A Unified Family of Covariate-Adjusted Response-Adaptive Designs Based on Efficiency and Ethics

Hu, Jianhua; Zhu, Hongjian; Hu, Feifang

doi:10.1080/01621459.2014.903846

Cited by 35 publications

(43 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recently Hu and Hu (2012) discussed some limitations of these classical designs and proposed a generalized family of covariate-adaptive designs, and obtained their theoretical properties. For more discussion of handling covariates in clinical trials, see McEntegart (2003), Zhang et al (2007), Rosenberger and Sverdlov (2008), Hu, Zhu, and Hu (2014), and reference therein.…”

Section: Introductionmentioning

confidence: 99%

Testing Hypotheses of Covariate-Adaptive Randomized Clinical Trials

Ma¹,

Hu²,

Zhang³

2015

Journal of the American Statistical Association

Self Cite

View full text Add to dashboard Cite

Covariate-adaptive designs are often implemented to balance important covariates in clinical trials. However, the theoretical properties of conventional testing hypotheses are usually unknown under covariate-adaptive randomized clinical trials. In the literature, most studies are based on simulations. In this article, we provide theoretical foundation of hypothesis testing under covariate-adaptive designs based on linear models. We derive the asymptotic distributions of the test statistics of testing both treatment effects and the significance of covariates under null and alternative hypotheses. Under a large class of covariate-adaptive designs, (i) the hypothesis testing to compare treatment effects is usually conservative in terms of small Type I error; (ii) the hypothesis testing to compare treatment effects is usually more powerful than complete randomization; and (iii) the hypothesis testing for significance of covariates is still valid. The class includes most of the covariate-adaptive designs in the literature; for example, Pocock and Simon's marginal procedure, stratified permuted block design, etc. Numerical studies are also performed to assess their corresponding finite sample properties. Supplementary material for this article is available online.

show abstract

Section: Introductionmentioning

confidence: 99%

Testing Hypotheses of Covariate-Adaptive Randomized Clinical Trials

Ma¹,

Hu²,

Zhang³

2015

Journal of the American Statistical Association

Self Cite

View full text Add to dashboard Cite

show abstract

“…[19,48,50]) and for the parameters of the success probability p j (t) (see e.g. [24]). The connection between these two approaches is also highlighted in [24,Section 2.2].…”

Section: 3mentioning

confidence: 99%

Nonparametric covariate-adjusted response-adaptive design based on a functional urn model

Aletti¹,

Ghiglietti²,

Rosenberger³

2018

Ann. Statist.

View full text Add to dashboard Cite

In this paper we propose a general class of covariate-adjusted response-adaptive (CARA) designs based on a new functional urn model. We prove strong consistency concerning the functional urn proportion and the proportion of subjects assigned to the treatment groups, in the whole study and for each covariate profile, allowing the distribution of the responses conditioned on covariates to be estimated nonparametrically. In addition, we establish joint central limit theorems for the above quantities and the sufficient statistics of features of interest, which allow to construct procedures to make inference on the conditional response distributions. These results are then applied to typical situations concerning Gaussian and binary responses.MSC 2010 subject classifications: Primary 62L20, 60F05, 62E20, 62L05; secondary 62F12, 62P10

show abstract

“…Many bioethicists think the purpose of adaptive designs is to make research more ethical, but this view does not seem to be widely shared outside of bioethics. Some statisticians have argued for an ethical value to adaptive trials or have worked on specific adaptive methods to improve trial ethics by increasing patient allocation to effective treatments while maintaining study power . Yet other scientists have noted that adaptive designs can “provide a false sense of beneficence” by implying a preference to allocate subjects to the better‐performing arm, when adaptive trials are actually designed to improve efficiency irrespective of subject welfare, unless attention to subject welfare is explicitly included in the design .…”

Section: Pharmaceutical Trials and Adaptive‐design Ethicsmentioning

confidence: 99%

The Real‐World Ethics of Adaptive‐Design Clinical Trials

Bothwell¹,

Kesselheim²

2017

Hastings Center Report

View full text Add to dashboard Cite

From the earliest application of modern randomized controlled trials in medical research, scientists and observers have deliberated the ethics of randomly allocating study participants to trial control arms. Adaptive RCT designs have been promoted as ethically advantageous over conventional RCTs because they reduce the allocation of subjects to what appear to be inferior treatments. Critical assessment of this claim is important, as adaptive designs are changing medical research, with the potential to significantly shift how clinical trials are conducted. Policy-makers are swiftly moving to encourage greater use of adaptive designs. In 2016, the newly enacted 21st Century Cures Act instructed the Food and Drug Administration to help product sponsors incorporate adaptive methods into proposed clinical trial protocols and applications for investigational drugs and also biological products. In this article, we review the ethical justifications commonly offered for adaptive designs, explore these arguments in the context of actual trials, and contend that clinical equipoise is a useful standard for adaptive-trial ethics. We distinguish between theoretical and clinical equipoise and explain why ethical arguments related to adaptive trials tend to focus on the former. Yet we contend that theoretical equipoise can be an unreliable standard for adaptive ethics. While we contend that clinical equipoise is the most critical principle for the primary ethical concerns posed by adaptive trials, we suggest ethical approaches to deal with some additional concerns unique to adaptive designs.

show abstract

A Unified Family of Covariate-Adjusted Response-Adaptive Designs Based on Efficiency and Ethics

Cited by 35 publications

References 43 publications

Testing Hypotheses of Covariate-Adaptive Randomized Clinical Trials

Testing Hypotheses of Covariate-Adaptive Randomized Clinical Trials

Nonparametric covariate-adjusted response-adaptive design based on a functional urn model

The Real‐World Ethics of Adaptive‐Design Clinical Trials

Contact Info

Product

Resources

About