Simultaneously investigating multiple treatments in a single study achieves considerable efficiency in contrast to the traditional two-arm trials.Balancing treatment allocation for influential covariates has become in...Simultaneously investigating multiple treatments in a single study achieves considerable efficiency in contrast to the traditional two-arm trials.Balancing treatment allocation for influential covariates has become increasingly important in today’s clinical trials.The multi-arm covariate-adaptive randomized clinical trial is one of the most powerful tools to incorporate covariate information and multiple treatments in a single study.Pocock and Simon’s procedure has been extended to the multi-arm case.However,the theoretical properties of multi-arm covariate-adaptive randomization have remained largely elusive for decades.In this paper,we propose a general framework for multi-arm covariate-adaptive designs which also includes the two-arm case,and establish the corresponding theory under widely satisfied conditions.The theoretical results provide new insights into the balance properties of covariate-adaptive randomization procedures and make foundations for most existing statistical inferences under two-arm covariate-adaptive randomization.Furthermore,these open a door to study the theoretical properties of statistical inferences for clinical trials based on multi-arm covariateadaptive randomization procedures.展开更多
In the past decade,significant progress has been made regarding inference under covariate-adaptive randomisation.We thank Prof.Shao for a timely review of the growing literature about the topic.The paper is focused on...In the past decade,significant progress has been made regarding inference under covariate-adaptive randomisation.We thank Prof.Shao for a timely review of the growing literature about the topic.The paper is focused on the most important and commonly used class of covariate-adaptive randomisation methods,i.e.,those balancing discrete covariates.The recent advances in robust inference are emphasised and discussed in detail.Several types of outcomes,such as continuous and time-to-event data,are covered.We here provide some additional recent results from the following five perspectives.展开更多
基金supported by the National Key R&D Program of China (Grant No.2018YFC2000302)National Natural Science Foundation of China (Grant Nos.11731012,11731011 and 12031005)+1 种基金Ten Thousands Talents Plan of Zhejiang Province (Grant No.2018R52042)the Fundamental Research Funds for the Central Universities。
文摘Simultaneously investigating multiple treatments in a single study achieves considerable efficiency in contrast to the traditional two-arm trials.Balancing treatment allocation for influential covariates has become increasingly important in today’s clinical trials.The multi-arm covariate-adaptive randomized clinical trial is one of the most powerful tools to incorporate covariate information and multiple treatments in a single study.Pocock and Simon’s procedure has been extended to the multi-arm case.However,the theoretical properties of multi-arm covariate-adaptive randomization have remained largely elusive for decades.In this paper,we propose a general framework for multi-arm covariate-adaptive designs which also includes the two-arm case,and establish the corresponding theory under widely satisfied conditions.The theoretical results provide new insights into the balance properties of covariate-adaptive randomization procedures and make foundations for most existing statistical inferences under two-arm covariate-adaptive randomization.Furthermore,these open a door to study the theoretical properties of statistical inferences for clinical trials based on multi-arm covariateadaptive randomization procedures.
基金partly supported by National Natural Science Foundation of China[GrantNumber 11801559],[Grant Number 12031005].
文摘In the past decade,significant progress has been made regarding inference under covariate-adaptive randomisation.We thank Prof.Shao for a timely review of the growing literature about the topic.The paper is focused on the most important and commonly used class of covariate-adaptive randomisation methods,i.e.,those balancing discrete covariates.The recent advances in robust inference are emphasised and discussed in detail.Several types of outcomes,such as continuous and time-to-event data,are covered.We here provide some additional recent results from the following five perspectives.
