Literature DB >> 32220701

Lyman-Kutcher-Burman normal tissue complication probability modeling for radiation-induced esophagitis in non-small cell lung cancer patients receiving proton radiotherapy.

Zeming Wang1, Mei Chen2, Jian Sun3, Shengpeng Jiang4, Li Wang5, Xiaochun Wang1, Narayan Sahoo1, G Brandon Gunn6, Steven J Frank6, Quynh-Nhu Nguyen6, Zhongxing Liao6, Joe Y Chang6, X Ronald Zhu1, Xiaodong Zhang7.   

Abstract

PURPOSE: 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).
MATERIAL AND METHODS: 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 TD50) were determined using maximum likelihood estimation. Overall performance of the model was quantified by Nagelkerke's R2 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.
RESULTS: 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 TD50 = 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.
CONCLUSION: 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.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Lyman–Kutcher–Burman model; Non–small cell lung cancer; Normal tissue complication probability; Passive-scattering proton therapy; Radiation-induced esophagitis

Mesh:

Substances:

Year:  2020        PMID: 32220701     DOI: 10.1016/j.radonc.2020.03.003

Source DB:  PubMed          Journal:  Radiother Oncol        ISSN: 0167-8140            Impact factor:   6.280


  8 in total

1.  Predictive performance of different NTCP techniques for radiation-induced esophagitis in NSCLC patients receiving proton radiotherapy.

Authors:  Mei Chen; Zeming Wang; Shengpeng Jiang; Jian Sun; Li Wang; Narayan Sahoo; G Brandon Gunn; Steven J Frank; Cheng Xu; Jiayi Chen; Quynh-Nhu Nguyen; Joe Y Chang; Zhongxing Liao; X Ronald Zhu; Xiaodong Zhang
Journal:  Sci Rep       Date:  2022-06-02       Impact factor: 4.996

2.  Normal tissue complication probability models for prospectively scored late rectal and urinary morbidity after proton therapy of prostate cancer.

Authors:  Jesper Pedersen; Xiaoying Liang; Curtis Bryant; Nancy Mendenhall; Zuofeng Li; Ludvig P Muren
Journal:  Phys Imaging Radiat Oncol       Date:  2021-11-08

3.  Investigating the potential of proton therapy for hypoxia-targeted dose escalation in non-small cell lung cancer.

Authors:  Andreas Köthe; Nicola Bizzocchi; Sairos Safai; Antony John Lomax; Damien Charles Weber; Giovanni Fattori
Journal:  Radiat Oncol       Date:  2021-10-11       Impact factor: 3.481

4.  Radiation-Induced Esophagitis in Non-Small-Cell Lung Cancer Patients: Voxel-Based Analysis and NTCP Modeling.

Authors:  Serena Monti; Ting Xu; Radhe Mohan; Zhongxing Liao; Giuseppe Palma; Laura Cella
Journal:  Cancers (Basel)       Date:  2022-04-05       Impact factor: 6.639

5.  Dosimetric analysis and biological evaluation between proton radiotherapy and photon radiotherapy for the long target of total esophageal squamous cell carcinoma.

Authors:  Yongbin Cui; Yuteng Pan; Zhenjiang Li; Qiang Wu; Jingmin Zou; Dali Han; Yong Yin; Changsheng Ma
Journal:  Front Oncol       Date:  2022-10-03       Impact factor: 5.738

6.  Function-Wise Dual-Omics analysis for radiation pneumonitis prediction in lung cancer patients.

Authors:  Bing Li; Ge Ren; Wei Guo; Jiang Zhang; Sai-Kit Lam; Xiaoli Zheng; Xinzhi Teng; Yunhan Wang; Yang Yang; Qinfu Dan; Lingguang Meng; Zongrui Ma; Chen Cheng; Hongyan Tao; Hongchang Lei; Jing Cai; Hong Ge
Journal:  Front Pharmacol       Date:  2022-09-19       Impact factor: 5.988

7.  Prostate cancer tumour control probability modelling for external beam radiotherapy based on multi-parametric MRI-GTV definition.

Authors:  Ilias Sachpazidis; Panayiotis Mavroidis; Constantinos Zamboglou; Christina Marie Klein; Anca-Ligia Grosu; Dimos Baltas
Journal:  Radiat Oncol       Date:  2020-10-20       Impact factor: 3.481

8.  Substantial Sparing of Organs at Risk with Modern Proton Therapy in Lung Cancer, but Altered Breathing Patterns Can Jeopardize Target Coverage.

Authors:  Camilla Grindeland Boer; Kristine Fjellanger; Inger Marie Sandvik; Maren Ugland; Grete May Engeseth; Liv Bolstad Hysing
Journal:  Cancers (Basel)       Date:  2022-03-08       Impact factor: 6.639

  8 in total

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