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5087 项随机对照试验中数据捏造和其他非随机抽样的原因,这些试验发表于麻醉学和一般医学期刊。

Data fabrication and other reasons for non-random sampling in 5087 randomised, controlled trials in anaesthetic and general medical journals.

机构信息

Department of Anaesthesia, Peri-operative Medicine and Intensive Care, Torbay Hospital, UK.

出版信息

Anaesthesia. 2017 Aug;72(8):944-952. doi: 10.1111/anae.13938. Epub 2017 Jun 4.

Abstract

Randomised, controlled trials have been retracted after publication because of data fabrication and inadequate ethical approval. Fabricated data have included baseline variables, for instance, age, height or weight. Statistical tests can determine the probability of the distribution of means, given their standard deviation and the number of participants in each group. Randomised, controlled trials have been retracted after the data distributions have been calculated as improbable. Most retracted trials have been written by anaesthetists and published by specialist anaesthetic journals. I wanted to explore whether the distribution of baseline data in trials was consistent with the expected distribution. I wanted to determine whether trials retracted after publication had distributions different to trials that have not been retracted. I wanted to determine whether data distributions in trials published in specialist anaesthetic journals have been different to distributions in non-specialist medical journals. I analysed the distribution of 72,261 means of 29,789 variables in 5087 randomised, controlled trials published in eight journals between January 2000 and December 2015: Anaesthesia (399); Anesthesia and Analgesia (1288); Anesthesiology (541); British Journal of Anaesthesia (618); Canadian Journal of Anesthesia (384); European Journal of Anaesthesiology (404); Journal of the American Medical Association (518) and New England Journal of Medicine (935). I chose these journals as I had electronic access to the full text. Trial p values were distorted by an excess of baseline means that were similar and an excess that were dissimilar: 763/5015 (15.2%) trials that had not been retracted from publication had p values that were within 0.05 of 0 or 1 (expected 10%), that is, a 5.2% excess, p = 1.2 × 10 . The p values of 31/72 (43%) trials that had been retracted after publication were within 0.05 of 0 or 1, a rate different to that for unretracted trials, p = 1.03 × 10 . The difference between the distributions of these two subgroups was confirmed by comparison of their overall distributions, p = 5.3 × 10 . Each journal exhibited the same abnormal distribution of baseline means. There was no difference in distributions of baseline means for 1453 trials in non-anaesthetic journals and 3634 trials in anaesthetic journals, p = 0.30. The rate of retractions from JAMA and NEJM, 6/1453 or 1 in 242, was one-quarter the rate from the six anaesthetic journals, 66/3634 or 1 in 55, relative risk (99%CI) 0.23 (0.08-0.68), p = 0.00022. A probability threshold of 1 in 10,000 identified 8/72 (11%) retracted trials (7 by Fujii et al.) and 82/5015 (1.6%) unretracted trials. Some p values were so extreme that the baseline data could not be correct: for instance, for 43/5015 unretracted trials the probability was less than 1 in 10 (equivalent to one drop of water in 20,000 Olympic-sized swimming pools). A probability threshold of 1 in 100 for two or more trials by the same author identified three authors of retracted trials (Boldt, Fujii and Reuben) and 21 first or corresponding authors of 65 unretracted trials. Fraud, unintentional error, correlation, stratified allocation and poor methodology might have contributed to the excess of randomised, controlled trials with similar or dissimilar means, a pattern that was common to all the surveyed journals. It is likely that this work will lead to the identification, correction and retraction of hitherto unretracted randomised, controlled trials.

摘要

随机对照试验在发表后因数据伪造和伦理批准不足而被撤回。伪造的数据包括基线变量,例如年龄、身高或体重。统计检验可以确定给定其标准差和每组参与者数量的平均值分布的概率。在数据分布被计算为不可能的情况下,随机对照试验被撤回。大多数被撤回的试验是由麻醉师撰写并由专业麻醉期刊发表的。我想探讨试验中基线数据的分布是否与预期分布一致。我想确定已发表后撤回的试验与未撤回的试验的分布是否不同。我想确定发表在专业麻醉期刊上的试验的数据分布是否与非专业医学期刊上的分布不同。我分析了在 2000 年 1 月至 2015 年 12 月期间发表在八个期刊的 5087 项随机对照试验的 29789 个变量的 72261 个平均值的分布:麻醉(399);麻醉与镇痛(1288);麻醉学(541);英国麻醉杂志(618);加拿大麻醉杂志(384);欧洲麻醉学杂志(404);美国医学会杂志(518)和新英格兰医学杂志(935)。我选择这些期刊是因为我可以访问全文。试验 p 值因相似和不相似的基线平均值过多而失真:未撤回的 5015 项试验中有 763 项(15.2%)的 p 值在 0.05 以内接近 0 或 1(预期的 10%),即 5.2%的多余,p = 1.2×10 。已发表后撤回的 31 项试验(43%)的 p 值在 0.05 以内接近 0 或 1,与未撤回试验的 p 值不同,p = 1.03×10 。通过比较它们的总体分布,证实了这两个亚组之间的分布差异,p = 5.3×10 。每个期刊都表现出相同的异常基线平均值分布。在非麻醉期刊的 1453 项试验和麻醉期刊的 3634 项试验中,基线平均值的分布没有差异,p = 0.30。从 JAMA 和 NEJM 撤回的试验比例为 6/1453 或 1/242,是从六个麻醉期刊撤回的试验比例 66/3634 或 1/55 的四分之一,相对风险(99%CI)为 0.23(0.08-0.68),p = 0.00022。概率阈值为 1/10000 可识别出 8/72(11%)撤回的试验(7 项由 Fujii 等人)和 82/5015(1.6%)未撤回的试验。一些 p 值非常极端,以至于基线数据不可能是正确的:例如,对于 5015 个未撤回的试验中的 43 个,概率小于 1/10000(相当于在 20000 个奥林匹克标准游泳池中只有一滴)。对于相同作者的两个或更多试验的概率阈值为 1/100,则可识别出 3 名撤回试验的作者(Boldt、Fujii 和 Reuben)和 65 名未撤回试验的 21 名第一或对应作者。欺诈、无意错误、相关性、分层分配和较差的方法学可能导致具有相似或不同平均值的随机对照试验过多,这种模式在所有调查期刊中都很常见。这项工作很可能会导致以前未撤回的随机对照试验的识别、纠正和撤回。

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