谁从基于互联网的对话参与RCT (I-CONECT) 中受益最多? 个性化医学方法应用于行为干预研究的应用
C-Y Wu1, K Yu, S E Arnold
1Chao-Yi Wu, 149 13th floor, 10-003C, Boston, MA, USA, chwu3@mgh.harvard.edu, 02129; 617-724-2428.
The journal of prevention of Alzheimer's disease
|May 6, 2024
概括
个性化治疗反应分析揭示了影响阿尔茨海默病干预结果的关键因素. 这种方法有助于识别响应者并估计认知衰退的潜在延迟,以更好地设计临床试验.
科学领域:
- 神经科学是一个神经科学.
- 老年学是指老年学的学科.
- 临床心理学 临床心理学
背景情况:
- 阿尔茨海默病 (AD) 临床试验经常由于疾病异质性而失败.
- 个体特征和疾病过程各有不同,影响治疗的有效性.
- 需要一种新的方法来理解差异化治疗效应.
研究的目的:
- 采用个体级治疗响应 (ITR) 方法来识别治疗响应者的特征.
- 通过I-CONECT行为干预来估计认知衰退节省的时间.
- 模拟阿尔茨海默病干预措施治疗效果的异质性.
主要方法:
- 利用了基于互联网的对话参与临床试验 (I-CONECT) 的数据.
- 使用随机森林模型生成全球认知 (MoCA) 和语义流 (CFA) 的ITR分数.
- 使用SHAP和决策树来识别响应者特征和估计节省的时间.
主要成果:
- 对于MoCA观察到治疗反应的实质性异质性,对于CFA观察到的适度.
- 年龄,认知状态,社会参与,教育和个性影响了治疗反应.
- 受访者显示认知能力下降的潜在延迟为3-6个月.
结论:
- ITR分析对于分析治疗响应者和为未来的试验设计提供信息是有价值的.
- 测量认知衰退节省的时间为临床意义提供了洞察力.
- 这种方法可以增强阿尔茨海默病的个性化药物.
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