More about the webinar
Sequential designs can greatly reduce the potential cost of a trial by stopping early where evidence is strongly in favour (efficacy) or against (futility) the treatment at an early interim analysis. For example, the accelerated approval of Covid-19 vaccine trials in 2020 were based on sequential design approaches.
A wide variety of methods are available for sequential designs such as error-spending, Haybittle-Peto and Wang-Tsiatis designs with careful consideration between these needed to justify design choices to sponsors and regulators.
These design choices are even more complicated when dealing with complex endpoints such as time-to-event where considerations such as accrual, hazard rates and dropout can have substantial effects on the statistical and practical aspects of study design.
Choosing between different sequential design choices can be difficult but simulation can be used to explore the performance of a sequential design under a wide variety of scenarios including different effect sizes, test statistic choices and stopping boundaries.
These simulations provide context on the expected probability of stopping for efficacy or futility at each interim analysis and the expected overall sample size that will be recruited for a sequential trial under those assumptions.
In this free webinar, we discuss the choices available for sequential designs, how sequential designs are adapted for complex endpoints such as time-to-event and how simulation can allow exploration of sequential design’s operating characteristics under a range of scenarios.
