Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA.
Contemp Clin Trials. 2012 Jan;33(1):172-7. doi: 10.1016/j.cct.2011.09.011. Epub 2011 Oct 1.
It is widely recognized that traditional randomized controlled trials (RCTs) have limited generalizability due to the numerous ways in which conditions of RCTs differ from those experienced each day by patients and physicians. As a result, there has been a recent push towards pragmatic trials that better mimic real-world conditions. One way in which RCTs differ from normal everyday experience is that all patients in the trial have uncertainty about what treatment they were assigned. Outside of the RCT setting, if a patient is prescribed a drug then there is no reason for them to wonder if it is a placebo. Uncertainty about treatment assignment could affect both treatment and placebo response. We use a potential outcomes approach to define relevant causal effects based on combinations of treatment assignment and belief about treatment assignment. We show that traditional RCTs are designed to estimate a quantity that is typically not of primary interest. We propose a new study design that has the potential to provide information about a wider range of interesting causal effects.
人们普遍认识到，由于 RCT 条件与患者和医生日常所经历的条件在众多方面存在差异，传统的随机对照试验（RCT）具有有限的普遍性。因此，最近人们一直在推动更符合实际情况的实用临床试验。RCT 与正常日常生活的不同之处之一是，试验中的所有患者对他们接受的治疗都不确定。在 RCT 环境之外，如果患者被开了一种药物，那么他们就没有理由怀疑它是否是安慰剂。对治疗分配的不确定性可能会影响治疗和安慰剂的反应。我们使用潜在结果方法来根据治疗分配和对治疗分配的信念的组合来定义相关的因果效应。我们表明，传统的 RCT 旨在估计通常不是主要关注点的数量。我们提出了一种新的研究设计，有可能提供有关更广泛的有趣因果效应的信息。
