Premium
Managing competing demands in the implementation of response‐adaptive randomization in a large multicenter phase III acute stroke trial
Author(s) -
Zhao Wenle,
Durkalski Valerie
Publication year - 2014
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.6213
Subject(s) - randomization , covariate , randomness , computer science , restricted randomization , clinical trial , frequentist inference , statistical power , statistics , random assignment , econometrics , medicine , mathematics , machine learning , artificial intelligence , bayesian probability , bayesian inference
It is well known that competing demands exist between the control of important covariate imbalance and protection of treatment allocation randomness in confirmative clinical trials. When implementing a response‐adaptive randomization algorithm in confirmative clinical trials designed under a frequentist framework, additional competing demands emerge between the shift of the treatment allocation ratio and the preservation of the power. Based on a large multicenter phase III stroke trial, we present a patient randomization scheme that manages these competing demands by applying a newly developed minimal sufficient balancing design for baseline covariates and a cap on the treatment allocation ratio shift in order to protect the allocation randomness and the power. Statistical properties of this randomization plan are studied by computer simulation. Trial operation characteristics, such as patient enrollment rate and primary outcome response delay, are also incorporated into the randomization plan. Copyright © 2014 John Wiley & Sons, Ltd.