Centre for Evidence-Based Medicine Odense (CEBMO) and Cochrane Denmark, Department of Clinical Research, University of Southern Denmark, Odense, Denmark.
Open Patient data Explorative Network (OPEN), Odense University Hospital, Odense, Denmark.
Cochrane Database Syst Rev. 2023 Mar 6;3(3):MR000055. doi: 10.1002/14651858.MR000055.pub2.
An estimated 60% of pharmacological randomised trials use placebo control interventions to blind (i.e. mask) participants. However, standard placebos do not control for perceptible non-therapeutic effects (i.e. side effects) of the experimental drug, which may unblind participants. Trials rarely use active placebo controls, which contain pharmacological compounds designed to mimic the non-therapeutic experimental drug effects in order to reduce the risk of unblinding. A relevant improvement in the estimated effects of active placebo compared with standard placebo would imply that trials with standard placebo may overestimate experimental drug effects.
We aimed to estimate the difference in drug effects when an experimental drug is compared with an active placebo versus a standard placebo control intervention, and to explore causes for heterogeneity. In the context of a randomised trial, this difference in drug effects can be estimated by directly comparing the effect difference between the active placebo and standard placebo intervention.
We searched PubMed, CENTRAL, Embase, two other databases, and two trial registries up to October 2020. We also searched reference lists and citations and contacted trial authors.
We included randomised trials that compared an active placebo versus a standard placebo intervention. We considered trials both with and without a matching experimental drug arm.
We extracted data, assessed risk of bias, scored active placebos for adequacy and risk of unintended therapeutic effect, and categorised active placebos as unpleasant, neutral, or pleasant. We requested individual participant data from the authors of four cross-over trials published after 1990 and one unpublished trial registered after 1990. Our primary inverse-variance, random-effects meta-analysis used standardised mean differences (SMDs) of active versus standard placebo for participant-reported outcomes at earliest post-treatment assessment. A negative SMD favoured the active placebo. We stratified analyses by trial type (clinical or preclinical) and supplemented with sensitivity and subgroup analyses and meta-regression. In secondary analyses, we investigated observer-reported outcomes, harms, attrition, and co-intervention outcomes.
We included 21 trials (1462 participants). We obtained individual participant data from four trials. Our primary analysis of participant-reported outcomes at earliest post-treatment assessment resulted in a pooled SMD of -0.08 (95% confidence interval (CI) -0.20 to 0.04; I = 31%; 14 trials), with no clear difference between clinical and preclinical trials. Individual participant data contributed 43% of the weight of this analysis. Two of seven sensitivity analyses found more pronounced and statistically significant differences; for example, in the five trials with low overall risk of bias, the pooled SMD was -0.24 (95% CI -0.34 to -0.13). The pooled SMD of observer-reported outcomes was similar to the primary analysis. The pooled odds ratio (OR) for harms was 3.08 (95% CI 1.56 to 6.07), and for attrition, 1.22 (95% CI 0.74 to 2.03). Co-intervention data were limited. Meta-regression found no statistically significant association with adequacy of the active placebo or risk of unintended therapeutic effect.
AUTHORS' CONCLUSIONS: We did not find a statistically significant difference between active and standard placebo control interventions in our primary analysis, but the result was imprecise and the CI compatible with a difference ranging from important to irrelevant. Furthermore, the result was not robust, because two sensitivity analyses produced a more pronounced and statistically significant difference. We suggest that trialists and users of information from trials carefully consider the type of placebo control intervention in trials with high risk of unblinding, such as those with pronounced non-therapeutic effects and participant-reported outcomes.
据估计,60%的药理学随机试验使用安慰剂对照干预来进行盲法(即掩盖)。然而,标准安慰剂并不能控制实验药物的可感知非治疗作用(即副作用),这可能会使参与者失去盲法。试验很少使用活性安慰剂对照,其中包含设计用于模拟非治疗性实验药物作用的药理学化合物,以降低失盲的风险。与标准安慰剂相比,活性安慰剂的估计效果的相关改善意味着使用标准安慰剂的试验可能高估了实验药物的效果。
我们旨在估计当实验药物与活性安慰剂相比与标准安慰剂对照干预时药物效果的差异,并探讨异质性的原因。在随机试验的背景下,这种药物效果的差异可以通过直接比较活性安慰剂和标准安慰剂干预之间的效果差异来估计。
我们检索了 PubMed、CENTRAL、Embase、另外两个数据库和两个试验注册处,截至 2020 年 10 月。我们还检索了参考文献和引用,并联系了试验作者。
我们纳入了比较活性安慰剂与标准安慰剂干预的随机试验。我们考虑了既有对照药物臂也没有对照药物臂的试验。
我们提取了数据,评估了偏倚风险,对活性安慰剂的充分性和非预期治疗作用的风险进行了评分,并将活性安慰剂归类为不愉快、中性或愉快。我们向 4 项发表于 1990 年后的交叉试验的作者和 1 项 1990 年后注册的未发表试验的作者请求了个体参与者数据。我们的主要逆方差、随机效应荟萃分析使用了最早治疗后评估时的活性与标准安慰剂之间的标准化均数差值(SMD)来表示参与者报告的结局。负 SMD 有利于活性安慰剂。我们按试验类型(临床或临床前)进行分层分析,并辅以敏感性和亚组分析以及荟萃回归。在次要分析中,我们研究了观察者报告的结局、危害、失访和共干预结局。
我们纳入了 21 项试验(1462 名参与者)。我们从四项试验中获得了个体参与者数据。我们对最早治疗后评估时的参与者报告结局进行的主要分析得出了一个 SMD 的汇总值为-0.08(95%置信区间(CI)-0.20 至 0.04;I = 31%;14 项试验),在临床和临床前试验之间没有明显差异。个体参与者数据占这一分析的 43%权重。两项敏感性分析中的两项发现了更显著和统计学上显著的差异;例如,在总体偏倚风险较低的五项试验中,汇总 SMD 为-0.24(95% CI -0.34 至 -0.13)。观察者报告结局的汇总 SMD 与主要分析相似。危害的汇总比值比(OR)为 3.08(95% CI 1.56 至 6.07),失访的 OR 为 1.22(95% CI 0.74 至 2.03)。共干预数据有限。荟萃回归发现,活性安慰剂的充分性或非预期治疗作用的风险与结果之间没有统计学上的显著关联。
我们的主要分析中未发现活性和标准安慰剂对照干预之间存在统计学上的显著差异,但结果不精确,置信区间与从重要到无关的差异范围相兼容。此外,结果并不稳健,因为两项敏感性分析产生了更显著和统计学上显著的差异。我们建议,对于那些具有明显非治疗作用和参与者报告结局的高失盲风险的试验,试验设计者和试验信息使用者应仔细考虑试验中使用的安慰剂对照干预类型。