Bias in Peripheral Depression Biomarkers
Bias in Peripheral Depression Biomarkers
复制标题
DOI：
10.1159/000441457
复制
发表时间：
2016-01-01
影响因子：
22.8
通讯作者：
Berk, Michael
中科院分区：
文献类型：
--
作者：
Carvalho, Andre F.;Koehler, Cristiano A.;Berk, Michael
背景资料：为了帮助区分患有重度抑郁症（MDD）的个体与健康对照，已经提出了许多外周生物标志物。迄今为止，尚未对支持发表显著结果或夸大效应量的偏倚的存在进行全面评价。研究方法：在这里，我们进行了一个全面的审查荟萃分析的外周非遗传生物标志物，可以区分个人与非抑郁症的控制。检索了截至2015年4月10日的PubMed/ MEDLINE、EMBASE和PsycINFO数据库。结果：从15篇参考文献中，我们获得了31项合格的荟萃分析，评价MDD（21，201例病例和78，363例对照）的生物标志物。20项荟萃分析报告了具有统计学意义的效应量估计值。在29项荟萃分析中，异质性较高（I-2 >= 50%）。我们合理地假设荟萃分析的真实效应量等于其最大的研究。观察到20种生物标志物的显著汇总效应量估计值。我们在21项荟萃分析中观察到统计学显著性研究过多。该荟萃分析的汇总效应量高于25项荟萃分析中最大研究的效应，而11项荟萃分析有证据表明小型研究的效应。结论：我们的研究结果表明，在MDD外周生物标志物的文献中，有过多的研究具有统计学显著性结果。有选择地发表“实证研究”和有选择地报告结果是可能的机制。在本文献中，荟萃分析的效应量估计值可能被夸大。(C)2016 S. Karger AG，巴塞尔
Background: To aid in the differentiation of individuals with major depressive disorder (MDD) from healthy controls, numerous peripheral biomarkers have been proposed. To date, no comprehensive evaluation of the existence of bias favoring the publication of significant results or inflating effect sizes has been conducted. Methods: Here, we performed a comprehensive review of meta-analyses of peripheral nongenetic biomarkers that could discriminate individuals with MDD from nondepressed controls. PubMed/ MEDLINE, EMBASE, and PsycINFO databases were searched through April 10, 2015. Results: From 15 references, we obtained 31 eligible meta-analyses evaluating biomarkers in MDD (21,201 cases and 78,363 controls). Twenty meta-analyses reported statistically significant effect size estimates. Heterogeneity was high (I-2 >= 50%) in 29 meta-analyses. We plausibly assumed that the true effect size for a meta-analysis would equal the one of its largest study. A significant summary effect size estimate was observed for 20 biomarkers. We observed an excess of statistically significant studies in 21 meta-analyses. The summary effect size of the meta-analysis was higher than the effect of its largest study in 25 meta-analyses, while 11 meta-analyses had evidence of small-study effects. Conclusions: Our findings suggest that there is an excess of studies with statistically significant results in the literature of peripheral biomarkers for MDD. The selective publication of 'positive studies' and the selective reporting of outcomes are possible mechanisms. Effect size estimates of meta-analyses may be inflated in this literature. (C) 2016 S. Karger AG, Basel