ArticleFrontiers in oncology2023
Analysis of the risk factors of radiation pneumonitis in patients after radiotherapy for esophageal squamous cell carcinoma.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 4 citations in OpenAlex.
- CT-based radiomics combined with deep learning for predicting radiation pneumonitis in patients with esophageal cancer: a two-center study.Frontiers in oncology · 2026Article
- Predictive nomogram for risk of pulmonary infection in lung cancer patients undergoing radiochemotherapy: development and performance evaluation.American journal of cancer research · 2025Article
- Analysis of risk factors for anastomotic leakage after radical esophagectomy for esophageal squamous cell carcinoma.Frontiers in medicine · 2025Article
- Predictive Value of Simulated CT Radiomics Combined with Ipsilateral Lung Dosimetry Parameters for Radiation Pneumonitis in Patients with Esophageal Cancer: A Machine Learning-Based Retrospective Study.International journal of general medicine · 2024Article
- Identification of biomarkers for tumor regression grade in esophageal squamous cell carcinoma patients after neoadjuvant chemoradiotherapy.Frontiers in oncology · 2024Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
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Abstract
Objective: To predict the risk factors of radiation pneumonitis (RP) in patients with esophageal squamous cell carcinoma (ESCC) who received radiotherapy. Methods: From January 2015 to October 2021, 477 ESCC patients were enrolled and were assessed retrospectively. All these patients received radiotherapy for primary lesions or mediastinal metastatic lymph nodes. Clinical efficacy and adverse events (AEs) were observed. Univariate analysis identified clinical and dosimetric factors associated with the development of RP, and multivariate logistic regression analysis identified independent potential risk factors associated with the development of RP. Nomograms were constructed to predict RP based on the results of multivariate logistic regression analysis. Results: Among the 477 ESCC patients, the incidence of RP was 22.2%, and the incidence of grade 4 or higher RP was 1.5%. Univariate analysis indicated that chronic obstructive pulmonary disease (COPD), pulmonary infection, leucopenia, PTV volume, V5, V20, V30 and MLD affected the occurrence of RP. The multivariate logistic regression analysis indicated that COPD (OR:1.821, 95%CI:1.111-2.985; Conclusion: We have determined the risk factors of RP and grade 4 or higher RP in ESCC patients after radiotherapy. MLD, V20, COPD were independent factors for RP. It was necessary to take measures to reduce or avoid the occurrence of RP for patients with these risk factors at the early stage.
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