Mavridis Dimitris, Efthimiou Orestis, Leucht Stefan, Salanti Georgia
Department of Primary Education, University of Ioannina, University Campus, PO Box 1186, 45110 Ioannina, Greece; Department of Hygiene and Epidemiology, University of Ioannina, PO Box 1186, 45110 Ioannina, Greece.
Department of Hygiene and Epidemiology, University of Ioannina, PO Box 1186, 45110 Ioannina, Greece.
J Clin Epidemiol. 2016 Jan;69:161-9. doi: 10.1016/j.jclinepi.2015.05.027. Epub 2015 Jun 5.
Publication bias (PB) may seriously compromise inferences from meta-analyses. The aim of this article was to assess the potential effect of small-study effects and PB on the recently estimated relative effectiveness and ranking of pharmacological treatments for schizophrenia.
We used a recently published network of 167 trials involving 36,871 patients and comparing the effectiveness of 15 antipsychotics and placebo. We used novel visual and statistical methods to explore if smaller trials are associated with larger treatment effects and a selection model to explore if the probability of trial publication is associated with the magnitude of effect. We conducted a network meta-analysis of the published evidence as our primary analysis and used a sensitivity analysis considering low, moderate, and severe selection bias (that corresponds to the number of unpublished trials) with an aim to evaluate robustness of point estimates and ranking. We explored whether placebo-controlled and head-to-head trials are associated with different levels of PB.
We found that small placebo-controlled trials exaggerated slightly the efficacy of antipsychotics, and PB was not unlikely in the evidence based on placebo-controlled trials; however, ranking of antipsychotics remained robust.
The total evidence comprises many head-to-head trials that do not appear to be prone to small-study effects or PB, and indirect evidence appears to "wash out" some of the biases in the placebo-controlled trials.
发表偏倚(PB)可能会严重影响荟萃分析的推断。本文旨在评估小样本研究效应和发表偏倚对近期估计的精神分裂症药物治疗相对疗效及排名的潜在影响。
我们使用了最近发表的一个包含167项试验的网络,涉及36,871名患者,比较了15种抗精神病药物和安慰剂的疗效。我们使用新颖的视觉和统计方法来探究较小的试验是否与较大的治疗效果相关,以及使用一个选择模型来探究试验发表的可能性是否与效应大小相关。我们对已发表的证据进行了网络荟萃分析作为主要分析,并进行了一项敏感性分析,考虑低、中、重度选择偏倚(对应未发表试验的数量),目的是评估点估计和排名的稳健性。我们探究了安慰剂对照试验和直接比较试验是否与不同程度的发表偏倚相关。
我们发现小型安慰剂对照试验略微夸大了抗精神病药物的疗效,并且基于安慰剂对照试验的证据中存在发表偏倚的可能性较大;然而,抗精神病药物的排名仍然稳健。
总体证据包括许多直接比较试验,这些试验似乎不易受到小样本研究效应或发表偏倚的影响,并且间接证据似乎“消除”了安慰剂对照试验中的一些偏倚。