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ORIGINAL RESEARCH article

Front. Oncol.
Sec. Radiation Oncology
Volume 14 - 2024 | doi: 10.3389/fonc.2024.1490348
This article is part of the Research Topic Cancer Immunity and Radiotherapy View all articles

Radiomic and Dosimetric Parameter-based Nomogram Predicts Radiation Esophagitis in Patients with Non-Small Cell Lung Cancer Undergoing Combined Immunotherapy and Radiotherapy

Provisionally accepted
Kang Wang Kang Wang 1Junfeng Zhao Junfeng Zhao 1Jinghao Duan Jinghao Duan 1Changxing Feng Changxing Feng 1Ying Li Ying Li 2Li Li Li Li 1Shuanghu Yuan Shuanghu Yuan 1,3*
  • 1 Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, and Shandong Academy of Medical Sciences, Jinan, Shandong, China., Jinan, Shandong, China
  • 2 Department of Medical Oncology, Shandong Cancer Hospital, Shandong University, Jinan, Shandong Province, China
  • 3 Department of Radiation Oncology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China., Hefei, Anhui, China

The final, formatted version of the article will be published soon.

    Background: The combination of immune checkpoint inhibitors (ICIs) and radiotherapy (RT) may increase the risk of radiation esophagitis (RE). This study aimed to establish and validate a new nomogram to predict RE in patients with non-small cell lung cancer (NSCLC) undergoing immunochemotherapy followed by RT (ICI-RT). Methods: The 102 eligible patients with NSCLC treated with ICI-RT were divided into training (n = 71) and validation (n = 31) cohorts. Clinicopathologic features, dosimetric parameters, inflammatory markers, and radiomic score (Radscore) were included in the univariate logistic regression analysis, and factors with p < 0.05 in the univariate analysis were included in the multivariate logistic regression analysis. Factors with significant predictive values were obtained and used for developing the nomogram. The area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve were used to validate the model. Results: A total of 38 (37.3%) patients developed RE. Univariate and multivariate analyses identified the following independent predictors of RE: a maximum dose delivered to the esophagus >58.4 Gy, a mean esophagus dose >13.3 Gy, and the Rad-score. The AUCs of the nomogram in the training and validation cohorts were 0.918 (95% confidence interval[CI]: 0.824-1.000) and 0.833 (95% CI: 0.697-0.969), respectively, indicating good discrimination.The calibration curves showed good agreement between the predicted occurrence of RE and the actual observations. The decision curve showed a satisfactory positive net benefit at most threshold probabilities, suggesting a good clinical effect. Conclusions: We developed and validated a nomogram based on imaging histological features and RT dosimetric parameters. This model can effectively predict the occurrence of RE in patients with NSCLC treated using ICI-RT.

    Keywords: Radiation esophagitis, non-small-cell lung cancer, Radiomics, Radiotherapy, Immunotherapy

    Received: 03 Sep 2024; Accepted: 03 Dec 2024.

    Copyright: © 2024 Wang, Zhao, Duan, Feng, Li, Li and Yuan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Shuanghu Yuan, Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, and Shandong Academy of Medical Sciences, Jinan, Shandong, China., Jinan, Shandong, China

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