Xu Chang, Doi Suhail A R, Zhou Xiaoqin, Lin Lifeng, Furuya-Kanamori Luis, Tao Fangbiao
Ministry of Education Key Laboratory for Population Health Across-life Cycle & Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Anhui, China; School of Public Health, Anhui Medical University, Anhui, China.
Department of Population Medicine, College of Medicine, QU Health, Qatar University, Doha, Qatar.
Sleep Med Rev. 2022 Dec;66:101708. doi: 10.1016/j.smrv.2022.101708. Epub 2022 Oct 19.
In this study, we examined the data reproducibility issues in systematic reviews in sleep medicine. We searched for systematic reviews of randomized controlled trials published in sleep medicine journals. The metadata in meta-analyses among the eligible systematic reviews were collected. The original sources of the data were reviewed to see if the components used in the meta-analyses were correctly extracted or estimated. The impacts of the data reproducibility issues were investigated. We identified 48 systematic reviews with 244 meta-analyses of continuous outcomes and 54 of binary outcomes. Our results suggest that for continuous outcomes, 20.03% of the data used in meta-analyses cannot be reproduced at the trial level, and 43.44% of the data cannot be reproduced at the meta-analysis level. For binary outcomes, the proportions were 14.14% and 40.74%. In total, 83.33% of the data cannot be reproduced at the systematic review level. Our further analysis suggested that these reproducibility issues would lead to as much as 6.52% of the available meta-analyses changing the direction of the effects, and 9.78% changing the significance of the P-values. Sleep medicine systematic reviews and meta-analyses face serious issues in terms of data reproducibility, and further efforts are urgently needed to improve this situation.
在本研究中,我们调查了睡眠医学系统评价中的数据可重复性问题。我们检索了睡眠医学期刊上发表的随机对照试验的系统评价。收集了符合条件的系统评价中的荟萃分析的元数据。审查了数据的原始来源,以查看荟萃分析中使用的成分是否被正确提取或估计。研究了数据可重复性问题的影响。我们确定了48项系统评价,其中有244项对连续结局的荟萃分析和54项对二元结局的荟萃分析。我们的结果表明,对于连续结局,荟萃分析中使用的数据有20.03%在试验水平上无法重现,43.44%的数据在荟萃分析水平上无法重现。对于二元结局,这两个比例分别为14.14%和40.74%。总体而言,83.33%的数据在系统评价水平上无法重现。我们的进一步分析表明,这些可重复性问题将导致多达6.52%的可用荟萃分析改变效应方向,9.78%改变P值的显著性。睡眠医学系统评价和荟萃分析在数据可重复性方面面临严重问题,迫切需要进一步努力改善这种情况。