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在随机临床试验中估计治疗效果时考虑感知、安慰剂和揭盲效应。

Accounting for perception, placebo and unmasking effects in estimating treatment effects in randomised clinical trials.

作者信息

Jamshidian Farid, Hubbard Alan E, Jewell Nicholas P

机构信息

Division of Biostatistics, School of Public Health, University of California, Berkeley, CA, USA.

Division of Biostatistics, School of Public Health, University of California, Berkeley, CA, USA

出版信息

Stat Methods Med Res. 2014 Jun;23(3):293-307. doi: 10.1177/0962280211413449. Epub 2011 Sep 8.

Abstract

There is a rich literature on the role of placebos in experimental design and evaluation of therapeutic agents or interventions. The importance of masking participants, investigators and evaluators to treatment assignment (treatment or placebo) has long been stressed as a key feature of a successful trial design. Nevertheless, there is considerable variability in the technical definition of the placebo effect and the impact of treatment assignments being unmasked. We suggest a formal concept of a 'perception effect' and define unmasking and placebo effects in the context of randomised trials. We employ modern tools from causal inference to derive semi-parametric estimators of such effects. The methods are illustrated on a motivating example from a recent pain trial where the occurrence of treatment-related side effects acts as a proxy for unmasking.

摘要

关于安慰剂在治疗药物或干预措施的实验设计与评估中的作用,已有丰富的文献资料。长期以来,人们一直强调让参与者、研究者和评估者对治疗分配(治疗或安慰剂)保持盲态,这是成功试验设计的一个关键特征。然而,安慰剂效应的技术定义以及治疗分配被揭盲的影响存在相当大的差异。我们提出了一个“感知效应”的正式概念,并在随机试验的背景下定义了揭盲和安慰剂效应。我们运用因果推断的现代工具来推导此类效应的半参数估计量。通过一个近期疼痛试验中的激励性例子来说明这些方法,在该试验中,与治疗相关的副作用的发生可作为揭盲的替代指标。

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