Ioannidis John P A
Clinical and Molecular Epidemiology Unit, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, and Biomedical Research Institute, Foundation for Research and Technology–Hellas, Ioannina, Greece.
Arch Gen Psychiatry. 2011 Aug;68(8):773-80. doi: 10.1001/archgenpsychiatry.2011.28. Epub 2011 Apr 4.
Many studies report volume abnormalities in diverse brain structures in patients with various mental health conditions.
To evaluate whether there is evidence for an excess number of statistically significant results in studies of brain volume abnormalities that suggest the presence of bias in the literature.
PubMed (articles published from January 2006 to December 2009).
Recent meta-analyses of brain volume abnormalities in participants with various mental health conditions vs control participants with 6 or more data sets included, excluding voxel-based morphometry.
Standardized effect sizes were extracted in each data set, and it was noted whether the results were "positive" (P < .05) or not. For each data set in each meta-analysis, I estimated the power to detect at α = .05 an effect equal to the summary effect of the respective meta-analysis. The sum of the power estimates gives the number of expected positive data sets. The expected number of positive data sets can then be compared against the observed number.
From 8 articles, 41 meta-analyses with 461 data sets were evaluated (median, 10 data sets per meta-analysis) pertaining to 7 conditions. Twenty-one of the 41 meta-analyses had found statistically significant associations, and 142 of 461 (31%) data sets had positive results. Even if the summary effect sizes of the meta-analyses were unbiased, the expected number of positive results would have been only 78.5 compared with the observed number of 142 (P < .001).
There are too many studies with statistically significant results in the literature on brain volume abnormalities. This pattern suggests strong biases in the literature, with selective outcome reporting and selective analyses reporting being possible explanations.
许多研究报告了患有各种心理健康状况的患者在不同脑结构中的体积异常。
评估在脑体积异常研究中是否存在证据表明存在过多具有统计学意义的结果，这表明文献中存在偏差。
PubMed（2006年1月至2009年12月发表的文章）。
对患有各种心理健康状况的参与者与对照组参与者进行的脑体积异常的近期荟萃分析，纳入6个或更多数据集，不包括基于体素的形态测量学。
在每个数据集中提取标准化效应量，并记录结果是否为“阳性”（P <.05）。对于每个荟萃分析中的每个数据集，我估计了在α =.05水平下检测到等于相应荟萃分析汇总效应的效应的功效。功效估计值的总和给出了预期阳性数据集的数量。然后可以将预期阳性数据集的数量与观察到的数量进行比较。
从8篇文章中，评估了与7种状况相关的41项荟萃分析，共461个数据集（中位数，每项荟萃分析10个数据集）。41项荟萃分析中有21项发现了具有统计学意义的关联，461个数据集中有142个（31%）结果为阳性。即使荟萃分析的汇总效应量无偏差，与观察到的142个相比，预期阳性结果数量也仅为78.5（P <.001）。
关于脑体积异常的文献中有太多研究具有统计学意义的结果。这种模式表明文献中存在强烈的偏差，选择性结果报告和选择性分析报告可能是解释原因。
