决策树分析作为一种初步的基于证据的工具,用于识别与遗传性复发性发烧和周期性发烧相比,儿童不分化的复发性发烧综合征,口腔炎和腺炎综合征,口腔炎和腺炎综合征
Riccardo Papa1, Francesca Bovis2, Silvia Federici3
1IRCCS Istituto Giannina Gaslini, UOC Reumatologia e Malattie Autoinfiammatorie, Genoa, Italy.
Arthritis & rheumatology (Hoboken, N.J.)
|December 21, 2025
概括
制定基于证据的标准可以对系统性未定义发烧 (SURF) 患者进行分类,将其与遗传性复发性发烧 (HRF) 和周期性发烧,口炎,喉炎和腺炎 (PFAPA) 综合征区分开来. 这些标准有助于为未来的研究形成更均的患者队列.
科学领域:
- 风湿病学和免疫学
- 遗传学和基因组学 遗传学和基因组学
- 临床诊断 临床诊断 临床诊断
背景情况:
- 系统性未定义发烧 (SURF) 患者存在诊断方面的挑战.
- 准确的分类对于有针对性的治疗和研究队列的同质性至关重要.
- 现有的标准可能无法完全区分SURF与其他自身炎症综合征,如遗传性复发性发烧 (HRF) 和周期性发烧,口炎,喉炎和腺炎 (PFAPA).
研究的目的:
- 建立基于证据的标准来分类系统性未定义发烧 (SURF) 患者.
- 为了区分SURF患者与遗传性复发性发烧 (HRF) 和周期性发烧,口炎,喉炎和腺炎 (PFAPA) 综合征.
主要方法:
- 使用112名SURF患者的数据开发了一个决策树模型和一个后勤回归模型.
- 疾病控制组包括具有遗传确认HRF或PFAPA综合征的患者.
- 外部验证对来自四个附加中心的123名患者进行.
主要成果:
- 一个结合临床和遗传数据的决策树模型在识别SURF患者时实现了91%的准确性.
- 使用基因测试进行的后勤回归模型显示准确率为89.2%.
- 决策树模型在外部验证队列中表现出强大的歧视力 (AUC 96.3%).
结论:
- 可以制定基于证据的标准来对SURF患者进行分类,特别是将其与HRF和PFAPA综合征区分开来.
- 这些标准作为一种初步工具,用于在未来的研究中招募更同质的患者队列.
- 结合临床和遗传数据的决策树模型显示了准确的SURF患者分类的巨大潜力.
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