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As clinical trials increase in complexity, the requirements for trial designs to adapt to these complications increase.
From dealing with non-proportional hazards in survival analysis to creating seamless Phase II/III clinical trials, it is an exciting time to be involved in clinical trial design and analysis.
Flexible Survival Analysis Designs
Non-proportional hazards and other complex survival curves have become of increasing interest, due to being commonly seen in immunotherapy development. This has led to interest in assessing the robustness of standard methods and alternative methods that better adapt to deviations.
Stepped-Wedge designs
Cluster-randomized designs are often adopted when there is a high risk of contamination if cluster members were randomized individually. Stepped-wedge designs are useful in cases where it is difficult to apply a particular treatment to half of the clusters at the same time.
Multi-Arm Multi-Stage (MAMS)
MAMs designs provide the ability to assess more treatments in less time than could be done with a series of two-arm trials and can offer smaller sample size requirements when compared to that required for the equivalent number of two-arm trials.
In this webinar, we have explored power analysis assuming complex survival curves and the weighted log-rank test as one candidate model to deal with a delayed survival effect, looked at the design of a Group Sequential MAMS design and explored its design requirements, and introduced stepped-wedge designs while providing insight into the more complex, flexible randomization schedules available.
nQuery helps make your clinical trials faster, less costly and more successful with tools for sample size calculation - refining Frequentist, Bayesian & Adaptive designs.
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Who is this for?
This will be highly beneficial if you're a biostatistician, scientist, or clinical trial professional who is involved in sample size calculation and the optimization of clinical trials in:
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