Parallel Group Adaptive Designs [Two-Stage / GS Designs]

posted by Alex – Austria, 2023-12-22 11:08 (179 d 06:30 ago) – Posting: # 23800
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Hi all,

I am wondering whether the following publication made it to your attention: Wynne et al. (2022): A randomized, adaptive design, doubleblind, 3-arm, parallel study assessing the pharmacokinetics and safety of AVT02, a high-concentration (100 mg/mL) Adalimumab biosimilar, in healthy adult subjects (ALVOPAD FIRST). I would love to get your opinion on it.

I was the opinion that only simulation-based methods (Fuglsang 2014 - Sequential Bioequivalence Approaches for Parallel Designs) are currently available/acceptable for parallel group designs due to the complexity of contructing repeated confidence intervals allowing for unequal variances between groups (a requirement for parallel designs according to FDA guidelines). However, in the publication repeated confidence intervals were constructed using the Fisher combination test assuming equal variances (3 parallel treatment arms were analysed using ANOVA). What do you think about it?

I also have another question (likely a stupid one but it is in my head since some time). As there seems to be no solution currently avaiable for adaptive parallel group designs that analytically controls the type-I-error using the confidence interval inclusion approach and allows for unequal variances, wouldn't it be acceptable to use a hypothesis test like in (Maurer 2016 - Controlling the type I error rate in two-stage sequential adaptive designs when testing for average bioequivalence) only? In that case, we cannot construct confidence intervals consistent with the hypothesis test but the decision for BE=Y/N can be answered, right? I know that FDA guidelines state that it needs to be done by the confidence interval but is this less preferable than using Potvin's algorithm (not strictly controlling type-I-error)?

Thanks in advance, any opinion is highly recommended!

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