Integrating radiotherapy-related factors, clinical indicators, individual patient features, and circulating cytokine profiles, notably IL-6 and TGF-β1, into machine-learning-based predictive models may be beneficial for anticipating unfavourable normal tissue responses to radiation in prostate cancer patients [38,39,41]. This evidence concerns the gene TGFB1 and prostate carcinoma.