估计长度测量持续疾病进展的终点,以阿尔茨海默病为例
Haoyan Hu1, Miroslaw Brys2, Stephen J Ruberg3
1Global Statistical Sciences, Eli Lilly and Company, Indianapolis, IN, 46285, USA. hu_haoyan@lilly.com.
Therapeutic innovation & regulatory science
|July 17, 2025
概括
时间平均测量 (TAM) 提供了比基线变化更直观的阿尔茨海默病终点. 这种方法更好地反映了随时间推移的治疗效益,并有助于患者和临床医生的理解.
科学领域:
- 临床试验 临床试验
- 神经退行性疾病 神经退行性疾病
- 生物统计学 生物统计学
背景情况:
- 目前的阿尔茨海默病临床试验终点,如认知/功能尺度的基线变化,可能无法随着时间的推移完全捕捉治疗效果.
- 这些传统的终点对患者和临床医生来说可能很难直观地理解,特别是考虑到疾病进展率的不同.
研究的目的:
- 探索时间平均测量 (TAM) 作为阿尔茨海默病临床试验的新型终点.
- 建议使用TAM的相对变化来量化治疗差异.
- 在ICH E9 (R1) 估计框架内对传统终点进行TAM评估.
主要方法:
- 根据ICH E9 (R1) 准则,根据处理间流事件和缺失数据的各种策略,定义了估计值.
- 探索时间平均测量 (TAM) 作为一个新的终点.
- 使用相对变化的量化治疗差异.
- 进行了回顾性分析,比较TAM与基线的变化,相对疾病进展模型和疾病进展的斜率.
主要成果:
- 时间平均测量 (TAM) 为阿尔茨海默病试验提供了一个替代的终点.
- 使用TAM的相对变化表明,与传统方法相比,对治疗效果的看法不同.
- 估计策略和归算方法的选择影响了比较结果.
结论:
- 时间平均测量 (TAM) 为阿尔茨海默病研究提供了潜在的更有信息和更易于理解的终点.
- 进一步探索TAM及其在ICH E9 (R1) 指南中的应用是有必要的.
- 这种方法可以改善阿尔茨海默病临床试验中治疗益处的解释.
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