在高风险人群中监测胃癌风险的常规血清测试指数小组的开发
Mengmeng Wang1, Zengyan Zong2, Shuyi Wu1
1Department of Clinical Laboratory, the Key Laboratory of Advanced Interdisciplinary Studies Center, the First Affiliated Hospital of Guangzhou Medical University, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, Guangzhou, Guangdong, China.
Annals of clinical and laboratory science
|July 24, 2024
概括
这项研究使用常规血液检查开发了胃癌 (GC) 风险的非侵入性预测模型. 该模型有效地识别了需要进一步调查早期胃癌 (EGC) 的患者.
科学领域:
- 在瘤学瘤学.
- 生物标志物 生物标志物
- 医学诊断 医学诊断 医学诊断
背景情况:
- 胃癌 (GC) 仍然是一个重大的全球健康挑战.
- 早期检测对于改善患者的治疗结果和生存率至关重要.
- 在临床实践中,用于GC风险分层的非侵入性方法非常可取.
研究的目的:
- 使用非侵入性参数开发和验证胃癌 (GC) 风险的预测模型.
- 评估模型在分层患者中的有效性,基于他们患GC的风险.
- 提供一个具有成本效益的工具,用于早期识别高风险的个人GC.
主要方法:
- 一项病例控制研究涉及138名GC患者和319名慢性非缩性胃炎 (CNAG) 患者.
- 从常规血液检查中分析血液学,生物化学和凝血参数.
- 使用随机森林和物流回归的特征选择和模型构建,在R版本 4.2.3.3 中进行统计分析.
主要成果:
- 开发了一个物流回归模型,其中包括D-二元体,癌胚抗原 (CEA),碳水化合物抗原724 (CA724) 和血红蛋白 (HGB).
- 该模型实现了0.8093 (训练组) 和0.8076 (测试组) 的曲线下面面积 (AUC),表明了良好的预测性能.
- 为实时GC风险评估创建了一个视觉名录和一个交互式HTML工具.
结论:
- 开发的非侵入性预测模型足以识别早期胃癌 (EGC) 风险.
- 这个模型为临床应用提供了一个有价值,具有成本效益的工具.
- 该模型可以帮助实施针对GC的有针对性的预防和干预策略.
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