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A prognostic model for predicting progression-free survival in patients with advanced non-small cell lung cancer after image-guided microwave ablation plus chemotherapy

OBJECTIVES: This study aimed to build and validate a prediction model that can predict progression-free survival (PFS) in patients with advanced non-small cell lung cancer (NSCLC) after image-guided microwave ablation (MWA) plus chemotherapy. METHODS: Data from a previous multi-center randomized con...

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Autores principales: Kong, Fanhao, Yang, Honglan, Wang, Qiaoxia, Wei, Zhigang, Ye, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10598089/
https://www.ncbi.nlm.nih.gov/pubmed/37318606
http://dx.doi.org/10.1007/s00330-023-09804-9
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author Kong, Fanhao
Yang, Honglan
Wang, Qiaoxia
Wei, Zhigang
Ye, Xin
author_facet Kong, Fanhao
Yang, Honglan
Wang, Qiaoxia
Wei, Zhigang
Ye, Xin
author_sort Kong, Fanhao
collection PubMed
description OBJECTIVES: This study aimed to build and validate a prediction model that can predict progression-free survival (PFS) in patients with advanced non-small cell lung cancer (NSCLC) after image-guided microwave ablation (MWA) plus chemotherapy. METHODS: Data from a previous multi-center randomized controlled trial (RCT) was used and assigned to either the training data set or the external validation data set according to the location of the centers. Potential prognostic factors were identified by multivariable analysis in the training data set and used to construct a nomogram. After bootstraps internal and external validation, the predictive performance was evaluated by concordance index (C-index), Brier Score, and calibration curves. Risk group stratification was conducted using the score calculated by the nomogram. Then a simplified scoring system was built to make risk group stratification more convenient. RESULTS: In total, 148 patients (training data set: n = 112; external validation data set: n = 36) were enrolled for analysis. Six potential predictors were identified and entered into the nomogram, including weight loss, histology, clinical TNM stage, clinical N category, tumor location, and tumor size. The C-indexes were 0.77 (95% CI, 0.65–0.88, internal validation) and 0.64 (95% CI, 0.43–0.85, external validation). The survival curves of different risk groups also displayed significant distinction (p < 0.0001). CONCLUSIONS: We found weight loss, histology, clinical TNM stage, clinical N category, tumor location, and tumor size were prognostic factors of progression after receiving MWA plus chemotherapy and constructed a prediction model that can predict PFS. CLINICAL RELEVANCE STATEMENT: The nomogram and scoring system will assist physicians to predict the individualized PFS of their patients and decide whether to perform or terminate MWA and chemotherapy according to the expected benefits. KEY POINTS: • Build and validate a prognostic model using the data from a previous randomized controlled trial to predict progression-free survival after receiving MWA plus chemotherapy. • Weight loss, histology, clinical TNM stage, clinical N category, tumor location, and tumor size were prognostic factors. • The nomogram and scoring system published by the prediction model can be used to assist physicians to make clinical decisions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00330-023-09804-9.
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spelling pubmed-105980892023-10-26 A prognostic model for predicting progression-free survival in patients with advanced non-small cell lung cancer after image-guided microwave ablation plus chemotherapy Kong, Fanhao Yang, Honglan Wang, Qiaoxia Wei, Zhigang Ye, Xin Eur Radiol Oncology OBJECTIVES: This study aimed to build and validate a prediction model that can predict progression-free survival (PFS) in patients with advanced non-small cell lung cancer (NSCLC) after image-guided microwave ablation (MWA) plus chemotherapy. METHODS: Data from a previous multi-center randomized controlled trial (RCT) was used and assigned to either the training data set or the external validation data set according to the location of the centers. Potential prognostic factors were identified by multivariable analysis in the training data set and used to construct a nomogram. After bootstraps internal and external validation, the predictive performance was evaluated by concordance index (C-index), Brier Score, and calibration curves. Risk group stratification was conducted using the score calculated by the nomogram. Then a simplified scoring system was built to make risk group stratification more convenient. RESULTS: In total, 148 patients (training data set: n = 112; external validation data set: n = 36) were enrolled for analysis. Six potential predictors were identified and entered into the nomogram, including weight loss, histology, clinical TNM stage, clinical N category, tumor location, and tumor size. The C-indexes were 0.77 (95% CI, 0.65–0.88, internal validation) and 0.64 (95% CI, 0.43–0.85, external validation). The survival curves of different risk groups also displayed significant distinction (p < 0.0001). CONCLUSIONS: We found weight loss, histology, clinical TNM stage, clinical N category, tumor location, and tumor size were prognostic factors of progression after receiving MWA plus chemotherapy and constructed a prediction model that can predict PFS. CLINICAL RELEVANCE STATEMENT: The nomogram and scoring system will assist physicians to predict the individualized PFS of their patients and decide whether to perform or terminate MWA and chemotherapy according to the expected benefits. KEY POINTS: • Build and validate a prognostic model using the data from a previous randomized controlled trial to predict progression-free survival after receiving MWA plus chemotherapy. • Weight loss, histology, clinical TNM stage, clinical N category, tumor location, and tumor size were prognostic factors. • The nomogram and scoring system published by the prediction model can be used to assist physicians to make clinical decisions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00330-023-09804-9. Springer Berlin Heidelberg 2023-06-15 2023 /pmc/articles/PMC10598089/ /pubmed/37318606 http://dx.doi.org/10.1007/s00330-023-09804-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Oncology
Kong, Fanhao
Yang, Honglan
Wang, Qiaoxia
Wei, Zhigang
Ye, Xin
A prognostic model for predicting progression-free survival in patients with advanced non-small cell lung cancer after image-guided microwave ablation plus chemotherapy
title A prognostic model for predicting progression-free survival in patients with advanced non-small cell lung cancer after image-guided microwave ablation plus chemotherapy
title_full A prognostic model for predicting progression-free survival in patients with advanced non-small cell lung cancer after image-guided microwave ablation plus chemotherapy
title_fullStr A prognostic model for predicting progression-free survival in patients with advanced non-small cell lung cancer after image-guided microwave ablation plus chemotherapy
title_full_unstemmed A prognostic model for predicting progression-free survival in patients with advanced non-small cell lung cancer after image-guided microwave ablation plus chemotherapy
title_short A prognostic model for predicting progression-free survival in patients with advanced non-small cell lung cancer after image-guided microwave ablation plus chemotherapy
title_sort prognostic model for predicting progression-free survival in patients with advanced non-small cell lung cancer after image-guided microwave ablation plus chemotherapy
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10598089/
https://www.ncbi.nlm.nih.gov/pubmed/37318606
http://dx.doi.org/10.1007/s00330-023-09804-9
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