ArticleBMC medical research methodology2024
The impact of allocation bias on test decisions in clinical trials with multiple endpoints using multiple testing strategies.
Article in BMC medical research methodology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
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Who cites it
5 citing papers in PubMed.
- Is any research ever truly bias-free? The myth of objectivity in science.Naunyn-Schmiedeberg's archives of pharmacology · 2026Review
- Investigating the necessity of preoperative coronary angiography for infection-related cardiac implantable electronic device explantation.American heart journal plus : cardiology research and practice · 2026Article
- Comparison of primary analysis strategies of randomized controlled trials with multiple endpoints with application to kidney transplantation.Scientific reports · 2026Article
- Does randomization matter in rare disease clinical trials.PloS one · 2026Article
- Assessing allocation bias in stratified clinical trials with multi-component endpoints evaluated using the stratified Wei-Lachin test.PloS one · 2026Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
backgroundConsidering multiple endpoints in clinical trials provide a more comprehensive understanding of treatment effects and may lead to increased power or reduced sample size, which may be beneficial in rare diseases. Besides the small sample sizes, allocation bias is an issue that affects the validity of these trials. We investigate the impact of allocation bias on testing decisions in clinical trials with multiple endpoints and offer a tool for selecting an appropriate randomization procedure (RP).
methodsWe derive a model for quantifying the effect of allocation bias depending on the RP in the case of two-arm parallel group trials with continuous multiple endpoints. We focus on two approaches to analyze multiple endpoints, either the Šidák procedure to show efficacy in at least one endpoint and the all-or-none procedure to show efficacy in all endpoints.
resultsTo evaluate the impact of allocation bias on the test decision we propose a biasing policy for multiple endpoints. The impact of allocation on the test decision is measured by the family-wise error rate of the Šidák procedure and the type I error rate of the all-or-none procedure. Using the biasing policy we derive formulas to calculate these error rates. In simulations we show that, for the Šidák procedure as well as for the all-or-none procedure, allocation bias leads to inflation of the mean family-wise error and mean type I error, respectively. The strength of this inflation is affected by the choice of the RP.
conclusionAllocation bias should be considered during the design phase of a trial to increase validity. The developed methodology is useful for selecting an appropriate RP for a clinical trial with multiple endpoints to minimize allocation bias effects.
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Registered trials
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