ArticleFrontiers in oncology2022
Using inflammatory indexes and clinical parameters to predict radiation esophagitis in patients with small-cell lung cancer undergoing chemoradiotherapy.
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 5 papers.
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Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Trial
- An explainable nomogram incorporating systemic inflammatory indicators and radiation esophagitis for risk assessment of radiation pneumonitis in lung cancer.Frontiers in immunology · 2026Article
- Development and validation of a serum inflammatory biomarker-driven machine-learning model for prognostic stratification in surgical limited-stage small cell lung cancer.Translational lung cancer research · 2025Article
- Clinical implications of the serum platelet-to-lymphocyte ratio in the modern radiation oncology era: research update and literature review.Radiation oncology (London, England) · 2024Review
- Clinical impact of first-line PD-1 or PD-L1 inhibitors combined with chemotherapy in extensive-stage small cell lung cancer patients: A real-world multicenter propensity score-matched study.Thoracic cancer · 2023Article
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9 authors at 1 institution in 1 country.
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Abstract
Objective: Radiation esophagitis (RE) is a common adverse effect in small cell lung cancer (SCLC) patients undergoing thoracic radiotherapy. We aim to develop a novel nomogram to predict the acute severe RE (grade≥2) receiving chemoradiation in SCLC patients. Materials and methods: the risk factors were analyzed by logistic regression, and a nomogram was constructed based on multivariate analysis results. The clinical value of the model was evaluated using the area under the receiver operating curve (ROC) curve (AUC), calibration curves, and decision curve analysis (DCA). The correlations of inflammation indexes were assessed using Spearman correlation analysis. Results: Eighty-four of 187 patients (44.9%) developed grade ≥2 RE. Univariate analysis indicated that concurrent chemoradiotherapy (CCRT, p < 0.001), chemotherapy cycle (p = 0.097), system inflammation response index (SIRI, p = 0.048), prognostic-nutrition index (PNI, p = 0.073), platelets-lymphocyte radio (PLR, p = 0.026), platelets-albumin ratio (PAR, p = 0.029) were potential predictors of RE. In multivariate analysis, CCRT [p < 0.001; OR, 3.380; 95% CI, 1.767-6.465], SIRI (p = 0.047; OR, 0.436; 95% CI, 0.192-0.989), and PAR (p = 0.036; OR, 2.907; 95% CI, 1.071-7.891) were independent predictors of grade ≥2 RE. The AUC of nomogram was 0.702 (95% CI, 0.626-0.778), which was greater than each independent predictor (CCRT: 0.645; SIRI: 0.558; PAR: 0.559). Calibration curves showed high coherence between the predicted and actual observation RE, and DCA displayed satisfactory clinical utility. Conclusion: In this study, CCRT, SIRI, and PAR were independent predictors for RE (grade ≥2) in patients with SCLC receiving chemoradiotherapy. We developed and validated a predictive model through these factors. The developed nomogram with superior prediction ability can be used as a quantitative model to predict RE.
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