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

Abstract 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 med...

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Autores principales:	Chao Zhu, Jialin Ding, Songping Wang, Qingtao Qiu, Youxin Ji, Linlin Wang
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2021
Materias:	esophageal cancer esophageal fistula prognostic factors radiomics Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
Acceso en línea:	https://doaj.org/article/d55ac551265e49c2a72b7580f2061d4d
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spelling	oai:doaj.org-article:d55ac551265e49c2a72b7580f2061d4d2021-12-02T02:34:55ZDevelopment and validation of a prognostic nomogram for malignant esophageal fistula based on radiomics and clinical factors1759-77141759-770610.1111/1759-7714.14115https://doaj.org/article/d55ac551265e49c2a72b7580f2061d4d2021-12-01T00:00:00Zhttps://doi.org/10.1111/1759-7714.14115https://doaj.org/toc/1759-7706https://doaj.org/toc/1759-7714Abstract 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.Chao ZhuJialin DingSongping WangQingtao QiuYouxin JiLinlin WangWileyarticleesophageal canceresophageal fistulaprognostic factorsradiomicsNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENThoracic Cancer, Vol 12, Iss 23, Pp 3110-3120 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	esophageal cancer esophageal fistula prognostic factors radiomics Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
spellingShingle	esophageal cancer esophageal fistula prognostic factors radiomics Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Chao Zhu Jialin Ding Songping Wang Qingtao Qiu Youxin Ji Linlin Wang Development and validation of a prognostic nomogram for malignant esophageal fistula based on radiomics and clinical factors
description	Abstract 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.
format	article
author	Chao Zhu Jialin Ding Songping Wang Qingtao Qiu Youxin Ji Linlin Wang
author_facet	Chao Zhu Jialin Ding Songping Wang Qingtao Qiu Youxin Ji Linlin Wang
author_sort	Chao Zhu
title	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_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_sort	development and validation of a prognostic nomogram for malignant esophageal fistula based on radiomics and clinical factors
publisher	Wiley
publishDate	2021
url	https://doaj.org/article/d55ac551265e49c2a72b7580f2061d4d
work_keys_str_mv	AT chaozhu developmentandvalidationofaprognosticnomogramformalignantesophagealfistulabasedonradiomicsandclinicalfactors AT jialinding developmentandvalidationofaprognosticnomogramformalignantesophagealfistulabasedonradiomicsandclinicalfactors AT songpingwang developmentandvalidationofaprognosticnomogramformalignantesophagealfistulabasedonradiomicsandclinicalfactors AT qingtaoqiu developmentandvalidationofaprognosticnomogramformalignantesophagealfistulabasedonradiomicsandclinicalfactors AT youxinji developmentandvalidationofaprognosticnomogramformalignantesophagealfistulabasedonradiomicsandclinicalfactors AT linlinwang developmentandvalidationofaprognosticnomogramformalignantesophagealfistulabasedonradiomicsandclinicalfactors
_version_	1718402378550476800

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

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