一个新的模型使用白细胞来区分轻度自主皮质醇分泌和非功能上腺腺瘤
Xin Zhao1, Jiaquan Zhou2, Xiaohong Lyu3
1Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
Scientific reports
|October 9, 2024
概括
使用白细胞参数的新诊断工具可以帮助区分轻度自主皮质醇分泌 (MACS) 和非功能性上腺腺瘤 (NFA). 这种方法简化了对MACS的查,特别是在资源有限的环境中.
科学领域:
- 内分泌学 在内分泌学.
- 在瘤学瘤学.
- 血液学 血液学 血液学
背景情况:
- 轻度自主皮质醇分泌 (MACS) 是上腺瘤的常见原因.
- 目前对MACS的查方法复杂且资源密集.
- 对于MACS,需要更简单的诊断工具.
研究的目的:
- 开发一种诊断工具,使用白细胞相关参数将MACS与非功能性上腺腺瘤 (NFA) 区分开来.
- 评估机器学习 (ML) 和分类和回归树 (CART) 模型在诊断MACS中的有效性.
主要方法:
- 在567名患者身上进行了一项具有倾向性得分匹配的回顾性病例对照研究 (197名MACS,370名NFA).
- 分析了白细胞相关的参数,并使用Youden的J指数和AUC评估了它们的诊断性能.
- ML和CART模型被外部开发和验证.
主要成果:
- 白细胞参数,除了基细胞百分比,在MACS和NFA组之间有显著差异.
- 在训练组中,CART模型实现了高诊断精度 (AUC 0.872,灵敏度95%,特异性75.7%).
- 在外部验证队列中,ML和CART模型都显示出良好的预测准确性.
结论:
- 基于白细胞参数的CART模型可以有效地区分MACS和NFA.
- 这种基于白细胞的模型为MACS查提供了一个有希望的,更简单的方法.
- 开发的诊断工具可以帮助临床医生管理上腺意外瘤.
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