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Das, S.K., Zhou, S., Zhang, J., et al. (2007) Predicting Lung Radiotherapy-Induced Pneumonitis Using a Model Combining Parametric Lyman Probit with Nonparametric Decision Trees. International Journal of Radiation Oncology, Biology, Physics, 68, 1212-1221.
https://doi.org/10.1016/j.ijrobp.2007.03.064

has been cited by the following article:

• TITLE: Biomarkers Associated with Radiation-Induced Lung Injury in Cancer Patients

  AUTHORS: Yuan-Yuan Chen, Dong-Xu Ao, Chen-Yang Zuo, Jun Cai

  KEYWORDS: Radiation Induced Lung Injury, RILI, Fibrosis, Biomarkers

  JOURNAL NAME: Journal of Biosciences and Medicines, Vol.11 No.10, October 27, 2023

  ABSTRACT: Radiotherapy (RT) is a common and effective non-surgical treatment for thoracic solid tumors, and radiation-induced lung injury (RILI) is the most common side effect of radiotherapy. Even if RT is effective in the treatment of cancer patients, severe radiation pneumonitis (RP) or pulmonary fibrosis (PF) can reduce the quality of life of patients and may even lead to serious consequences of death. Therefore, how to overcome the problem of accurate prediction and early diagnosis of RT for pulmonary toxicity is very important. This review summarizes the related factors of RILI and the related biomarkers for early prediction of RILI.