Lyman-Kutcher-Burman normal tissue complication probability modeling for radiation-induced esophagitis in non-small cell lung cancer patients receiving proton radiotherapy.
retrospective_cohort · Level III
Where this comes from
- Record sourced from PubMed, PMID 32220701.
- Also identified by DOI 10.1016/j.radonc.2020.03.003 and PMC identifier 10035357.
- No licence information is recorded for this record.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
To develop and test an Lyman-Kutcher-Burman (LKB) normal tissue complication probability (NTCP) model to predict radiation-induced esophagitis (RE) in non-small cell lung cancer (NSCLC) patients receiving passive-scattering proton therapy (PSPT). We retrospectively reviewed 328 NSCLC patients receiving PSPT at our institution. Esophagitis severity was graded by physicians according to the Common Toxicity Criteria for Adverse Events version 3.0, and the primary endpoint was grade ≥2 RE within 6 months from the first treatment. LKB model parameters (n, m, and TD<sub>50</sub>) were determined using maximum likelihood estimation. Overall performance of the model was quantified by Nagelkerke's R<sup>2</sup> and the scaled Brier score. Discriminative ability was evaluated using the area under the receiver operating curve (AUC), and calibration was assessed with the Hosmer-Lemeshow goodness-of-fit test. Bootstrap internal validation was performed to assess the model uncertainty and generalizability. Grade 2-3 RE was observed in 136 (41.5%) patients, and no grade 4-5 RE was reported. The optimal LKB parameters were: n = 0.24, m = 0.51, and TD<sub>50</sub> = 44.83 Gy (relative biological effectiveness). The optimism-corrected AUC was 0.783, and the Hosmer-Lemeshow test showed significant agreement between predicted and observed morbidity. Bootstrap validation verified that the model was robust to similar future populations. Our LKB NTCP model to predict grade ≥2 RE in NSCLC patients who received PSPT showed good predictive performance and robustness to similar future populations, and a smaller volume effect than the previously observed in photon-treated populations. External validation of the model is warranted.
Medical subject headings
- Carcinoma, Non-Small-Cell Lung
- Esophagitis
- Lung Neoplasms