested by Harrell's concordance index, the receiver operating characteristic (ROC) curve, calibration plots, residual plot, the integrated discrimination improvement (IDI), net reclassification improvement (NRI), and decision curve analysis (DCA). RESULTS: The concordance index (0.661 for the training cohort and 0.688 for the validation cohort) and the area under the ROC curve (training cohort: 0.709 for 1‐year and 0.727 for 2‐year OS prediction; validation cohort: 0.737 for 1‐year and 0.734 for 2‐year OS prediction) indicated satisfactory discriminative ability of the nomogram. Calibration curve and DCA presented great prognostic accuracy, and clinical applicability. Its prognostic accuracy preceded the AJCC staging with evaluated NRI (1‐year: 0.327; 2‐year: 0.302) and IDI (1‐year: 0.138; 2‐year: 0.130). CONCLUSION: Our study established a nomogram for the prediction of 1‐ and 2‐year OS in patients with NSCLC diagnosed with stage M1a, facilitating healthcare workers to accurately evaluate the individual survival of M1a NSCLC patients. The accuracy and clinical applicability of this nomogram were validated. |
format | Online Article Text |
id | pubmed-8921928 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Blackwell Publishing Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-89219282022-03-21 A novel LASSO‐derived prognostic model predicting survival for non‐small cell lung cancer patients with M1a diseases Chen, Hongchao Huang, Chen Ge, Huiqing Chen, Qianshun Chen, Jing Li, Yuqiang Chen, Haiyong Luo, Shiyin Zhao, Lilan Xu, Xunyu Cancer Med Cancer Prevention INTRODUCTION: The current American Joint Committee on Cancer (AJCC) M1a staging of non‐small cell lung cancer (NSCLC) encompasses a wide disease spectrum, showing diverse prognosis. METHODS: Patients who diagnosed in an earlier period formed the training cohort, and those who diagnosed thereafter formed the validation cohort. Kaplan–Meier analysis was performed for the training cohort by dividing the M1a stage into three subgroups: (I) malignant pleural effusion (MPE) or malignant pericardial effusion (MPCE); (II) separate tumor nodules in contralateral lung (STCL); and (III) pleural tumor nodules on the ipsilateral lung (PTIL). Gender, age, histologic, N stage, grade, surgery for primary site, lymphadenectomy, M1a groups, and chemotherapy were selected as independent prognostic factors using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. And a nomogram was constructed using Cox hazard regression analysis. Accuracy and clinical practicability were separately tested by Harrell's concordance index, the receiver operating characteristic (ROC) curve, calibration plots, residual plot, the integrated discrimination improvement (IDI), net reclassification improvement (NRI), and decision curve analysis (DCA). RESULTS: The concordance index (0.661 for the training cohort and 0.688 for the validation cohort) and the area under the ROC curve (training cohort: 0.709 for 1‐year and 0.727 for 2‐year OS prediction; validation cohort: 0.737 for 1‐year and 0.734 for 2‐year OS prediction) indicated satisfactory discriminative ability of the nomogram. Calibration curve and DCA presented great prognostic accuracy, and clinical applicability. Its prognostic accuracy preceded the AJCC staging with evaluated NRI (1‐year: 0.327; 2‐year: 0.302) and IDI (1‐year: 0.138; 2‐year: 0.130). CONCLUSION: Our study established a nomogram for the prediction of 1‐ and 2‐year OS in patients with NSCLC diagnosed with stage M1a, facilitating healthcare workers to accurately evaluate the individual survival of M1a NSCLC patients. The accuracy and clinical applicability of this nomogram were validated. Blackwell Publishing Ltd 2022-02-06 /pmc/articles/PMC8921928/ /pubmed/35128839 http://dx.doi.org/10.1002/cam4.4560 Text en © 2022 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Cancer Prevention Chen, Hongchao Huang, Chen Ge, Huiqing Chen, Qianshun Chen, Jing Li, Yuqiang Chen, Haiyong Luo, Shiyin Zhao, Lilan Xu, Xunyu A novel LASSO‐derived prognostic model predicting survival for non‐small cell lung cancer patients with M1a diseases |
title | A novel LASSO‐derived prognostic model predicting survival for non‐small cell lung cancer patients with M1a diseases |
title_full | A novel LASSO‐derived prognostic model predicting survival for non‐small cell lung cancer patients with M1a diseases |
title_fullStr | A novel LASSO‐derived prognostic model predicting survival for non‐small cell lung cancer patients with M1a diseases |
title_full_unstemmed | A novel LASSO‐derived prognostic model predicting survival for non‐small cell lung cancer patients with M1a diseases |
title_short | A novel LASSO‐derived prognostic model predicting survival for non‐small cell lung cancer patients with M1a diseases |
title_sort | novel lasso‐derived prognostic model predicting survival for non‐small cell lung cancer patients with m1a diseases |
topic | Cancer Prevention |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8921928/ https://www.ncbi.nlm.nih.gov/pubmed/35128839 http://dx.doi.org/10.1002/cam4.4560 |
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