安慰剂
医学
随机对照试验
中止
随机化
期望理论
安慰剂反应
物理疗法
慢性疼痛
内科学
心理学
社会心理学
病理
替代医学
作者
Lene Vase,Jan Vollert,Nanna Brix Finnerup,Xiaopeng Miao,Gary Atkinson,Scott Marshall,Robert Németh,Bernd Lange,Charlie Liss,Donald D. Price,Christoph Maier,Troels S. Jensen,Märta Segerdahl
出处
期刊:Pain
[Lippincott Williams & Wilkins]
日期:2015-05-07
卷期号:156 (9): 1795-1802
被引量:100
标识
DOI:10.1097/j.pain.0000000000000217
摘要
A large number of analgesics have failed to prove superiority over placebo in randomized controlled trials (RCTs), and as this has been related to increasing placebo responses, there is currently an interest in specifying predictors of the placebo response. The literature on placebo mechanisms suggests that factors related to patients' expectations of treatment efficacy are pivotal for the placebo response. Also, general characteristics of RCTs have been suggested to influence the placebo response. Yet, only few meta-analyses have directly tested these hypotheses. Placebo data from 9 industrially sponsored, randomized, double-blind, placebo-controlled, multicenter phase III trials in 2017 adult patients suffering from chronic painful osteoarthritis (hip or knee) or low back pain were included. The primary outcome was pain intensity. Based on previous studies, we chose 3 expectancy-related primary predictors: type of active medication, randomization ratio, and number of planned face-to-face visits. In addition, explorative analyses tested whether RCT and patients' characteristics predicted the placebo response. Opioid trials, a high number of planned face-to-face visits, and randomization ratio predicted the magnitude of the placebo response, thereby supporting the expectancy hypothesis. Exploratory models with baseline pain intensity, age, washout length, and discontinuation because of adverse events accounted for approximately 10% of the variability in the placebo response. Based on these results and previous mechanisms studies, we think that patients' perception of treatment allocation and expectations toward treatment efficacy could potently predict outcomes of RCTs.
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