ArticlePharmaceutical statistics2021
Controlling type I error rates in multi-arm clinical trials: A case for the false discovery rate.
Article in Pharmaceutical statistics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis 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
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Lessons Learned from Phase II and Phase III Trials Investigating Therapeutic Agents for Cerebral Ischemia Associated with Aneurysmal Subarachnoid Hemorrhage.Neurocritical care · 2022Pooled it
- The analgesic effect of total intravenous anaesthesia with propofol versus inhalational anaesthesia for acute postoperative pain after hepatectomy: a randomized controlled trial.BMC anesthesiology · 2023Trial
- A Pre-Implementation Enhancement Strategy to Increase the Yield of Training and Consultation for School-Based Behavioral Preventive Practices: a Triple-Blind Randomized Controlled Trial.Prevention science : the official journal of the Society for Prevention Research · 2023Trial
- Trial
- Multiplicity adjustments in parallel-group multi-arm trials sharing a control group: Clear guidance is needed.Contemporary clinical trials · 2022Trial
- Navigating challenges in pediatric trial conduct: integrating bayesian sequential design with semiparametric elicitation for handling primary and secondary endpoints.BMC medical research methodology · 2025Article
- Inter-organizational alignment and implementation outcomes in integrated mental healthcare for children and adolescents: a cross-sectional observational study.Implementation science : IS · 2024Observational
- Inter-Organizational Alignment and Implementation Outcomes in Integrated Mental Healthcare for Children and Adolescents: A Cross-Sectional Observational Study.Research square · 2024Article
- Online error rate control for platform trials.Statistics in medicine · 2023Article
- Online control of the False Discovery Rate in group-sequential platform trials.Statistical methods in medical research · 2022Article
- Intervention Tournaments: An Overview of Concept, Design, and Implementation.Perspectives on psychological science : a journal of the Association for Psychological Science · 2022Article
- Decision rules for identifying combination therapies in open-entry, randomized controlled platform trials.Pharmaceutical statistics · 2022Article
- Practical Considerations and Recommendations for Master Protocol Framework: Basket, Umbrella and Platform Trials.Therapeutic innovation & regulatory science · 2021Review
- Collaborative Platform Trials to Fight COVID-19: Methodological and Regulatory Considerations for a Better Societal Outcome.Clinical pharmacology and therapeutics · 2021Review
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Multi-arm trials are an efficient way of simultaneously testing several experimental treatments against a shared control group. As well as reducing the sample size required compared to running each trial separately, they have important administrative and logistical advantages. There has been debate over whether multi-arm trials should correct for the fact that multiple null hypotheses are tested within the same experiment. Previous opinions have ranged from no correction is required, to a stringent correction (controlling the probability of making at least one type I error) being needed, with regulators arguing the latter for confirmatory settings. In this article, we propose that controlling the false-discovery rate (FDR) is a suitable compromise, with an appealing interpretation in multi-arm clinical trials. We investigate the properties of the different correction methods in terms of the positive and negative predictive value (respectively how confident we are that a recommended treatment is effective and that a non-recommended treatment is ineffective). The number of arms and proportion of treatments that are truly effective is varied. Controlling the FDR provides good properties. It retains the high positive predictive value of FWER correction in situations where a low proportion of treatments is effective. It also has a good negative predictive value in situations where a high proportion of treatments is effective. In a multi-arm trial testing distinct treatment arms, we recommend that sponsors and trialists consider use of the FDR.
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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.