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A radiomics prognostic scoring system for predicting progression-free survival in patients with stage IV non-small cell lung cancer treated with platinum-based chemotherapy

OBJECTIVE: To develop and validate a radiomics prognostic scoring system (RPSS) for prediction of progression-free survival (PFS) in patients with stage IV non-small cell lung cancer (NSCLC) treated with platinum-based chemotherapy. METHODS: In this retrospective study, four independent cohorts of s...

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Autores principales: He, Lan, Li, Zhenhui, Chen, Xin, Huang, Yanqi, Yan, Lixu, Liang, Changhong, Liu, Zaiyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8580802/
https://www.ncbi.nlm.nih.gov/pubmed/34815633
http://dx.doi.org/10.21147/j.issn.1000-9604.2021.05.06
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author He, Lan
Li, Zhenhui
Chen, Xin
Huang, Yanqi
Yan, Lixu
Liang, Changhong
Liu, Zaiyi
author_facet He, Lan
Li, Zhenhui
Chen, Xin
Huang, Yanqi
Yan, Lixu
Liang, Changhong
Liu, Zaiyi
author_sort He, Lan
collection PubMed
description OBJECTIVE: To develop and validate a radiomics prognostic scoring system (RPSS) for prediction of progression-free survival (PFS) in patients with stage IV non-small cell lung cancer (NSCLC) treated with platinum-based chemotherapy. METHODS: In this retrospective study, four independent cohorts of stage IV NSCLC patients treated with platinum-based chemotherapy were included for model construction and validation (Discovery: n=159; Internal validation: n=156; External validation: n=81, Mutation validation: n=64). First, a total of 1,182 three-dimensional radiomics features were extracted from pre-treatment computed tomography (CT) images of each patient. Then, a radiomics signature was constructed using the least absolute shrinkage and selection operator method (LASSO) penalized Cox regression analysis. Finally, an individualized prognostic scoring system incorporating radiomics signature and clinicopathologic risk factors was proposed for PFS prediction. RESULTS: The established radiomics signature consisting of 16 features showed good discrimination for classifying patients with high-risk and low-risk progression to chemotherapy in all cohorts (All P<0.05). On the multivariable analysis, independent factors for PFS were radiomics signature, performance status (PS), and N stage, which were all selected into construction of RPSS. The RPSS showed significant prognostic performance for predicting PFS in discovery [C-index: 0.772, 95% confidence interval (95% CI): 0.765−0.779], internal validation (C-index: 0.738, 95% CI: 0.730−0.746), external validation (C-index: 0.750, 95% CI: 0.734−0.765), and mutation validation (C-index: 0.739, 95% CI: 0.720−0.758). Decision curve analysis revealed that RPSS significantly outperformed the clinicopathologic-based model in terms of clinical usefulness (All P<0.05). CONCLUSIONS: This study established a radiomics prognostic scoring system as RPSS that can be conveniently used to achieve individualized prediction of PFS probability for stage IV NSCLC patients treated with platinum-based chemotherapy, which holds promise for guiding personalized pre-therapy of stage IV NSCLC.
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spelling pubmed-85808022021-11-22 A radiomics prognostic scoring system for predicting progression-free survival in patients with stage IV non-small cell lung cancer treated with platinum-based chemotherapy He, Lan Li, Zhenhui Chen, Xin Huang, Yanqi Yan, Lixu Liang, Changhong Liu, Zaiyi Chin J Cancer Res Original Article OBJECTIVE: To develop and validate a radiomics prognostic scoring system (RPSS) for prediction of progression-free survival (PFS) in patients with stage IV non-small cell lung cancer (NSCLC) treated with platinum-based chemotherapy. METHODS: In this retrospective study, four independent cohorts of stage IV NSCLC patients treated with platinum-based chemotherapy were included for model construction and validation (Discovery: n=159; Internal validation: n=156; External validation: n=81, Mutation validation: n=64). First, a total of 1,182 three-dimensional radiomics features were extracted from pre-treatment computed tomography (CT) images of each patient. Then, a radiomics signature was constructed using the least absolute shrinkage and selection operator method (LASSO) penalized Cox regression analysis. Finally, an individualized prognostic scoring system incorporating radiomics signature and clinicopathologic risk factors was proposed for PFS prediction. RESULTS: The established radiomics signature consisting of 16 features showed good discrimination for classifying patients with high-risk and low-risk progression to chemotherapy in all cohorts (All P<0.05). On the multivariable analysis, independent factors for PFS were radiomics signature, performance status (PS), and N stage, which were all selected into construction of RPSS. The RPSS showed significant prognostic performance for predicting PFS in discovery [C-index: 0.772, 95% confidence interval (95% CI): 0.765−0.779], internal validation (C-index: 0.738, 95% CI: 0.730−0.746), external validation (C-index: 0.750, 95% CI: 0.734−0.765), and mutation validation (C-index: 0.739, 95% CI: 0.720−0.758). Decision curve analysis revealed that RPSS significantly outperformed the clinicopathologic-based model in terms of clinical usefulness (All P<0.05). CONCLUSIONS: This study established a radiomics prognostic scoring system as RPSS that can be conveniently used to achieve individualized prediction of PFS probability for stage IV NSCLC patients treated with platinum-based chemotherapy, which holds promise for guiding personalized pre-therapy of stage IV NSCLC. AME Publishing Company 2021-10-31 /pmc/articles/PMC8580802/ /pubmed/34815633 http://dx.doi.org/10.21147/j.issn.1000-9604.2021.05.06 Text en Copyright ©2021Chinese Journal of Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-sa/4.0/This work is licensed under a Creative Commons Attribution-Non Commercial-Share Alike 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/ (https://creativecommons.org/licenses/by-nc-sa/4.0/)
spellingShingle Original Article
He, Lan
Li, Zhenhui
Chen, Xin
Huang, Yanqi
Yan, Lixu
Liang, Changhong
Liu, Zaiyi
A radiomics prognostic scoring system for predicting progression-free survival in patients with stage IV non-small cell lung cancer treated with platinum-based chemotherapy
title A radiomics prognostic scoring system for predicting progression-free survival in patients with stage IV non-small cell lung cancer treated with platinum-based chemotherapy
title_full A radiomics prognostic scoring system for predicting progression-free survival in patients with stage IV non-small cell lung cancer treated with platinum-based chemotherapy
title_fullStr A radiomics prognostic scoring system for predicting progression-free survival in patients with stage IV non-small cell lung cancer treated with platinum-based chemotherapy
title_full_unstemmed A radiomics prognostic scoring system for predicting progression-free survival in patients with stage IV non-small cell lung cancer treated with platinum-based chemotherapy
title_short A radiomics prognostic scoring system for predicting progression-free survival in patients with stage IV non-small cell lung cancer treated with platinum-based chemotherapy
title_sort radiomics prognostic scoring system for predicting progression-free survival in patients with stage iv non-small cell lung cancer treated with platinum-based chemotherapy
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8580802/
https://www.ncbi.nlm.nih.gov/pubmed/34815633
http://dx.doi.org/10.21147/j.issn.1000-9604.2021.05.06
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