False individual patient data and zombie randomised controlled trials submitted to Anaesthesia
- PMID: 33040331
- DOI: 10.1111/anae.15263
False individual patient data and zombie randomised controlled trials submitted to Anaesthesia
Abstract
Concerned that studies contain false data, I analysed the baseline summary data of randomised controlled trials when they were submitted to Anaesthesia from February 2017 to March 2020. I categorised trials with false data as 'zombie' if I thought that the trial was fatally flawed. I analysed 526 submitted trials: 73 (14%) had false data and 43 (8%) I categorised zombie. Individual patient data increased detection of false data and categorisation of trials as zombie compared with trials without individual patient data: 67/153 (44%) false vs. 6/373 (2%) false; and 40/153 (26%) zombie vs. 3/373 (1%) zombie, respectively. The analysis of individual patient data was independently associated with false data (odds ratio (95% credible interval) 47 (17-144); p = 1.3 × 10-12 ) and zombie trials (odds ratio (95% credible interval) 79 (19-384); p = 5.6 × 10-9 ). Authors from five countries submitted the majority of trials: China 96 (18%); South Korea 87 (17%); India 44 (8%); Japan 35 (7%); and Egypt 32 (6%). I identified trials with false data and in turn categorised trials zombie for: 27/56 (48%) and 20/56 (36%) Chinese trials; 7/22 (32%) and 1/22 (5%) South Korean trials; 8/13 (62%) and 6/13 (46%) Indian trials; 2/11 (18%) and 2/11 (18%) Japanese trials; and 9/10 (90%) and 7/10 (70%) Egyptian trials, respectively. The review of individual patient data of submitted randomised controlled trials revealed false data in 44%. I think journals should assume that all submitted papers are potentially flawed and editors should review individual patient data before publishing randomised controlled trials.
Keywords: fabrication; individual patient data; randomised controlled trials; research misconduct; zombie.
© 2020 Association of Anaesthetists.
Comment in
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Hundreds of thousands of zombie randomised trials circulate among us.Anaesthesia. 2021 Apr;76(4):444-447. doi: 10.1111/anae.15297. Epub 2020 Oct 30. Anaesthesia. 2021. PMID: 33124075 No abstract available.
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Stamp out fake clinical data by working together.Nature. 2022 Jan;601(7892):167. doi: 10.1038/d41586-022-00025-6. Nature. 2022. PMID: 35017708 No abstract available.
References
-
- Ioannidis JPA. Why most published research findings are false. PLoS Medicine 2005; 2: e124.
-
- Nair S, Yean C, Yoo J, Leff J, Delphin E, Adams D. Reasons for article retraction in anesthesiology: a comprehensive analysis. Canadian Journal of Anesthesia 2020; 67: 57-63.
-
- Dal-Ré R, Ayuso C. Reasons for and time to retraction of genetic articles published between 1970 and 2018. Journal of Medical Genetics 2020; 57: 435.
-
- Brainard J, You J. What a massive database of retracted papers reveals about science publishing's ‘death penalty’. Science 2018. https://doi.org/10.1126/science.aav8384 (accessed 28/07/2019).
-
- Carlisle JB. The analysis of 168 randomised controlled trials to test data integrity. Anaesthesia 2012; 67: 521-37.
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