在适应剂量存在的情况下,对时间到事件数据的暴露-反应分析:有效的方法和陷
Alexandra Lavalley-Morelle1, Félicien Le Louedec1, Richard Anziano1
1Pharmetheus A.B., Uppsala, Sweden.
CPT: pharmacometrics & systems pharmacology
|November 21, 2025
概括
建议使用时间变化的暴露指标来分析时间到事件数据中的暴露-反应关系. 模拟表明,时间静态指标在各种条件下并不总是产生可靠的结果.
科学领域:
- 药理动力学和药理动力学
- 统计建模 统计建模
- 临床试验设计 临床试验设计
背景情况:
- 对时间到事件 (TTE) 数据分析暴露-反应 (E-R) 关系是复杂的,因为时间依赖因素.
- 一种常见的方法是使用时间静态暴露指标 (例如,初始或最后一次暴露) 而不是动态评估.
研究的目的:
- 用模拟来比较时间静态与时间变化的指标的性能,以评估TTE数据中的E-R关系.
- 在不同的模拟场景下评估不同暴露指标的可靠性.
主要方法:
- 模拟的药理动力学 (PK) 暴露使用一个单间模型.
- 用参数比例危险模型生成的TTE数据,将每周的PK平均度作为时间变化的共变量.
- 使用沃尔德测试对各种剂量,药物积累,事件类型和时间场景中的暴露效应参数进行评估的ER关系意义.
主要成果:
- 没有一个单一的时间静态暴露指标在所有模拟条件中显示出一致的可靠性.
- 时间变化的暴露指标在所有测试场景中表现出强大的统计特性和良好的表现.
- I型错误和功率分析表明时间静态方法的局限性.
结论:
- 随时间变化的暴露指标在TTE数据中分析ER关系时优越,因为它们的可靠性始终如一.
- 建议在统计模型中使用时间变化的共变量,以便在TTE分析中准确评估E-R.
- 在 E-R TTE 分析中避免使用时间静态指标,以确保有效的统计属性.
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