Background
Bayesian clinical trial designs are increasingly common; given their promotion by the US Food and Drug Administration, the future use of the Bayesian approach will only continue to increase. Innovations are possible when using the Bayesian approach to improve the efficiency of drug development and the accuracy of clinical trials, especially in the context of substantial data missingness.
Objective
This study aimed to explain the foundations, interpretations, and scientific justification of the Bayesian approach in the setting of lecanemab trial 201, a Bayesian-designed phase 2 dose-finding trial; to indicate the efficiency of using a Bayesian design; and to demonstrate how it accommodates innovations in the prospective design and also treatment-dependent types of missing data..
Methods
- This study was a Bayesian analysis of a clinical trial comparing the efficacy of 5 lecanemab 201 dosages for the treatment of early Alzheimer’s disease.
- The goal of the Lecanemab 201 trial was to identify the effective dose 90 (ED90), the dose achieving at least 90% of the maximum effectiveness of doses considered in the trial.
- This study evaluated the Bayesian adaptive randomization used, in which patients were preferentially assigned to doses that would give more information about the ED90 and its efficacy.
Results
- A total of 854 patients were included in the trial treatment: 238 were in the placebo group (median age, 72 years; 137 female) and 587 were assigned to a lecanemab 201 treatment group (median age, 72 years; 272 female).
- The Bayesian approach improved the efficiency of a clinical trial by prospective adapting to the trial’s interim results.
- By the end of the trial, more patients had been assigned to the better-performing doses.
- The Bayesian posterior probability that the ED90 was superior to placebo was 97.5% at 12 months and 97.7% at 18 months.
- The respective probabilities of super-superiority were 63.8% and 76.0%.
- The primary analysis of the randomized Bayesian lecanemab 201 trial found in the context of missing data that the most effective dose of lecanemab nearly doubles its estimated efficacy at 18 months of follow-up in comparison with restricting analysis to patients who completed the full 18 months of the trial.
Conclusion
This study concluded that innovations associated with the Bayesian approach can improve the efficiency of drug development and the accuracy of clinical trials, even in the context of substantial data missingness.