肺癌患者同时患有肺结核的生存预测的炎症营养生物标志物模型
Hongqi Zhou1, Zihao Zhao2, Jinhai Wang3
1Oncology Department, Guiyang Public Health Treatment Center, Guiyang, China.
Frontiers in molecular biosciences
|August 20, 2025
概括
该研究使用炎症营养标志物开发了肺癌和肺结核患者的新预后模型. 该模型准确预测存活率,并确定针对性干预的高风险个体.
科学领域:
- 癌症学
- 肺病学
- 生物标志物
- 预测模型
背景情况:
- 肺癌和结核病 (TB) 的并发症带来了独特的预后挑战.
- 现有的预后模型不能充分解决这种特定的患者群体.
- 炎症和营养标志物在预测各种疾病的结果方面具有潜力.
研究的目的:
- 开发和验证肺癌和结核病患者的多维预后模型.
- 在这个群体中评估八种炎症营养生物标志物的预后价值.
- 为风险分层提供一个工具,并指导潜在的干预措施.
主要方法:
- 对100名肺癌和结核病患者进行了回顾性研究.
- 使用八种炎症营养标志物 (NLR,PLR,SII,LMR,PNI,HALP,HRR,ALB/GLB) 作为预测剂.
- 使用LASSO回归来选择特征和Cox比例危险模型进行生存分析.
- 通过ROC曲线,C指数和校准图表与引导重新采样来评估模型性能.
主要成果:
- 最后一个模型包括糖尿病,ECOG PS,NLR,PNI,HRR和RDW.
- ECOG PS被确定为一个独立的预后因素 (HR = 1.76, p = 0. 04).
- 诺米图表显示出良好的性能 (C指数=0.71) 和优异的校准.
- 一个高风险小组 (ECOG PS ≥2和NLR>8) 显示了接近零的5年生存率.
- 在 ECOG PS 和 NLR 之间发现了显著的相互作用 (p = 0. 032).
结论:
- 这是首个结合肺癌和结核病患者的炎症营养标志物的验证预后模型.
- 该模型作为个体风险分层的定量工具.
- 这些发现支持对高风险患者进行营养干预.
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