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多发性硬化症子组:基于患者报告的结果和大量临床样本的数据驱动集群

Alessandro S De Nadai¹, Ryan J Zamora¹, Alyse Finch¹

¹McLean Hospital, Harvard Medical School, Belmont, MA, USA.

Multiple sclerosis (Houndmills, Basingstoke, England)

|October 18, 2024

概括

这项研究使用患者报告的结果确定了九种不同的多发性硬化症 (MS) 亚型,揭示了各种症状模式,并使MS护理的个性化医疗方法成为可能.

科学领域:

神经学神经学
临床研究临床研究
数据科学数据科学数据科学

背景情况:

多发性硬化症 (MS) 的标准临床评估在捕捉患者体验和症状多样性方面存在局限性.
患者的观点和个体症状变化对于综合性多发性硬化症护理至关重要.

研究的目的:

根据患者报告的身体,认知和情绪症状的结果 (PROs) 确定MS (PwMS) 患者的子组.
将这些基于PRO的子组与人口统计,临床和神经性能数据相关联.

主要方法:

在来自6,619名参与者的大量PRO数据集上使用隐性个人资料分析 (LPA).
使用横截面研究设计来分析症状模式.

主要成果:

确定了9种不同的多发性硬化症亚型,其特征是PRO模式.
亚型主要分为低,中等和高移动障碍类别.
观察到意想不到的模式,包括在一些具有低非移动性症状的子组中高移动性障碍.

结论:

通过整合PRO和数据驱动方法,突出了在MS中精准医学的潜力.
基于PRO的分组提供了一种具有成本效益的个性化方法来表征MS症状.
这些发现可以为临床实践提供信息,并指导多发性硬化症的未来研究.

关键词:

多发性硬化症 (MS) 是一种疾病.在健康方面存在差异.隐性个人资料分析 (LPA)患者报告的结果 (PROs).

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