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Li Z, Gong J, Shi L, Li J, Yang Z, Chai G, Lv B, Xiang G, Wang B, Carr SR, Fiorelli A, Shi M, Zhao Y, Zhao L. Clinical-radiomics nomogram for the risk prediction of esophageal fistula in patients with esophageal squamous cell carcinoma treated with intensity-modulated radiation therapy or volumetric-modulated arc therapy. J Thorac Dis 2024; 16:2032-2048. [PMID: 38617757 PMCID: PMC11009608 DOI: 10.21037/jtd-24-191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 03/08/2024] [Indexed: 04/16/2024]
Abstract
Background Esophageal fistula (EF) is a serious adverse event as a result of radiotherapy in patients with esophageal cancer (EC). We aimed to identify the predictive factors and establish a prediction model of EF in patients with esophageal squamous cell carcinoma (ESCC) who underwent intensity-modulated radiation therapy (IMRT) or volumetric-modulated arc therapy (VMAT). Methods Patients with ESCC treated with IMRT or VMAT from January 2013 to December 2020 at Xijing Hospital were retrospectively analyzed. Ultimately, 43 patients with EF and 129 patients without EF were included in the analysis and propensity-score matched in a 1:3 ratio. The clinical characteristics and radiomics features were extracted. Univariate and multivariate stepwise logistic regression analyses were used to determine the risk factors associated with EF. Results The median follow-up time was 24.0 months (range, 1.3-104.9 months), and the median overall survival (OS) was 13.1 months in patients with EF. A total of 1,158 radiomics features were extracted, and eight radiomics features were selected for inclusion into a model for predicting EF, with an area under the receiver operating characteristic curve (AUC) value of 0.794. Multivariate analysis showed that tumor length, tumor volume, T stage, lymphocyte rate (LR), and grade IV esophagus stenosis were related to EF, and the AUC value of clinical model for predicting EF was 0.849. The clinical-radiomics model had the best performance in predicting EF with an AUC value of 0.896. Conclusions The clinical-radiomics nomogram can predict the risk of EF in ESCC patients and is helpful for the individualized treatment of EC.
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Affiliation(s)
- Zhaohui Li
- Department of Radiation Oncology, Xijing Hospital, Air Force Medical University, Xi’an, China
| | - Jie Gong
- Department of Radiation Oncology, Xijing Hospital, Air Force Medical University, Xi’an, China
| | - Liu Shi
- Department of Radiation Oncology, Xijing Hospital, Air Force Medical University, Xi’an, China
| | - Jie Li
- Department of Radiation Oncology, Xijing Hospital, Air Force Medical University, Xi’an, China
| | - Zhi Yang
- Department of Radiation Oncology, Xijing Hospital, Air Force Medical University, Xi’an, China
| | - Guangjin Chai
- Department of Radiation Oncology, Xijing Hospital, Air Force Medical University, Xi’an, China
| | - Bo Lv
- Department of Radiation Oncology, Xijing Hospital, Air Force Medical University, Xi’an, China
| | - Geng Xiang
- Department of Radiation Oncology, Xijing Hospital, Air Force Medical University, Xi’an, China
| | - Bin Wang
- Department of Radiation Oncology, Xijing Hospital, Air Force Medical University, Xi’an, China
| | - Shamus R. Carr
- Thoracic Surgery Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Alfonso Fiorelli
- Thoracic Surgery Unit, University of Campania “Luigi Vanvitelli”, Naples, Italy
| | - Mei Shi
- Department of Radiation Oncology, Xijing Hospital, Air Force Medical University, Xi’an, China
| | - Yilin Zhao
- Department of Clinical Oncology, Xijing Hospital, Air Force Medical University, Xi’an, China
| | - Lina Zhao
- Department of Radiation Oncology, Xijing Hospital, Air Force Medical University, Xi’an, China
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