基于手术前营养-炎症评分的模型,用于预测结肠直肠癌患者的粘膜皮质分离
Jie Yuan1,2, Yali Hu3, Jiaying Wang3
1Department of Health Management, Beidaihe Rest and Recuperation Center for PLA Joint Logistics Support Force, Qinhuangdao, 066000, China.
Scientific reports
|August 24, 2025
概括
这项研究开发了一种预测模型,使用手术前的营养-炎症标志物来识别结直肠癌手术后具有粘膜皮肤分离 (MCS) 高风险的患者,从而改善早期并发症预测.
科学领域:
- 癌症学
- 手术并发症
- 生物标志物
背景情况:
- 粘膜皮质分离 (MCS) 是结直肠癌 (CRC) 手术后的一个常见并发症.
- 在手术前预测MCS风险可以有助于患者的治疗和结果.
研究的目的:
- 评估手术前营养-炎症标志物的CRC手术后MCS预测能力.
- 开发和验证一种新的MCS风险预测模型.
主要方法:
- 对内部和外部CRC患者的临床数据进行回顾性分析.
- 使用逻辑回归的营养-炎症评分 (NIS) 和名录模型的开发.
- 使用ROC曲线,校准曲线和决策曲线分析 (DCA) 验证模型.
主要成果:
- 包括GLR,SII和PNI在内的营养-炎症评分 (NIS) 显示出良好的预测值 (AUC=0. 752).
- 年龄,终端口腔,和NIS (≥3) 被确定为MCS的独立风险因素.
- 在训练和验证队列中,诺米克模型实现了高AUC (0. 850- 0. 909),显示出良好的校准和临床效用.
结论:
- 一个整合年龄,终端口腔和NIS的手术前诺莫格拉姆模型准确地预测了CRC患者的MCS风险.
- 这种模型在预测术后MCS和指导患者护理方面具有有前途的临床应用.
- 预测模型的风险得分与MCS愈合时间,住院时间和化疗间隔相关.
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