在分散的临床试验中确定样本大小
Feng Tian1, Ruitao Lin1, Suyu Liu1
1Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
本研究引入了一个新的样本大小计算方法去中心化临床试验 (DCT),解决了当前研究中的差距. 该方法准确地确定各种DCT设计的样本大小,提高了研究功率和精度.
科学领域:
- 临床试验方法论 临床试验方法论
- 流行病学 流行病学
- 药物开发 药物开发
背景情况:
- 分散的临床试验 (DCT) 正在流行病学和药物开发中变得越来越突出.
- 确定适当的样本大小对于DCT设计至关重要,但缺乏全面的指导.
- 本文解决了这一差距,为DCT提出了一种新的样本大小计算方法.
研究的目的:
- 提出一个强大而准确的样本大小计算方法,专门用于分散的临床试验.
- 提供一个工具,在DCT中解释在现场和外部来源之间的数据异质性.
主要方法:
- 开发了一种采样大小计算方法,使用加权的z测试来处理现场和场外数据的差异和平均差异.
- 衍生闭式样本大小公式用于横截面,纵向和集群研究设计.
- 使用心血管疾病和疼痛管理试验的例子验证了该方法.
主要成果:
- 拟议的方法在各种条件下 (效果大小,ICC,差异,患者比率) 为DCT提供准确和可靠的样本大小确定.
- 与传统试验的常规样本大小公式相比,证明了更高的精度和功率保存.
- 数字研究证实了该方法在各种场景中的有效性.
结论:
- 开发的方法为DCT中样本大小计算提供了一个准确,易于使用的工具.
- 该方法适用于横截面和纵向/集群试验设计.
- 用户友好的软件支持实施这种样本大小确定方法.
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