• Anaesthesia · May 2012

    Review

    The analysis of 168 randomised controlled trials to test data integrity.

    Carlisle investigated the distribution of independent variables between study groups in Fujii's fraudulent research:

    "The published distributions of 28/33 variables (85%) were inconsistent with the expected distributions, such that the likelihood of their occurring ranged from 1 in 25 to less than 1 in 1 000 000 000 000 000 000 000 000 000 000 000 (1 in 1033), equivalent to p values of 0.04 to < 1 × 10-33 , respectively."

    summary
    • J B Carlisle.
    • Consultant Anaesthetist, Torbay Hospital, South Devon NHS Foundation Trust, Torquay, UK.
    • Anaesthesia. 2012 May 1; 67 (5): 521-537.

    AbstractThe purpose of this study was to use some statistical methods to assess if randomised controlled trials (RCTs) published by one particular author (Fujii) contained data of unusual consistency. I searched seven electronic databases, retrieving 168 RCTs published by this author between 1991 and July 2011. I extracted rates for categorical variables and means (SDs) for continuous variables, and compared these published distributions with distributions that would be expected by chance. The published distributions of 28/33 variables (85%) were inconsistent with the expected distributions, such that the likelihood of their occurring ranged from 1 in 25 to less than 1 in 1 000 000 000 000 000 000 000 000 000 000 000 (1 in 10(33)), equivalent to p values of 0.04 to < 1 × 10(-33) , respectively. In 141 human studies, 13/13 published continuous variable distributions were inconsistent with expected, their likelihoods being: weight < 1 in 10(33) ; age < 1 in 10(33) ; height < 1 in 10(33) ; last menstrual period 1 in 4.5 × 10(15) ; baseline blood pressure 1 in 4.2 × 10(5) ; gestational age 1 in 28; operation time < 1 in 10(33) ; anaesthetic time < 1 in 10(33) ; fentanyl dose 1 in 6.3 × 10(8) ; operative blood loss 1 in 5.6 × 10(9) ; propofol dose 1 in 7.7 × 10(7) ; paracetamol dose 1 in 4.4 × 10(2) ; uterus extrusion time 1 in 33. The published distributions of 7/11 categorical variables in these 141 studies were inconsistent with the expected, their likelihoods being: previous postoperative nausea and vomiting 1 in 2.5 × 10(6) ; motion sickness 1 in 1.0 × 10(4) ; male or female 1 in 140; antihypertensive drug 1 in 25; postoperative headache 1 in 7.1 × 10(10) ; postoperative dizziness 1 in 1.6 × 10(6) ; postoperative drowsiness 1 in 3.8 × 10(4) . Distributions for individual RCTs were inconsistent with the expected in 96/134 human studies by Fujii et al. that reported more than two continuous variables, their likelihood ranging from 1 in 22 to 1 in 140 000 000 000 (1 in 1.4 × 10(11)), compared with 12/139 RCTs by other authors. In 26 canine studies, the distributions of 8/9 continuous variables were inconsistent with the expected, their likelihoods being: right atrial pressure < 1 in 10(33) ; diaphragmatic stimulation (100 Hz) < 1 in 10(33) ; pulmonary artery occlusion pressure < 1 in 10(33) ; diaphragmatic stimulation (20 Hz) < 1 in 10(33) ; heart rate 1 in 6.3 × 10(10) ; mean pulmonary artery pressure 1 in 2.2 × 10(14) ; mean arterial pressure 1 in 6.3 × 10(7) ; cardiac output 1 in 110. Distributions were inconsistent with the expected in 21/24 individual canine studies that reported more than two continuous variables, their likelihood ranging from 1 in 345 to 1 in 51 000 000 000 000 (1 in 5.1 × 10(13)).Anaesthesia © 2012 The Association of Anaesthetists of Great Britain and Ireland.

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    This article appears in the collection: Drowning in the Sea of Evidence.

    Notes

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    1

    Carlisle investigated the distribution of independent variables between study groups in Fujii's fraudulent research:

    "The published distributions of 28/33 variables (85%) were inconsistent with the expected distributions, such that the likelihood of their occurring ranged from 1 in 25 to less than 1 in 1 000 000 000 000 000 000 000 000 000 000 000 (1 in 1033), equivalent to p values of 0.04 to < 1 × 10-33 , respectively."

    Daniel Jolley  Daniel Jolley
     
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