一个实用的在线动态诺摩图,用于预测鼻癌的无进展生存率
Jiayan Zhang1,2, Jiayi Yu1, Dan Zhang1
1Department of Radiology, Chongqing General Hospital, Chongqing, China.
概括
在线动态诺米图准确预测鼻癌 (NPC) 患者的无进展生存期 (PFS). 这种工具使用明显扩散系数 (ADC),外瘤扩散 (ENS) 和淋巴细胞与单细胞的比率 (LMR),优于传统的TNM分期.
科学领域:
- 在瘤学瘤学.
- 放射学 放射学是指放射学
- 生物统计学 生物统计学
背景情况:
- 鼻癌 (NPC) 的预后仍然具有挑战性.
- 现有的分期系统可能无法完全捕捉个体患者的风险.
- 需要准确的工具来指导治疗和改善患者的治疗结果.
研究的目的:
- 开发和验证在NPC中预测无进展生存率 (PFS) 的在线动态名谱.
- 在NPC患者中确定PFS的独立预后因素.
- 为了比较名图的预测性能与AJCC第八届TNM分期系统.
主要方法:
- 从106名NPC患者的临床和成像数据的回顾性分析.
- 单变量和多变量考克斯回归以确定预后因素 (ADC,ENS,LMR).
- 使用C指数,校准曲线和决策曲线分析 (DCA) 来构建和验证名图.
主要成果:
- 鉴定了ADC,ENS和LMR作为NPCPFS的独立预后因素 (p <0.05).
- 诺米图表显示了有利的预测性能 (C指数=0.795) 和AUCs (0.792-0.849).
- 诺米图显著超过了AJCC第八届TNM分期系统 (AUCs = 0.543-0.592).
结论:
- 一个在线的动态名录集ADC,ENS和LMR有效地预测NPC中的PFS.
- 诺米图准确地将患者分为不同的风险组.
- 与当前的TNM分阶段系统相比,该工具提供了更高的预测效率.
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