ArticleAdvances in radiation oncology2026
Relative Biological Effectiveness of Carbon Ion Versus Photon Radiation Therapy for Acute Radiation-Induced Esophagitis in Locally Advanced Non-small Cell Lung Cancer Derived From Normal Tissue Complication Probability Modeling.
Article in Advances in radiation oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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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Authors and funding
13 authors.
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Abstract
Purpose: This study aimed to evaluate the relative biological effectiveness (RBE) of carbon-ion radiation therapy (CIRT) versus photon radiation therapy for acute radiation-induced esophagitis (ARIE) in patients with locally advanced non-small cell lung cancer, based on TD₅₀ derived from normal tissue complication probability (NTCP) models. Methods and Materials: A total of 165 propensity score-matched pairs of patients with locally advanced non-small cell lung cancer treated with CIRT or photon radiation therapy between January 2016 and December 2023 were analyzed. ARIE (grade ≥2, National Cancer Institute Common Terminology Criteria for Adverse Events v5.0) during or within 3 months postradiation therapy was the primary endpoint. The Lyman-Kutcher-Burman (LKB) NTCP model was developed using maximum-likelihood estimation. Model performance was assessed via 3-fold cross-validation and area under the receiver operating characteristic curve. The estimated RBE value was the TD₅₀ ratio between the photon radiation therapy and CIRT groups. Results: Grade ≥2 ARIE was observed in 6.7% of patients treated with CIRT and 19.4% of those treated with photons ( Conclusions: LKB-based NTCP modeling offers a clinically oriented framework to estimate RBE value for CIRT. Larger patient cohorts and external validation are required to enhance the model's generalizability and clinical applicability.
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