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BMC Medical Research Methodology· 2026Q1· Review

Adaptive platform trials: A revolution or a fleeting trend? A review of the strengths and limitations

Brett Doleman, Kristian Thorlund, Caroline Barkholt Kamp, Theis Lange et al.

Short summary

Platform trials, designed to efficiently evaluate multiple interventions within a single, ongoing infrastructure, offer potential advantages like resource optimization and faster therapy evaluation but face significant limitations including lack of blinding and reliance on non-concurrent controls.

AI-generated from the title and abstract; the full text is not read.

Key points

  • Platform trials enable efficient evaluation of multiple interventions within a single, ongoing infrastructure, allowing dynamic modifications like adding/removing treatment arms.
  • Key advantages include infrastructure reusability, cost-effectiveness, and efficiency in comparative effectiveness research.
  • Significant limitations include frequent lack of blinding, reliance on non-concurrent control groups, and response-adaptive randomization, which may introduce bias and reduce statistical power.
  • Evidence shows many platform trials do not fully exploit their potential, with 40% not adding new arms and insufficient statistical adjustments for multiple testing.
  • Success depends on rigorous methodological standards, maintaining trial integrity, and navigating operational/regulatory challenges.

AI-generated from the title and abstract; the full text is not read.

Abstract

Abstract Platform trials have gained significant attention in recent years, particularly during the COVID-19 pandemic, for their potential to deliver efficient and flexible clinical research. Designed to evaluate multiple interventions within a single, ongoing infrastructure, platform trials allow for dynamic trial modifications, such as adding or removing treatment arms. These features offer potential advantages over conventional randomised controlled trials, including resource optimisation, reduced participant numbers, and faster evaluation of new therapies. Despite these potential strengths, the design and implementation of platform trials are associated with several methodological and logistical challenges that may undermine their validity. This review critically evaluates the platform trial methodology, exploring its potential to revolutionise clinical research or serve merely as a transient innovation. We discuss key advantages such as infrastructure reusability, cost-effectiveness, and efficiency in comparative effectiveness research. However, we also highlight significant limitations. These include a frequent lack of blinding, reliance on non-concurrent control groups, and the use of response-adaptive randomisation, all of which may introduce bias, reduce statistical power, and compromise internal validity. Additional issues such as increased ethical and regulatory complexity, underreporting of negative results, and insufficient realisation of theoretical efficiencies further temper the enthusiasm for this design. Evidence from recent systematic reviews reveals that many platform trials do not fully exploit their potential—40% have not added new arms, and only a minority conduct appropriate statistical adjustments for multiple testing. Nevertheless, simulations suggest long-term cost and time savings compared to traditional randomised controlled trials, assuming adequate implementation. We conclude that platform trials are not inherently flawed, although must be designed and conducted with rigorous methodological standards. Their success depends on maintaining core principles of trial integrity—especially reducing the risks of systematic, random, and design errors—while navigating operational and regulatory challenges. Platform trials are likely to become an integral part of the clinical trial landscape, provided they supplement, rather than compromise, the foundations of evidence-based medicine.

The authors' abstract, as published at the source. BMC Medical Research Methodology, 2026 · DOI ↗

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Field: Statistics and Probability

Statistics and ProbabilityMathematics