来自元流行病学研究的令人信服的证据表明,随机试验中的效应被高估了,这些随机试验未能优化随机化,盲人患者和结果评估人员无法优化随机化
Ying Wang1, Sameer Parpia2, Rachel Couban3
1Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada.
Journal of clinical epidemiology
|November 8, 2023
概括
随机试验中的偏差风险,例如不充分的随机序列生成或分配隐,可能导致对效应的高估. 缺乏患者或结果评估者盲目的情况也会对效果估计产生重大影响,特别是在患者报告和主观结果方面.
科学领域:
- 临床试验方法论 临床试验方法论
- 生物统计学 生物统计学
- 证据综合 证据综合
背景情况:
- 偏差因素的风险可以影响随机试验中的效果估计.
- 超流行病学研究对于评估这些影响至关重要.
研究的目的:
- 在随机试验中,系统地调查潜在偏差因素风险对随机试验效果估计的影响.
- 综合从随机对照试验中偏见的元流行病学研究中的证据.
主要方法:
- 对元流行病学研究的系统调查.
- 包括使用试验间或试验内比较的研究.
- 提取了几率比率 (ROR) 的比率,并使用随机效应模型进行组合.
- 使用GRADE和ICER框架评估证据的确定性.
主要成果:
- 不充分的随机序列生成和分配隐藏可能会导致适度的效果高估 (中等确定性).
- 缺乏患者失明可能导致患者报告结果的大幅高估 (中等确定性).
- 缺乏结果评估者盲目的结果导致对主观结果的大幅高估 (高确定性).
- 试验提前停止的好处可能高估了效果 (中等确定性).
结论:
- 如果未能确保足够的随机化和分配隐,可能会导致适度高估.
- 缺乏失明显著高估了患者报告和主观结果的影响.
- 虽然其他偏见元素的证据有限,但它们的缺失仍然可能引入重要的偏见.
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