用基于身体组成特征的预测模型确定头部和部状细胞癌患者治疗放射治疗的个性化预后:引入概率计算器
Saeed Mohammadzadeh1,2, Alisa Mohebbi1,2, Fatemeh Asli1,2
1Universal Scientific Education and Research Network (USERN), Tehran, Iran.
Journal of imaging informatics in medicine
|November 11, 2025
概括
这项研究开发了一个使用成像和临床数据预测模型,以预测头部和部状细胞癌 (HNSCC) 的预后. 该模型准确预测患者的生存率和复发率,有助于个性化HNSCC管理.
科学领域:
- 在瘤学瘤学.
- 辐射疗法 辐射疗法
- 医疗成像医学成像
背景情况:
- 预测头部和部状细胞癌 (HNSCC) 的预后仍然具有挑战性.
- 放射治疗是HNSCC的主要治疗方式.
- 准确的预后模型对于个性化患者管理至关重要.
研究的目的:
- 开发和内部验证HNSCC患者预后的预测模型.
- 整合成像发现和临床数据,以提高预测准确度.
- 为预测生存,复发和HNSCC特异性死亡率提供一个工具.
主要方法:
- 对215名接受放射治疗的HNSCC患者的回顾性分析.
- 使用了放射治疗前后的腹部CT或PET/CT扫描.
- 采用了考克斯回归,引导/杰克-Knife验证,校准,决策曲线和ROC分析.
主要成果:
- 确定了年龄,放射治疗前和后的骨肌肉指数 (SMI) 作为主要预测因素.
- 实现了高预测性表现,曲线下的面积 (AUC) 值为生存率为0.867,复发率为0.758,HNSCC特异性死亡率为0.747.
- 在各种结果概率级别中表现出良好的校准和实用性.
结论:
- 综合成像临床模型有效预测HNSCC患者的结果.
- 该模型显示了改善个性化HNSCC治疗策略的潜力.
- 进一步应用可能会增强患者管理和治疗决策.
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