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现型化与败血症个体化绝对风险差异之间的关系:两项多中心试验中两种方法的二次分析
Victor B Talisa1,2, Sachin P Yende1,2,3, Derek C Angus1,2
1Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA.
Critical care explorations
|October 16, 2025
概括
在败血症试验中分组患者可能无法可靠地个性化护理. 个体绝对风险差异 (iARDs) 显示,即使在定义的子组内,治疗反应也存在显著差异,这引发了安全问题.
科学领域:
- 关键护理医学 关键护理医学
- 临床试验设计 临床试验设计
- 生物统计学 生物统计学
背景情况:
- 败血症患者群体对治疗干预的反应是可变的,这使治疗优化变得复杂.
- 目前用于识别毒性临床试验中的差异性治疗反应的方法不足以进行个体患者水平的预测.
研究的目的:
- 探索既有临床和生物分组方法与新型个性化绝对风险差异 (iARD) 模型之间的关系.
- 评估在败血症试验中确定患者子组内的iARDs的变异性.
- 评估分组对个性化败血症治疗的潜力,特别是早期目标导向疗法 (EGDT).
主要方法:
- 对早期败血症休克 (ProCESS) 和澳大利亚复苏性败血症评估 (ARISE) 随机对照试验的第二次分析.
- 临床 (α,β,γ,δ) 和生物 (超炎症,非超炎症) 亚表型应用于患者队列.
- 监督学习模型被用来预测90天死亡率的iARDs,利用临床变量和生物标志物数据.
主要成果:
- EGDT的平均治疗效果在临床和生物分组内各不相同,在一些 (β,非超炎症) 中显示潜在的益处,在其他 (γ,超炎症) 中显示潜在的危害.
- 重要的是,每个子组内预测的iARDs表现出广泛的范围,从显著的危害到相当大的好处.
- 例如,在β亚型中,虽然平均EGDT效应表明死亡率降低了8.5%,但个体预测从29%的死亡率增加到16%的死亡率降低,预计39%的患者会受到伤害.
结论:
- 虽然临床和生物学表型可以确定具有不同平均治疗效果的子组,但在这些组中,风险和益处的显著个体变化仍然存在.
- 这些发现引发了人们对使用当前表型化策略来个性化败血症治疗的可靠性和安全性的担忧.
- 需要进一步的研究来开发更准确的方法来预测毒症的个性化治疗.
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