Human Health Sciences, Kyoto University Graduate School of Medicine, Kyoto, Japan
Department of Emergency Medicine, National Hospital Organization Mito Medical Center, Ibaraki, Japan.
BMJ Evid Based Med. 2023 Feb;28(1):40-47. doi: 10.1136/bmjebm-2021-111861. Epub 2022 Jul 19.
Our objectives were to examine the magnitude of the proportion attributable to contextual effects (PCE), which shows what proportion of the treatment arm response can be achieved by the placebo arm across various interventions, and to examine PCE variability by outcome type and condition.
We conducted a meta-epidemiological study.
We searched the Cochrane Database of Systematic Reviews with the keyword 'placebo' in titles, abstracts and keywords on 1 January 2020.
We included reviews that showed statistically significant beneficial effects of the intervention over placebo for the first primary outcome.
We performed a random-effects meta-analysis to calculate PCEs based on the pooled result of each included review, grouped by outcome type and condition. The PCE quantifies how much of the observed treatment response can be achieved by the contextual effects.
No patient or member of the public was involved in conducting this research.
We included 328 out of 3175 Cochrane systematic reviews. The results of meta-analyses showed that PCEs varied greatly depending on outcome type (I=98%) or condition (I=98%), but mostly lie between 0.40 and 0.95. Overall, the PCEs were 0.65 (95% CI 0.59 to 0.72) on average. Subjective outcomes were 0.50 (95% CI 0.41 to 0.59), which was significantly smaller than those of semiobjective (PCE 0.78; 95% CI 0.72 to 0.85) or objective outcomes (PCE 0.94; 95% CI 0.91 to 0.97).
The results suggest that much of the observed benefit is not just due to the specific effect of the interventions. The specific effects of interventions may be larger for subjective outcomes than for objective or semiobjective outcomes. However, PCEs were exceptionally variable. When we evaluate the magnitude of PCEs, we should consider each PCE individually, for each condition, intervention and outcome in its context, to assess the importance of an intervention for each specific clinical setting.
本研究旨在检验与情境效应（PCE）相关的幅度，该幅度反映了在不同干预措施中，安慰剂组能够实现治疗组反应的比例；并按结局类型和条件检验 PCE 的变异性。
我们进行了一项荟萃流行病学研究。
我们于 2020 年 1 月 1 日，以“placebo”为关键词，在 Cochrane 系统评价数据库中检索标题、摘要和关键词。
我们纳入了显示干预措施对安慰剂有统计学显著益处的综述，其第一主要结局为阳性。
我们对每个纳入的综述进行了随机效应荟萃分析，根据每个综述的汇总结果计算 PCE，按结局类型和条件进行分组。PCE 定量评估了观察到的治疗反应中有多少可以归因于情境效应。
本研究未涉及患者或公众参与。
我们纳入了 328 篇 Cochrane 系统评价中的 3175 篇。荟萃分析结果表明，PCE 随结局类型（I²=98%）或条件（I²=98%）而有很大差异，但主要介于 0.40 到 0.95 之间。总体而言，PCE 平均为 0.65（95%CI 0.59 至 0.72）。主观结局为 0.50（95%CI 0.41 至 0.59），显著小于半客观结局（PCE 0.78；95%CI 0.72 至 0.85）或客观结局（PCE 0.94；95%CI 0.91 至 0.97）。
结果表明，观察到的大部分益处不仅仅是由于干预措施的特定效果。干预措施的特定效果对于主观结局可能比对客观或半客观结局更大。然而，PCE 变化非常大。当我们评估 PCE 的幅度时，我们应该考虑到每个条件、干预措施和结局的具体情况，单独评估每个 PCE，以评估干预措施对每个特定临床环境的重要性。
