ReviewBMC medicine2020
Evidence of unexplained discrepancies between planned and conducted statistical analyses: a review of randomised trials.
Review in BMC medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Occlusal outcome of orthodontic treatment: a systematic review with meta-analyses of randomized trials.European journal of orthodontics · 2024Pooled it
- Evaluating how clear the questions being investigated in randomised trials are: systematic review of estimands.BMJ (Clinical research ed.) · 2022Pooled it
- Do papers tell the whole story? A benchmark and framework for uncovering hidden implementation gaps in bioinformatics.Briefings in bioinformatics · 2026Article
- Article
- Discrepancies in safety reporting for chronic back pain clinical trials: an observational study from ClinicalTrials.gov and publications.BMC medical research methodology · 2025Observational
- How can we make sound replication decisions?Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Industry Involvement and Transparency in the Most Cited Clinical Trials, 2019-2022.JAMA network open · 2023Review
- A template for the authoring of statistical analysis plans.Contemporary clinical trials communications · 2023Article
- Eliminating Ambiguous Treatment Effects Using Estimands.American journal of epidemiology · 2023Article
- Article
- Treatment estimands in clinical trials of patients hospitalised for COVID-19: ensuring trials ask the right questions.BMC medicine · 2020Article
- How to design a pre-specified statistical analysis approach to limit p-hacking in clinical trials: the Pre-SPEC framework.BMC medicine · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
backgroundChoosing or altering the planned statistical analysis approach after examination of trial data (often referred to as 'p-hacking') can bias the results of randomised trials. However, the extent of this issue in practice is currently unclear. We conducted a review of published randomised trials to evaluate how often a pre-specified analysis approach is publicly available, and how often the planned analysis is changed.
methodsA review of randomised trials published between January and April 2018 in six leading general medical journals. For each trial, we established whether a pre-specified analysis approach was publicly available in a protocol or statistical analysis plan and compared this to the trial publication.
resultsOverall, 89 of 101 eligible trials (88%) had a publicly available pre-specified analysis approach. Only 22/89 trials (25%) had no unexplained discrepancies between the pre-specified and conducted analysis. Fifty-four trials (61%) had one or more unexplained discrepancies, and in 13 trials (15%), it was impossible to ascertain whether any unexplained discrepancies occurred due to incomplete reporting of the statistical methods. Unexplained discrepancies were most common for the analysis model (n = 31, 35%) and analysis population (n = 28, 31%), followed by the use of covariates (n = 23, 26%) and the approach for handling missing data (n = 16, 18%). Many protocols or statistical analysis plans were dated after the trial had begun, so earlier discrepancies may have been missed.
conclusionsUnexplained discrepancies in the statistical methods of randomised trials are common. Increased transparency is required for proper evaluation of results.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.