Sverdlov Oleksandr, Ryeznik Yevgen, Wong Weng-Kee
a Translational Sciences , Novartis Pharmaceuticals Corporation , East Hanover , New Jersey , USA.
J Biopharm Stat. 2014;24(4):732-54. doi: 10.1080/10543406.2014.903261.
We consider a design problem for a clinical trial with multiple treatment arms and time-to-event primary outcomes that are modeled using the Weibull family of distributions. The D-optimal design for the most precise estimation of model parameters is derived, along with compound optimal allocation designs that provide targeted efficiencies for various estimation problems and ethical considerations. The proposed optimal allocation designs are studied theoretically and are implemented using response-adaptive randomization for a clinical trial with censored Weibull outcomes. We compare the merits of our multiple-objective response-adaptive designs with traditional randomization designs and show that our designs are more flexible, realistic, generally more ethical, and frequently provide higher efficiencies for estimating different sets of parameters.
我们考虑一个针对具有多个治疗组和事件发生时间主要结局的临床试验的设计问题,这些结局使用威布尔分布族进行建模。推导了用于最精确估计模型参数的D - 最优设计,以及为各种估计问题和伦理考量提供目标效率的复合最优分配设计。对所提出的最优分配设计进行了理论研究,并通过响应自适应随机化应用于具有删失威布尔结局的临床试验。我们将多目标响应自适应设计的优点与传统随机化设计进行了比较,结果表明我们的设计更灵活、更现实、通常更符合伦理,并且在估计不同参数集时经常能提供更高的效率。