ArticleBMC medical research methodology2017
Why statistical inference from clinical trials is likely to generate false and irreproducible results.
Article in BMC medical research methodology, 2017. 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
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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.
- Effectiveness of Interventions to Improve Women's Experience of Pelvic Examinations: A Systematic Review and Meta-Analysis.BJOG : an international journal of obstetrics and gynaecology · 2026Pooled it
- Pooled it
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- The active construction of past episodes.Translational neuroscience · 2026Article
- Nonparametric assessment of regimen response curve estimators.Biometrics · 2025Article
- Multifractal foundations of biomarker discovery for heart disease and stroke.Scientific reports · 2023Article
- Towards Good Statistical Practice. CORSTAN Validated Questionnaire for Assessing the Correctness of Statistical Analysis in Medical Research.Problemy endokrinologii · 2021Article
- PK-DB: pharmacokinetics database for individualized and stratified computational modeling.Nucleic acids research · 2021Article
- Alternative causal inference methods in population health research: Evaluating tradeoffs and triangulating evidence.SSM - population health · 2020Article
- Translation, Cross-Cultural Adaptation, and Validation of the Pain Sensitivity Questionnaire in Dutch Healthy Volunteers.Pain research & management · 2020Article
- Navigating the development and dissemination of internet cognitive behavioral therapy (iCBT) for anxiety disorders in children and young people: A consensus statement with recommendations from the #iCBTLorentz Workshop Group.Internet interventions · 2018Article
- Effect of removing outliers on statistical inference: implications to interpretation of experimental data in medical research.Marshall journal of medicine · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
One area of biomedical research where the replication crisis is most visible and consequential is clinical trials. Why do outcomes of so many clinical trials contradict each other? Why is the effectiveness of many drugs and other medical interventions so low? Why have prescription medications become the third leading cause of death in the US and Europe after cardiovascular diseases and cancer? In answering these questions, the main culprits identified so far have been various biases and conflicts of interest in planning, execution and analysis of clinical trials as well as reporting their outcomes. In this work, we take an in-depth look at statistical methodology used in planning clinical trials and analyzing trial data. We argue that this methodology is based on various questionable and empirically untestable assumptions, dubious approximations and arbitrary thresholds, and that it is deficient in many other respects. The most objectionable among these assumptions is that of distributional homogeneity of subjects' responses to medical interventions. We analyze this and other assumptions both theoretically and through clinical examples. Our main conclusion is that even a totally unbiased, perfectly randomized, reliably blinded, and faithfully executed clinical trial may still generate false and irreproducible results. We also formulate a few recommendations for the improvement of the design and statistical methodology of clinical trials informed by our analysis.
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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.