Adaptive versus fixed designs in confirmatory clinical trials: centering the choice on ethics
Stef Baas, Lukas Pin, David S. Roberstoon, Frank Bretz, Hearn Jay Cho, Laura Flight, Rieke van der Graaf, Mackenzie Graham, Peter Jacko, Thomas Jaki, Jonathan Kimmelman, Andrea Manfrin, Richard Milne, Pavel Mozgunov, Philip Pallmann, Tom Parke, Mahesh K. B. Parmar, Vinciane Pirard, Kate Sahan, Jerome Amir Singh, Brian D. M. Tom, John C. Whittaker, Katie Wozniak, David Wright, Haiyan Zheng, Alex John London, Mark Sheehan, Sofía S. VillarBackground:
Because confirmatory clinical trials are costly, large-scale endeavors, the choice of their design carries significant weight. While the current methodological landscape offers tools to address residual pre-trial uncertainty through prespecified adaptations to design elements, design choices remain frequently constrained by prevailing orthodoxies.
Methods:
We examine how unacknowledged design uncertainties (e.g., sample size calculations based on incorrect effect size or variance estimates) impact the statistical, ethical, and resource-stewardship goals of confirmatory trials. We contrast how fixed and adaptive design strategies handle these uncertainties, detailing the operational safeguards, firewalls, and trade-offs (e.g., complexity, operational bias) required to preserve trial integrity.
Results:
Strict adherence to default templates prevents stakeholders from matching the design strategy to the specific complexities of the research question. We observe that the gold standard status of fixed designs often obscures their limitations in handling design uncertainties. A rigid adherence to these conventions can ethically hinder a trial’s ability to deliver conclusive results. Conversely, while adaptive designs can offer tools to efficiently reduce uncertainty, we acknowledge that adaptive elements are not without cost; their implementation requires rigorous safeguards to manage specific risks to trial integrity and potential operational biases.
Conclusion:
To better align clinical research with its ethical and scientific mandates, we issue two calls to action. First, trial designers, including statisticians, must clearly articulate how target and design uncertainties impact ethical obligations, promoting an open-minded evaluation of both fixed and adaptive methods. Second, stakeholders must foreground ethical considerations during design selection, requiring explicit justification for the use—or non-use—of adaptive elements. The ethical path forward is not to default to the old or blindly adopt the new, but to explicitly justify the chosen design based on its responsiveness to the specific uncertainties of the trial. We posit that trial design must transition from a habit-based process to one where pre-trial uncertainties are openly discussed and addressed.