Suppr超能文献

对具有完整数据共享政策的主要生物医学期刊中的随机对照试验进行数据共享和重新分析:对[具体年份1]和[具体年份2]发表的研究的调查

Data sharing and reanalysis of randomized controlled trials in leading biomedical journals with a full data sharing policy: survey of studies published in and .

作者信息

Naudet Florian, Sakarovitch Charlotte, Janiaud Perrine, Cristea Ioana, Fanelli Daniele, Moher David, Ioannidis John P A

机构信息

Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, California, USA.

Quantitative Sciences Unit, Division of Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA, USA.

出版信息

BMJ. 2018 Feb 13;360:k400. doi: 10.1136/bmj.k400.

Abstract

OBJECTIVES

To explore the effectiveness of data sharing by randomized controlled trials (RCTs) in journals with a full data sharing policy and to describe potential difficulties encountered in the process of performing reanalyses of the primary outcomes.

DESIGN

Survey of published RCTs.

SETTING

PubMed/Medline.

ELIGIBILITY CRITERIA

RCTs that had been submitted and published by and subsequent to the adoption of data sharing policies by these journals.

MAIN OUTCOME MEASURE

The primary outcome was data availability, defined as the eventual receipt of complete data with clear labelling. Primary outcomes were reanalyzed to assess to what extent studies were reproduced. Difficulties encountered were described.

RESULTS

37 RCTs (21 from and 16 from ) published between 2013 and 2016 met the eligibility criteria. 17/37 (46%, 95% confidence interval 30% to 62%) satisfied the definition of data availability and 14 of the 17 (82%, 59% to 94%) were fully reproduced on all their primary outcomes. Of the remaining RCTs, errors were identified in two but reached similar conclusions and one paper did not provide enough information in the Methods section to reproduce the analyses. Difficulties identified included problems in contacting corresponding authors and lack of resources on their behalf in preparing the datasets. In addition, there was a range of different data sharing practices across study groups.

CONCLUSIONS

Data availability was not optimal in two journals with a strong policy for data sharing. When investigators shared data, most reanalyses largely reproduced the original results. Data sharing practices need to become more widespread and streamlined to allow meaningful reanalyses and reuse of data.

TRIAL REGISTRATION

Open Science Framework osf.io/c4zke.

摘要

目的

探讨在实行全面数据共享政策的期刊中,通过随机对照试验(RCT)进行数据共享的有效性,并描述在对主要结局进行重新分析过程中可能遇到的困难。

设计

对已发表的随机对照试验进行调查。

研究背景

PubMed/Medline。

纳入标准

这些期刊采用数据共享政策后提交并发表的随机对照试验。

主要结局指标

主要结局为数据可用性,定义为最终收到带有清晰标注的完整数据。对主要结局进行重新分析,以评估研究结果在多大程度上得以重现,并描述遇到的困难。

结果

2013年至2016年间发表的37项随机对照试验(21项来自[期刊1名称],16项来自[期刊2名称])符合纳入标准。17/37(46%,95%置信区间30%至62%)满足数据可用性定义,其中17项中的14项(82%,59%至94%)所有主要结局均被完全重现。在其余的随机对照试验中,两项发现了错误,但得出了相似的结论,还有一篇论文在方法部分未提供足够信息以重现分析。发现的困难包括联系通讯作者存在问题,以及通讯作者在准备数据集方面缺乏资源。此外,不同研究组的数据共享做法存在差异。

结论

在两家有严格数据共享政策的期刊中,数据可用性并不理想。当研究者共享数据时,大多数重新分析在很大程度上重现了原始结果。数据共享做法需要更广泛且更简化,以便能够进行有意义的重新分析和数据重用。

试验注册

开放科学框架osf.io/c4zke。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9eb/5809812/d2f760fed483/nauf041198.f1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验