重新评估试点试验在为大规模试验提供信息效果和样本大小估计中的作用:一项超流行病学研究
Xiangji Ying1, Karen A Robinson1,2,3, Stephan Ehrhardt4
1Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.
BMJ evidence-based medicine
|July 25, 2023
概括
试点试验显著增加了全面试验的成功概率. 使用来自试点研究的置信区间边界,而不是点估计,可能会改善对更大的研究的样本大小估计.
科学领域:
- 临床试验方法论 临床试验方法论
- 基于证据的医学基于证据的医学.
- 生物统计学 生物统计学
背景情况:
- 关于试验试验在随后的大规模试验效果大小方面所具有的价值存在争议.
- 本研究以实证的方式评估了试点试验在估计实验效果和样本大小方面的作用.
研究的目的:
- 评估试点试验在预测全面试验结果方面的有用性.
- 确定试验试验结果是否会影响全面试验结果的意义和准确性.
主要方法:
- 在PubMed系统搜索试点和随后的全面试验 (2005-2018).
- 分析试验和实验试验之间的结果一致性 (方向和效果大小的大小).
- 后勤回归用于评估试点试验意义与实体试验意义之间的关联.
主要成果:
- 具有显著试点结果的全面试验是显著的2.72倍 (p=0.001).
- 试点试验经常产生更大的点估计值,但87%的置信区间包括全尺度估计值.
- 使用试点试验标准偏差的样本大小估计降低了显著全尺度结果的可能性 (OR=0.26,p=0.004).
结论:
- 试点试验提供了有关干预有效性的宝贵信号.
- 使用来自试点试验的置信区间边界,而不是点估计,可能会提高对全规模试验的功率计算.
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