Modeling Time-Dependent Recovery to Improve Esophagitis Prediction in Thoracic Reirradiation
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Le résumé fourni par la source
PURPOSE: In reirradiation, tumor control must be balanced against a high-risk of adverse effects. We evaluated the feasibility of a time-dependent recovery model to improve toxicity prediction. METHODS AND MATERIALS: Sixty-five high-risk thoracic reirradiation patients, identified by BID treatment, were included for modeling grade ≥2 acute esophagitis. The median (range) re-RT dose was 45 Gy (30-60) in 30 (20-40) fractions. Doses from each course were deformably registered to the most recent CT and converted to voxel-wise equivalent dose in 2-Gy fractions. We compared the discrimination of the last course dose, conventional direct accumulation without time consideration, and 3 time-dependent recovery models-mono-exponential, bi-exponential, and reciprocal time-each optimized via grid search with nested 5-fold cross-validation. Logistic regression with bootstrapping was used to assess the predictive value of mean and maximum dose. AUCs were compared using a bootstrap test. Covariates (age, chemotherapy, smoking status, and history of esophagitis from a previous course of thoracic radiation therapy) were also evaluated. RESULTS: After BID re-RT, 26.2% (17/65) of patients experienced grade ≥2 esophagitis. Incorporating time-dependent repair algorithms achieved a higher AUC than the last course dose and direct accumulation. The bi-exponential model incorporating history of prior esophagitis achieved the highest performance (mean dose AUC: 0.83 [95% CI, 0.70-0.94] vs direct accumulation: 0.74 [0.61-0.87], P = .040; maximum dose AUC: 0.78 [0.65-0.89] vs 0.67 [0.54-0.80], P = .015). CONCLUSIONS: Incorporating time-dependent recovery into dose accumulation is feasible, and our findings support its potential use over direct accumulation for more accurate toxicity prediction. These findings will pave the way for developing advanced outcome models for evidence-based reirradiation, ultimately reducing toxicity and optimizing doses for personalized and effective reirradiation.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Modeling Time-Dependent Recovery to Improve Esophagitis Prediction in Thoracic Reirradiation
- Date Crossref
- 01/07/2026
- Éditeur
- Elsevier BV
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Johns Hopkins University Department of Radiation Oncology and Molecular Radiation Sciences pays non établi dans la noticeUniversité ou école supérieure
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Johns Hopkins Medicine pays non établi dans la noticeÉtablissement de santé
Department of Radiation Oncology and Molecular Radiation Sciences — Johns Hopkins University et Johns Hopkins Medicine.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.