医学
肿瘤科
内科学
总体生存率
生存分析
预测模型
估计
梅德林
跟踪(教育)
临床试验
重症监护医学
医学物理学
试验预测值
肿瘤分期
存活率
作者
D. Dudas,T.J. Dilling,H. Jim,I.E.L. Naqa
标识
DOI:10.1016/j.radonc.2026.111441
摘要
Transformer-based survival models that integrate longitudinal PROs significantly enhance prognostic accuracy in SBRT-treated NSCLC patients. Loss of appetite and pain emerged as the most predictive symptoms, followed by overall wellbeing and shortness of breath. These findings suggest that targeted, symptom-focused PROs tracking could streamline clinical implementation and improve survival estimation in routine oncology care.
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