ArticleFrontiers in oncology2022
Incorporation of PET Metabolic Parameters With Clinical Features Into a Predictive Model for Radiotherapy-Related Esophageal Fistula in Esophageal Squamous Cell Carcinoma.
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 1 citations in OpenAlex.
- The Predictive Value of Radiomics for Esophagotracheal Fistula after Radiotherapy in Esophageal Cancer.Current medical imaging · 2026Article
- Risk Factors of Esophageal Fistula Associated with Volumetric Modulated Arc Therapy for Esophageal Squamous Cell Cancer.International journal of general medicine · 2024Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To determine whether the addition of metabolic parameters from fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography ( Methods and Materials: Anonymized data from 185 ESCC patients (20 radiotherapy-related EF-positive cases) were collected, including pre-therapy PET/CT scans and EF status. In total, 29 clinical features and 15 metabolic parameters from PET/CT were included in the analysis, and a least absolute shrinkage and selection operator logistic regression model was used to construct a risk score (RS) system. The predictive capabilities of the models were compared using receiver operating characteristic (ROC) curves. Results: In univariate analysis, metabolic tumor volume (MTV)_40% was a risk factor for radiotherapy (RT)-related EF, with an odds ratio (OR) of 1.036 [95% confidence interval (CI): 1.009-1.063, Conclusions: MTV_40% was a risk factor for RT-related EF in univariate analysis and was screened out using multivariate logistic regression. A model with clinical features can predict RT-related EF.
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