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精神障碍患者随机试验中的对照干预措施。

Control interventions in randomised trials among people with mental health disorders.

机构信息

Psychiatric Research Unit, Region Zealand Psychiatry, Slagelse, Denmark.

Centre for Evidence-Based Medicine Odense (CEBMO) and Cochrane Denmark, Department of Clinical Research, University of Southern Denmark, Odense, Denmark.

出版信息

Cochrane Database Syst Rev. 2022 Apr 4;4(4):MR000050. doi: 10.1002/14651858.MR000050.pub2.

Abstract

BACKGROUND

Control interventions in randomised trials provide a frame of reference for the experimental interventions and enable estimations of causality. In the case of randomised trials assessing patients with mental health disorders, many different control interventions are used, and the choice of control intervention may have considerable impact on the estimated effects of the treatments being evaluated.

OBJECTIVES

To assess the benefits and harms of typical control interventions in randomised trials with patients with mental health disorders. The difference in effects between control interventions translates directly to the impact a control group has on the estimated effect of an experimental intervention. We aimed primarily to assess the difference in effects between (i) wait-list versus no-treatment, (ii) usual care versus wait-list or no-treatment, and (iii) placebo interventions (all placebo interventions combined or psychological, pharmacological, and physical placebos individually) versus wait-list or no-treatment. Wait-list patients are offered the experimental intervention by the researchers after the trial has been finalised if it offers more benefits than harms, while no-treatment participants are not offered the experimental intervention by the researchers.

SEARCH METHODS

In March 2018, we searched MEDLINE, PsycInfo, Embase, CENTRAL, and seven other databases and six trials registers.

SELECTION CRITERIA

We included randomised trials assessing patients with a mental health disorder that compared wait-list, usual care, or placebo interventions with wait-list or no-treatment .

DATA COLLECTION AND ANALYSIS

Titles, abstracts, and full texts were reviewed for eligibility. Review authors independently extracted data and assessed risk of bias using Cochrane's risk of bias tool. GRADE was used to assess the quality of the evidence. We contacted researchers working in the field to ask for data from additional published and unpublished trials. A pre-planned decision hierarchy was used to select one benefit and one harm outcome from each trial. For the assessment of benefits, we summarised continuous data as standardised mean differences (SMDs) and dichotomous data as risk ratios (RRs). We used risk differences (RDs) for the assessment of adverse events. We used random-effects models for all statistical analyses. We used subgroup analysis to explore potential causes for heterogeneity (e.g. type of placebo) and sensitivity analyses to explore the robustness of the primary analyses (e.g. fixed-effect model).

MAIN RESULTS

We included 96 randomised trials (4200 participants), ranging from 8 to 393 participants in each trial. 83 trials (3614 participants) provided usable data. The trials included 15 different mental health disorders, the most common being anxiety (25 trials), depression (16 trials), and sleep-wake disorders (11 trials). All 96 trials were assessed as high risk of bias partly because of the inability to blind participants and personnel in trials with two control interventions. The quality of evidence was rated low to very low, mostly due to risk of bias, imprecision in estimates, and heterogeneity. Only one trial compared wait-list versus no-treatment directly but the authors were not able to provide us with any usable data on the comparison. Five trials compared usual care versus wait-list or no-treatment and found a SMD -0.33 (95% CI -0.83 to 0.16, I² = 86%, 523 participants) on benefits. The difference between all placebo interventions combined versus wait-list or no-treatment was SMD -0.37 (95% CI -0.49 to -0.25, I² = 41%, 65 trials, 2446 participants) on benefits. There was evidence of some asymmetry in the funnel plot (Egger's test P value of 0.087). Almost all the trials were small. Subgroup analysis found a moderate effect in favour of psychological placebos SMD -0.49 (95% CI -0.64 to -0.30; I² = 53%, 39 trials, 1656 participants). The effect of pharmacological placebos versus wait-list or no-treatment on benefits was SMD -0.14 (95% CI -0.39 to 0.11, 9 trials, 279 participants) and the effect of physical placebos was SMD -0.21 (95% CI -0.35 to -0.08, I² = 0%, 17 trials, 896 participants). We found large variations in effect sizes in the psychological and pharmacological placebo comparisons. For specific mental health disorders, we found significant differences in favour of all placebos for sleep-wake disorders, major depressive disorder, and anxiety disorders, but the analyses were imprecise due to sparse data. We found no significant differences in harms for any of the comparisons but the analyses suffered from sparse data. When using a fixed-effect model in a sensitivity analysis on the comparison for usual care versus wait-list and no-treatment, the results were significant with an SMD of -0.46 (95 % CI -0.64 to -0.28). We reported an alternative risk of bias model where we excluded the blinding domains seeing how issues with blinding may be seen as part of the review investigation itself. However, this did not markedly change the overall risk of bias profile as most of the trials still included one or more unclear bias domains.

AUTHORS' CONCLUSIONS: We found marked variations in effects between placebo versus no-treatment and wait-list and between subtypes of placebo with the same comparisons. Almost all the trials were small with considerable methodological and clinical variability in factors such as mental health population, contents of the included control interventions, and outcome domains. All trials were assessed as high risk of bias and the evidence quality was low to very low. When researchers decide to use placebos or usual care control interventions in trials with people with mental health disorders it will often lead to lower estimated effects of the experimental intervention than when using wait-list or no-treatment controls. The choice of a control intervention therefore has considerable impact on how effective a mental health treatment appears to be. Methodological guideline development is needed to reach a consensus on future standards for the design and reporting of control interventions in mental health intervention research.

摘要

背景

随机试验中的对照干预为实验干预提供了一个参照框架,并能够估计因果关系。在评估心理健康障碍患者的随机试验中,使用了许多不同的对照干预措施,对照干预措施的选择可能会对正在评估的治疗效果产生相当大的影响。

目的

评估随机试验中精神健康障碍患者的典型对照干预措施的益处和危害。对照干预措施之间的效果差异直接转化为对照组对实验干预效果的影响。我们的主要目的是评估以下三种对照干预措施之间的效果差异:(i)等待名单与无治疗,(ii)常规护理与等待名单或无治疗,以及(iii)安慰剂干预措施(所有安慰剂干预措施的组合或心理、药理和物理安慰剂分别)与等待名单或无治疗。等待名单上的患者在试验结束后,如果实验干预措施的益处大于危害,研究人员会向他们提供实验干预措施,而无治疗组的患者则不会得到研究人员的干预措施。

检索方法

2018 年 3 月,我们检索了 MEDLINE、PsycInfo、Embase、CENTRAL 和另外 7 个数据库以及 6 个试验注册处。

选择标准

我们纳入了评估心理健康障碍患者的随机试验,这些试验比较了等待名单、常规护理或安慰剂干预措施与等待名单或无治疗。

数据收集和分析

我们对标题、摘要和全文进行了评估,以确定其是否符合纳入标准。审查员独立提取数据,并使用 Cochrane 的偏倚风险工具评估风险。使用 GRADE 评估证据质量。我们联系了该领域的研究人员,要求他们提供额外已发表和未发表试验的数据。我们使用预先计划的决策层次来从每个试验中选择一个益处和一个危害结局。对于益处的评估,我们将连续数据汇总为标准化均数差(SMD),将二分类数据汇总为风险比(RR)。我们使用风险差异(RD)来评估不良反应。我们对所有统计分析均使用随机效应模型。我们使用亚组分析来探索潜在的异质性原因(例如,安慰剂的类型),并使用敏感性分析来探索主要分析的稳健性(例如,固定效应模型)。

主要结果

我们纳入了 96 项随机试验(4200 名参与者),每项试验中参与者的数量为 8 至 393 人。83 项试验(3614 名参与者)提供了可用数据。这些试验涉及 15 种不同的心理健康障碍,最常见的是焦虑症(25 项试验)、抑郁症(16 项试验)和睡眠-觉醒障碍(11 项试验)。所有 96 项试验均被评估为高偏倚风险,部分原因是在有两种对照干预措施的试验中无法对参与者和人员进行盲法。证据质量被评为低到极低,主要是由于偏倚风险、估计值不精确和异质性。只有一项试验直接比较了等待名单与无治疗,但作者无法为我们提供关于这一比较的任何可用数据。五项试验比较了常规护理与等待名单或无治疗,发现益处方面的 SMD-0.33(95%CI-0.83 至 0.16,I²=86%,523 名参与者)。所有安慰剂干预措施的组合与等待名单或无治疗之间的差异为 SMD-0.37(95%CI-0.49 至-0.25,I²=41%,65 项试验,2446 名参与者)。漏斗图的不对称性存在一定的证据(Egger 检验 P 值为 0.087)。几乎所有的试验都很小。亚组分析发现,心理安慰剂的效果适中,SMD-0.49(95%CI-0.64 至-0.30;I²=53%,39 项试验,1656 名参与者)。药理安慰剂与等待名单或无治疗相比,对益处的影响为 SMD-0.14(95%CI-0.39 至 0.11,9 项试验,279 名参与者),物理安慰剂的影响为 SMD-0.21(95%CI-0.35 至-0.08,I²=0%,17 项试验,896 名参与者)。我们发现心理和药理安慰剂比较中效果大小的变化很大。对于特定的心理健康障碍,我们发现所有安慰剂对睡眠-觉醒障碍、重度抑郁症和焦虑症都有显著的益处,但由于数据稀疏,分析结果不精确。我们没有发现任何对照之间的危害有显著差异,但分析受到数据稀疏的影响。在对常规护理与等待名单和无治疗进行敏感性分析时,我们使用固定效应模型,结果为 SMD-0.46(95%CI-0.64 至-0.28)。我们报告了一种替代的偏倚风险模型,该模型排除了看到与盲法相关的问题可能被视为审查调查本身的一部分的盲法领域。然而,这并没有显著改变整体偏倚风险状况,因为大多数试验仍然存在一个或多个不明确的偏倚领域。

作者结论

我们发现安慰剂与无治疗和等待名单之间以及安慰剂与同一比较的亚类之间的效果存在显著差异。几乎所有的试验都很小,在心理健康人群、纳入对照干预措施的内容以及结局领域等方面存在很大的方法学和临床变异性。所有试验均被评估为高偏倚风险,证据质量为低至非常低。当研究人员在患有心理健康障碍的患者中使用安慰剂或常规护理对照干预措施时,这通常会导致实验干预的估计效果低于使用等待名单或无治疗对照。因此,对照干预措施的选择对精神健康治疗的效果有很大的影响。需要制定方法学指南,就精神健康干预研究中对照干预措施的未来标准达成共识。

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