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使用机器学习来确定适合Anakinra治疗COVID-19的患者人群,根据紧急使用授权

Qi Liu¹, Raj Nair², Ruihao Huang¹

¹Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.

Clinical pharmacology and therapeutics

|February 13, 2024

概括

一项新的评分规则确定了可能受益于anakinra的住院COVID-19患者,支持其紧急使用授权. 这种方法有助于在suPAR测试不可用时做出治疗决定.

科学领域:

免疫学免疫学免疫学
传染性疾病传染性疾病
计算生物学计算生物学

背景情况:

阿纳金拉被认为是住院COVID-19患者的呼吸衰竭风险.
较高的suPAR水平可以识别可能受益的患者,但该测定方法尚未得到广泛应用.
紧急使用授权 (EUA) 需要可靠的患者选择方法.

研究的目的:

开发和验证临床评分规则,以识别患有升高suPAR水平 (≥6 ng/mL) 的患者.
通过在没有suPAR测定可用的情况下使患者识别成为可能,以支持anakinra的 EUA.

主要方法:

使用机器学习方法,基于SAVEMORE试验数据创建分数规则.
该评分规则是使用SAVE试验数据进行外部验证的.
该规则旨在识别那些在基线可能具有suPAR水平≥6ng/mL的患者.

主要成果:

开发的临床评分规则显示了高的积极预测价值和特异性.
该规则在识别患有升高suPAR的患者时表现出合理的敏感性.
外部验证证实了得分规则的性能.

结论:

临床评分规则有效地识别了住院COVID-19患者可能有升高的suPAR水平.
该工具支持anakinra的 EUA,通过允许适当的患者选择.
评分规则为临床决策提供了对suPAR试验的可行替代方案.

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