基于炎症和营养标志物的肺癌总生存风险预测模型
Hongqi Zhou1, Weiyun Jin2, Lindi Li1
1Oncology Department, Guiyang Public Health Treatment Center, Guiyang, China.
Scientific reports
|August 22, 2025
概括
这项研究使用炎症营养生物标志物为临床决策制定了肺癌死亡风险模型. 该模型确定了1年生存预测的关键预测因素,如年龄,阶段和血清白蛋白.
科学领域:
- 癌症学
- 生物标志物
- 预测模型
背景情况:
- 肺癌在全球面临重大健康挑战.
- 准确的死亡率预测对于个性化治疗策略至关重要.
- 炎症营养生物标志物在癌症预后方面具有前景.
研究的目的:
- 开发肺癌死亡率的多维风险预测模型.
- 确定与生存相关的特征性炎症营养生物标志物.
- 为了优化肺癌患者的临床决策.
主要方法:
- 对500名肺癌患者进行了分析.
- 使用LASSO逻辑回归和SVM-RFE进行特征选择和模型开发.
- 对八种炎症营养生物标志物的预后价值进行了评估.
主要成果:
- 年龄,临床阶段,差异化,ECOG PS 0-1,血清白蛋白,淋巴细胞与单细胞比率 (LMR),血红蛋白与红细胞分布宽度比率 (HRR) 和白蛋白与红蛋白比率 (ALB/ GLB) 是独立的预后因素.
- 成功开发了一年肺癌死亡率的预测模型.
- 创建了一个基于网络的计算器,以促进临床应用.
结论:
- 开发的模型有效预测肺癌患者的一年死亡率.
- 关键的炎症营养生物标志物可以提高预后准确性.
- 该工具支持临床决策和个性化治疗计划.
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