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Development and validation of a prognostic nomogram for malignant esophageal fistula based on radiomics and clinical factors

BACKGROUND: The current study aimed to comprehensively analyze the clinical prognostic factors of malignant esophageal fistula (MEF). Furthermore, this study sought to establish and validate prognostic nomograms incorporating radiomics and clinical factors to predict overall survival and median surv...

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Autores principales: Zhu, Chao, Ding, Jialin, Wang, Songping, Qiu, Qingtao, Ji, Youxin, Wang, Linlin
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/PMC8636210/
https://www.ncbi.nlm.nih.gov/pubmed/34647417
http://dx.doi.org/10.1111/1759-7714.14115
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author Zhu, Chao
Ding, Jialin
Wang, Songping
Qiu, Qingtao
Ji, Youxin
Wang, Linlin
author_facet Zhu, Chao
Ding, Jialin
Wang, Songping
Qiu, Qingtao
Ji, Youxin
Wang, Linlin
author_sort Zhu, Chao
collection PubMed
description BACKGROUND: The current study aimed to comprehensively analyze the clinical prognostic factors of malignant esophageal fistula (MEF). Furthermore, this study sought to establish and validate prognostic nomograms incorporating radiomics and clinical factors to predict overall survival and median survival after fistula for patients with MEF. METHODS: The records of 76 patients with MEF were retrospectively analyzed. A stepwise Cox proportional hazards regression model was employed to screen independent prognostic factors and develop clinical nomograms. Radiomic features were extracted from prefistula CT images and post fistula CT images. Least absolute shrinkage and selection operator (LASSO) regression and Cox regression algorithm was used to filter radiomic features and avoid overfitting. Radiomic signature was a linear combination of optimal features and corresponding coefficients. The joint prognostic nomograms was constructed by radiomic signatures and clinical features. All models were validated by Harrell's concordance index (C‐index), caliberation and bootstrap validation. RESULTS: For overall survival, age, prealbumin, KPS and interval between diagnosis of esophageal cancer and fistula were identified as independent prognostic factors and incorporated into the clinical nomogram. Age, prealbumin, serum albumin, KPS and neutrophil proportion were selected for the clinical nomogram of post fistula survival. The C‐index of overall survival nomogram was 0.719 (95% CI: 0.645–0.793) and that was 0.722 (95% CI: 0.653–0.791) in the post fistula survival nomogram. The radiomic signature developed by radiomic features of prefistula CT showed a significant correlation with both overall survival and post fistula survival. The C‐index of joint nomogarm for overall survival and post fistula survival was 0.831 (95% CI: 0.757–0.905) and 0.77 (95% CI: 0.686–0.854), respectively. The calibration curve showed the joint nomograms outperformed the clinical ones. CONCLUSIONS: The study presents nomograms incorporating independent clinical risk factors and radiomic signature to predict the prognosis of MEF. This prognostic classification system has the potential to guide therapeutic decisions for patients with malignant esophageal fistulas.
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spelling pubmed-86362102021-12-08 Development and validation of a prognostic nomogram for malignant esophageal fistula based on radiomics and clinical factors Zhu, Chao Ding, Jialin Wang, Songping Qiu, Qingtao Ji, Youxin Wang, Linlin Thorac Cancer Original Articles BACKGROUND: The current study aimed to comprehensively analyze the clinical prognostic factors of malignant esophageal fistula (MEF). Furthermore, this study sought to establish and validate prognostic nomograms incorporating radiomics and clinical factors to predict overall survival and median survival after fistula for patients with MEF. METHODS: The records of 76 patients with MEF were retrospectively analyzed. A stepwise Cox proportional hazards regression model was employed to screen independent prognostic factors and develop clinical nomograms. Radiomic features were extracted from prefistula CT images and post fistula CT images. Least absolute shrinkage and selection operator (LASSO) regression and Cox regression algorithm was used to filter radiomic features and avoid overfitting. Radiomic signature was a linear combination of optimal features and corresponding coefficients. The joint prognostic nomograms was constructed by radiomic signatures and clinical features. All models were validated by Harrell's concordance index (C‐index), caliberation and bootstrap validation. RESULTS: For overall survival, age, prealbumin, KPS and interval between diagnosis of esophageal cancer and fistula were identified as independent prognostic factors and incorporated into the clinical nomogram. Age, prealbumin, serum albumin, KPS and neutrophil proportion were selected for the clinical nomogram of post fistula survival. The C‐index of overall survival nomogram was 0.719 (95% CI: 0.645–0.793) and that was 0.722 (95% CI: 0.653–0.791) in the post fistula survival nomogram. The radiomic signature developed by radiomic features of prefistula CT showed a significant correlation with both overall survival and post fistula survival. The C‐index of joint nomogarm for overall survival and post fistula survival was 0.831 (95% CI: 0.757–0.905) and 0.77 (95% CI: 0.686–0.854), respectively. The calibration curve showed the joint nomograms outperformed the clinical ones. CONCLUSIONS: The study presents nomograms incorporating independent clinical risk factors and radiomic signature to predict the prognosis of MEF. This prognostic classification system has the potential to guide therapeutic decisions for patients with malignant esophageal fistulas. John Wiley & Sons Australia, Ltd 2021-10-14 2021-12 /pmc/articles/PMC8636210/ /pubmed/34647417 http://dx.doi.org/10.1111/1759-7714.14115 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
Zhu, Chao
Ding, Jialin
Wang, Songping
Qiu, Qingtao
Ji, Youxin
Wang, Linlin
Development and validation of a prognostic nomogram for malignant esophageal fistula based on radiomics and clinical factors
title Development and validation of a prognostic nomogram for malignant esophageal fistula based on radiomics and clinical factors
title_full Development and validation of a prognostic nomogram for malignant esophageal fistula based on radiomics and clinical factors
title_fullStr Development and validation of a prognostic nomogram for malignant esophageal fistula based on radiomics and clinical factors
title_full_unstemmed Development and validation of a prognostic nomogram for malignant esophageal fistula based on radiomics and clinical factors
title_short Development and validation of a prognostic nomogram for malignant esophageal fistula based on radiomics and clinical factors
title_sort development and validation of a prognostic nomogram for malignant esophageal fistula based on radiomics and clinical factors
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8636210/
https://www.ncbi.nlm.nih.gov/pubmed/34647417
http://dx.doi.org/10.1111/1759-7714.14115
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