实效性随机对照试验中的统计方法(Ⅰ): 解决依从性问题

Statistical methods in pragmatic randomized controlled trials (Ⅰ): addressing non-compliance

在真实世界数据研究中,实效性随机对照试验可提供最佳证据。尽管随机化原则可使其免受混杂因素的影响,但是由于依从性问题,其仍然需要面对随机后混杂偏倚。传统意向性治疗分析原则在此情况下会逐渐偏离试验原本所关注的疗效并使最终临床决策出现偏差,而传统代替方法也受到混杂偏倚的影响。因此,需要新方法来解决依从性问题,目前有工具变量估计法和现代符合方案集分析法2种。本文介绍了传统方法在实效性随机对照试验中的缺陷,论述了上述两种新方法,并指出其优势和劣势,以期为研究者今后开展实效性随机对照试验选择合理统计分析方法提供思路。

In the study of real-world data,the pragmatic randomized controlled trial can provide the optimal evidence for clinical decisions.Although randomization protects against confounding,post-randomization confounding may still arise due to non-compliance.Traditional intention-to-treat analysis will drift apart from true estimation and lead to deviation of clinical decisions.Meanwhile,the alternative traditional methods would subject to bias and confounding.Thus,new methods are required for revolution,i.e.,instrument variable method and modern per-protocol analysis.Our study reviews the defects of traditional methods in pragmatic randomized controlled trials,and then refers to two new methods with a detailed discussion of strengths and weaknesses.We aim to provide researches with insights on choosing the statistical methods for pragmatic trial.