基于基线数据和炎症和传染性标志物的基础上,构建和验证胃炎患者预后的诺莫格拉姆模型
Lanfang Zhang1, Lu Yang1, Lijun Meng1
1Department of Gastroenterology, The First Affiliated Hospital of Henan Medical University, Xinxiang, China.
Frontiers in medicine
|August 13, 2025
概括
一个新的Nomogram模型有效地预测胃炎预后,使用基线数据,炎症标志物和Helicobacter pylori感染. 该工具帮助临床医生为胃炎患者制定个性化治疗策略.
科学领域:
- 胃肠病学 胃肠病学
- 炎症性疾病 炎症性疾病
- 在瘤学瘤学.
背景情况:
- 胃炎是一种具有恶性进展潜力的全球性炎症性疾病.
- 像OLGA这样的现有分期系统主要关注癌症风险,忽视可修改的因素.
- 炎症标志物和Helicobacter pylori感染至关重要,但在胃炎预后中经常被忽视.
研究的目的:
- 开发和验证Nomogram预测模型用于胃炎预后.
- 将基线数据,炎症标志物和传染病原体纳入模型.
- 在胃炎管理中提供个性化临床治疗决策的工具.
主要方法:
- 从胃炎患者的临床数据的回顾性收集.
- 单变量和多变量分析以确定独立的风险因素.
- 使用C指数,校准曲线和AUC构建和内部验证Nomogram预测模型.
主要成果:
- 诺莫格拉姆模型表现出强大的预测准确性,AUC值为0.808 (训练) 和0.800 (验证).
- 确定的独立风险因素包括饮食评分,中性粒细胞比例,CRP,ESR,血清白蛋白和H. pylori感染.
- 该模型显示了良好的校准,并适合于训练和验证套件.
结论:
- 一个Nomogram模型整合了基线数据,炎症指标和传染病原体,有效地预测了胃炎的预后.
- 这种预测模型可以作为个性化胃炎临床治疗的宝贵参考.
- 这些发现强调了在胃炎管理中考虑可修改因素的重要性.
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