The additional operational cost of using Bayesian methods in an adaptive trial is usually small compared with the savings achieved through better decision-making and the use of fewer subjects. And Bayesian methods provide a level of flexibility that allows for more kinds of adaptive trials than more traditional methods.
The downside, of course, stems from that flexibility. Bayesian trials are more complex to design and execute, concludes Cato Research senior biostatistician John Johnson. And it's why he ranks the use of Bayesian methods among the five keys to successful adaptive trials.
Top of the list is to be aware of the upfront planning required, and to have project statisticians clear their calendars once that planning begins. "Because trial adaptations need to be pre-specified in the protocol, the range of possibilities--and the consequences of each--need to be considered," he writes in a Cato blog. "The statistician should be running many clinical trial simulations, even if this is a 'textbook' adaptive trial."
Johnson's remaining keys to success involve interim analyses, stakeholder buy-in and belief in interim results.
- see the blog