纵向测量和时间到事件结果的联合建模与使用功能主要组件分析的治愈分数
Siyuan Guo1, Jiajia Zhang2, Susan Halabi1
1Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina, USA.
Statistics in medicine
|December 5, 2024
概括
这项研究引入了一种联合建模方法,使用治疗模型中的纵向数据准确估计时间到事件结果. 该方法通过整合重复测量和计算治愈分数来增强生存分析,改善临床试验洞察力.
科学领域:
- 生物统计学 生物统计学
- 临床试验 临床试验
- 生存分析的分析.
背景情况:
- 纵向测量和时间到事件结果在临床研究中至关重要,但传统方法面临着离散观察和高审查率的挑战.
- 准确的估计需要利用重复观察超过基线值,特别是在潜在治愈的疾病.
研究的目的:
- 提出一种联合建模方法,在治疗分数框架内同时分析纵向数据和时间到事件结果.
- 为了应对离散纵向数据和生存分析中的高度审查的挑战.
- 为了研究纵向前列腺特异性抗原 (PSA) 测量和转移性前列腺癌的整体存活率之间的关系.
主要方法:
- 使用功能主要组件分析 (FPCA) 来灵活建模纵向数据,而不假定特定的曲线形式.
- 采用考克斯的比例危害混合治愈模型进行时间到事件结果分析.
- 采用准概率方法与预期最大化 (E-M) 算法进行纵向二进制观测,通过Akaike信息标准 (AIC) 选择调参数.
主要成果:
- 拟议的联合建模方法在广泛的模拟研究中证明了准确的估计.
- 该方法成功应用于临床试验数据集,揭示了纵向PSA水平和整体存活率之间的关联.
结论:
- 联合建模方法有效地将纵向测量和时间到事件数据集成到治愈模型中.
- 这种方法为分析复杂的临床试验数据提供了一个强大的框架,特别是在瘤学中,提高对疾病进展和治疗疗效的理解.
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