基于环境暴露因素的系统性红斑狼发病风险预测模型的开发
Ying Zhang1,2,3,4, Cheng Zhao2,3,4,5, Yu Lei2,3,4,5
1Department of Epidemiology and Biostatistics, Nanjing Medical University, Nanjing, China.
Lupus science & medicine
|November 21, 2024
概括
这项研究通过分析职业和环境因素,开发了一种针对系统性红斑狼 (SLE) 的新型预测模型. 森林MDG模型及其动态名录为预测SLE风险提供了一个用户友好的工具.
科学领域:
- 免疫学 免疫学 免疫学
- 环境健康 环境健康
- 生物统计学 生物统计学
背景情况:
- 系统性红斑狼 (SLE) 是一种复杂的自身免疫性疾病,受遗传和环境因素的影响.
- 现有的SLE预测模型往往缺乏全面整合职业和生活环境暴露.
- 了解这些环境影响对于早期干预和改善患者治疗结果至关重要.
研究的目的:
- 为SLE构建一个预测模型,将职业和生活环境暴露纳入其中.
- 开发一个用户友好的工具来评估SLE发病的相对风险.
- 促进更早,更有针对性的干预措施,对个体有SLE风险.
主要方法:
- 一项涉及316名SLE患者和851名健康志愿者的病例控制研究.
- 数据收集包括基本信息,职业史和环境暴露数据.
- 使用多变量逻辑回归构建了四种预测模型,并使用70/30分割,ROC曲线,校准和决策曲线进行验证.
主要成果:
- 森林MDG模型表现出强大的预测性能,训练组的AUC为0.903,验证组的AUC为0.851.
- 该模型显示出极好的准确性 (0.8338),通过留下一个缺失交叉验证证实.
- 为了实际的临床应用,创建了一个动态的nomogram,可以在线访问.
结论:
- 一个用户友好的动态名录已被开发用于预测SLE发病风险.
- 该模型有效地整合了职业和生活环境暴露.
- 这种工具可以帮助早期识别和管理SLE风险.
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