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Development and validation of a prediction model using molecular marker for long‐term survival in unresectable stage III non‐small cell lung cancer treated with chemoradiotherapy

BACKGROUND: This study aimed to establish a predictive nomogram integrating epidermal growth factor receptor (EGFR) mutation status for 3‐ and 5‐year overall survival (OS) in unresectable/inoperable stage III non‐small cell lung cancer (NSCLC) treated with definitive chemoradiotherapy. METHODS: A to...

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Autores principales: Yang, Yufan, Zhang, Tao, Zhou, Zongmei, Liang, Jun, Chen, Dongfu, Feng, Qinfu, Xiao, Zefen, Hui, Zhouguang, Lv, Jima, Deng, Lei, Wang, Xin, Wang, Wenqing, Wang, Jianyang, Liu, Wenyang, Zhai, Yirui, Wang, Jie, Bi, Nan, Wang, Luhua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons Australia, Ltd 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8807329/
https://www.ncbi.nlm.nih.gov/pubmed/34927371
http://dx.doi.org/10.1111/1759-7714.14218
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author Yang, Yufan
Zhang, Tao
Zhou, Zongmei
Liang, Jun
Chen, Dongfu
Feng, Qinfu
Xiao, Zefen
Hui, Zhouguang
Lv, Jima
Deng, Lei
Wang, Xin
Wang, Wenqing
Wang, Jianyang
Liu, Wenyang
Zhai, Yirui
Wang, Jie
Bi, Nan
Wang, Luhua
author_facet Yang, Yufan
Zhang, Tao
Zhou, Zongmei
Liang, Jun
Chen, Dongfu
Feng, Qinfu
Xiao, Zefen
Hui, Zhouguang
Lv, Jima
Deng, Lei
Wang, Xin
Wang, Wenqing
Wang, Jianyang
Liu, Wenyang
Zhai, Yirui
Wang, Jie
Bi, Nan
Wang, Luhua
author_sort Yang, Yufan
collection PubMed
description BACKGROUND: This study aimed to establish a predictive nomogram integrating epidermal growth factor receptor (EGFR) mutation status for 3‐ and 5‐year overall survival (OS) in unresectable/inoperable stage III non‐small cell lung cancer (NSCLC) treated with definitive chemoradiotherapy. METHODS: A total of 533 stage III NSCLC patients receiving chemoradiotherapy from 2013 to 2017 in our institution were included and divided into training and testing sets (2:1). Significant factors impacting OS were identified in the training set and integrated into the nomogram based on Cox proportional hazards regression. The model was subject to bootstrap internal validation and external validation within the testing set and an independent cohort from a phase III trial. The accuracy and discriminative capacity of the model were examined by calibration plots, C‐indexes and risk stratifications. RESULTS: The final multivariate model incorporated sex, smoking history, histology (including EGFR mutation status), TNM stage, planning target volume, chemotherapy sequence and radiation pneumonitis grade. The bootstrapped C‐indexes in the training set were 0.688, 0.710 for the 3‐ and 5‐year OS. For external validation, C‐indexes for 3‐ and 5‐year OS were 0.717, 0.720 in the testing set and 0.744, 0.699 in the external testing cohort, respectively. The calibration plots presented satisfying accuracy. The derivative risk stratification strategy classified patients into distinct survival subgroups successfully and performed better than the traditional TNM staging. CONCLUSIONS: The nomogram incorporating EGFR mutation status could facilitate survival prediction and risk stratification for individual stage III NSCLC, providing information for enhanced immunotherapy decision and future trial design.
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spelling pubmed-88073292022-02-04 Development and validation of a prediction model using molecular marker for long‐term survival in unresectable stage III non‐small cell lung cancer treated with chemoradiotherapy Yang, Yufan Zhang, Tao Zhou, Zongmei Liang, Jun Chen, Dongfu Feng, Qinfu Xiao, Zefen Hui, Zhouguang Lv, Jima Deng, Lei Wang, Xin Wang, Wenqing Wang, Jianyang Liu, Wenyang Zhai, Yirui Wang, Jie Bi, Nan Wang, Luhua Thorac Cancer Original Articles BACKGROUND: This study aimed to establish a predictive nomogram integrating epidermal growth factor receptor (EGFR) mutation status for 3‐ and 5‐year overall survival (OS) in unresectable/inoperable stage III non‐small cell lung cancer (NSCLC) treated with definitive chemoradiotherapy. METHODS: A total of 533 stage III NSCLC patients receiving chemoradiotherapy from 2013 to 2017 in our institution were included and divided into training and testing sets (2:1). Significant factors impacting OS were identified in the training set and integrated into the nomogram based on Cox proportional hazards regression. The model was subject to bootstrap internal validation and external validation within the testing set and an independent cohort from a phase III trial. The accuracy and discriminative capacity of the model were examined by calibration plots, C‐indexes and risk stratifications. RESULTS: The final multivariate model incorporated sex, smoking history, histology (including EGFR mutation status), TNM stage, planning target volume, chemotherapy sequence and radiation pneumonitis grade. The bootstrapped C‐indexes in the training set were 0.688, 0.710 for the 3‐ and 5‐year OS. For external validation, C‐indexes for 3‐ and 5‐year OS were 0.717, 0.720 in the testing set and 0.744, 0.699 in the external testing cohort, respectively. The calibration plots presented satisfying accuracy. The derivative risk stratification strategy classified patients into distinct survival subgroups successfully and performed better than the traditional TNM staging. CONCLUSIONS: The nomogram incorporating EGFR mutation status could facilitate survival prediction and risk stratification for individual stage III NSCLC, providing information for enhanced immunotherapy decision and future trial design. John Wiley & Sons Australia, Ltd 2021-12-19 2022-02 /pmc/articles/PMC8807329/ /pubmed/34927371 http://dx.doi.org/10.1111/1759-7714.14218 Text en © 2021 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, 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 Original Articles
Yang, Yufan
Zhang, Tao
Zhou, Zongmei
Liang, Jun
Chen, Dongfu
Feng, Qinfu
Xiao, Zefen
Hui, Zhouguang
Lv, Jima
Deng, Lei
Wang, Xin
Wang, Wenqing
Wang, Jianyang
Liu, Wenyang
Zhai, Yirui
Wang, Jie
Bi, Nan
Wang, Luhua
Development and validation of a prediction model using molecular marker for long‐term survival in unresectable stage III non‐small cell lung cancer treated with chemoradiotherapy
title Development and validation of a prediction model using molecular marker for long‐term survival in unresectable stage III non‐small cell lung cancer treated with chemoradiotherapy
title_full Development and validation of a prediction model using molecular marker for long‐term survival in unresectable stage III non‐small cell lung cancer treated with chemoradiotherapy
title_fullStr Development and validation of a prediction model using molecular marker for long‐term survival in unresectable stage III non‐small cell lung cancer treated with chemoradiotherapy
title_full_unstemmed Development and validation of a prediction model using molecular marker for long‐term survival in unresectable stage III non‐small cell lung cancer treated with chemoradiotherapy
title_short Development and validation of a prediction model using molecular marker for long‐term survival in unresectable stage III non‐small cell lung cancer treated with chemoradiotherapy
title_sort development and validation of a prediction model using molecular marker for long‐term survival in unresectable stage iii non‐small cell lung cancer treated with chemoradiotherapy
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8807329/
https://www.ncbi.nlm.nih.gov/pubmed/34927371
http://dx.doi.org/10.1111/1759-7714.14218
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