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已发表的随机试验中,公开可获取和符合预设统计分析方法的情况很低。

Public availability and adherence to prespecified statistical analysis approaches was low in published randomized trials.

机构信息

MRC Clinical Trials Unit at UCL, London, UK.

Pragmatic Clinical Trials Unit, Queen Mary University of London, London, UK.

出版信息

J Clin Epidemiol. 2020 Dec;128:29-34. doi: 10.1016/j.jclinepi.2020.07.015. Epub 2020 Jul 28.

Abstract

BACKGROUND AND OBJECTIVE

Prespecification of statistical methods in clinical trial protocols and statistical analysis plans can help to deter bias from p-hacking but is only effective if the prespecified approach is made available.

STUDY DESIGN AND SETTING

For 100 randomized trials published in 2018 and indexed in PubMed, we evaluated how often a prespecified statistical analysis approach for the trial's primary outcome was publicly available. For each trial with an available prespecified analysis, we compared this with the trial publication to identify whether there were unexplained discrepancies.

RESULTS

Only 12 of 100 trials (12%) had a publicly available prespecified analysis approach for their primary outcome; this document was dated before recruitment began for only two trials. Of the 12 trials with an available prespecified analysis approach, 11 (92%) had one or more unexplained discrepancies. Only 4 of 100 trials (4%) stated that the statistician was blinded until the SAP was signed off, and only 10 of 100 (10%) stated the statistician was blinded until the database was locked.

CONCLUSION

For most published trials, there is insufficient information available to determine whether the results may be subject to p-hacking. Where information was available, there were often unexplained discrepancies between the prespecified and final analysis methods.

摘要

背景与目的

临床试验方案中统计方法的预先设定有助于防止 p 值操纵带来的偏差,但只有在预先设定的方法可用的情况下才有效。

研究设计与设置

我们评估了 2018 年在 PubMed 中索引的 100 项随机试验中,预先设定的主要结局统计分析方法有多少次是公开可用的。对于每个有可用预先设定分析的试验,我们将其与试验出版物进行比较,以确定是否存在无法解释的差异。

结果

仅有 100 项试验中的 12 项(12%)具有公开的预先设定的主要结局分析方法;其中只有两项试验的该文件是在招募开始之前制定的。在 12 项具有可用预先设定分析方法的试验中,有 11 项(92%)存在一个或多个无法解释的差异。仅有 100 项试验中的 4 项(4%)表示统计师在 SAP 签署之前保持盲态,仅有 100 项试验中的 10 项(10%)表示统计师在数据库锁定之前保持盲态。

结论

对于大多数已发表的试验,没有足够的信息来确定结果是否可能受到 p 值操纵的影响。在有信息可用的情况下,预先设定和最终分析方法之间往往存在无法解释的差异。

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