预测风险人群的炎症性关节炎:风险分层分数的发展
Laurence Duquenne1, Elizabeth M Hensor1, Michelle Wilson1
1Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, and NIHR Leeds Biomedical Research Centre, Leeds, United Kingdom (L.D., E.M.H., M.W., L.G., J.L.N., K.H., A.D.M., R.C., N.S., K.M., P.E.).
Annals of internal medicine
|July 31, 2023
概括
新的得分可以使用生物标志物预测风险人群的炎症性关节炎 (IA). 这些工具有助于识别那些可能受益于早期干预和预防策略的人.
科学领域:
- 类风湿病学 类风湿病学
- 生物标志物 生物标志物
- 预测分析是一种预测分析.
背景情况:
- 炎症性关节炎 (IA) 是一种与免疫相关的疾病,其特征是突炎.
- 类风湿性关节炎是IA最常见的形式.
研究的目的:
- 在高危人群中开发IA的预测分数.
- 利用多维生物标志物提高预测准确度.
主要方法:
- 一项前性观察队列研究,涉及具有新的肌肉骨症状和阳性抗林蛋白抗体的个体.
- 开发了一个简单的物流回归得分和一个全面的最小绝对收缩和选择操作员Cox回归得分.
- 使用引导和决策曲线分析进行内部验证.
主要成果:
- 32.5%的参与者在研究期间发展了IA.
- 简单的得分识别了低风险的个体,其虚假阴性率为5%.
- 综合评分确定了高风险个体 (29%的错误阳性率),40%的人在1年内发展IA,71%的人在5年内发展IA.
结论:
- 简单的分数可以识别IA风险较低的个体,可能减少对二次护理的需求.
- 综合得分有助于风险分层和识别预防措施的候选人.
- 这两个分数都显示出临床护理和临床试验的前景.
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