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Public availability and adherence to prespecified statistical analysis approaches was low in published randomized
Brennan C Kahan1, Tahania Ahmad2, Gordon Forbes3
1MRC Clinical Trials Unit at UCL, London, UK.
Journal of Clinical Epidemiology
|July 31, 2020
Summary
Publicly available prespecified statistical analysis plans are crucial for preventing p-hacking in clinical trials. However, a study of 100 trials found only 12% had available plans, with most showing discrepancies.
Area of Science:
- Clinical Trials
- Biostatistics
- Research Integrity
Background:
- Prespecification of statistical methods in clinical trial protocols and statistical analysis plans (SAPs) is essential for deterring p-hacking.
- The effectiveness of prespecification relies on the public availability of these documented approaches.
Purpose of the Study:
- To evaluate the availability of prespecified statistical analysis approaches for primary outcomes in published randomized trials.
- To identify discrepancies between prespecified and published analysis methods in clinical trials.
Main Methods:
- A review of 100 randomized trials published in 2018 and indexed in PubMed.
- Assessment of the public availability of trial-specific prespecified statistical analysis plans.
- Comparison of prespecified analyses with published trial results to detect unexplained discrepancies.
Main Results:
- Only 12% (12 of 100) of trials had a publicly available prespecified analysis approach for their primary outcome.
- For the few trials with available plans, 92% (11 of 12) exhibited unexplained discrepancies between the prespecified and published methods.
- Blinding of statisticians until SAP sign-off or database lock was rarely reported (4% and 10%, respectively).
Conclusions:
- Most published clinical trials lack sufficient information to assess potential p-hacking due to the unavailability of prespecified analysis plans.
- Unexplained discrepancies between planned and executed analyses are common when prespecified methods are available, raising concerns about research integrity.
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