Dynamic balancing randomization in controlled clinical trials

Héritier, Stéphane; Gebski, Val; Pillai, Avinesh

doi:10.1002/sim.2421

Cited by 58 publications

(65 citation statements)

References 15 publications

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“…Conversely, improving efficiency by increasing balance may have a non-trivial impact on reducing trial costs. Therefore, measures of imbalance have been used as a criterion to compare the efficiency of simple randomization with other allocation techniques [11]. Other ways to increase statistical power in trials include targeted patient selection and use of covariate-adjusted analysis [12], but these approaches are outside the scope of this paper.…”

Section: Reviewmentioning

confidence: 99%

Allocation techniques for balance at baseline in cluster randomized trials: a methodological review

Ivers

Halperin

Barnsley

et al. 2012

Trials

186

206

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Reviews have repeatedly noted important methodological issues in the conduct and reporting of cluster randomized controlled trials (C-RCTs). These reviews usually focus on whether the intracluster correlation was explicitly considered in the design and analysis of the C-RCT. However, another important aspect requiring special attention in C-RCTs is the risk for imbalance of covariates at baseline. Imbalance of important covariates at baseline decreases statistical power and precision of the results. Imbalance also reduces face validity and credibility of the trial results. The risk of imbalance is elevated in C-RCTs compared to trials randomizing individuals because of the difficulties in recruiting clusters and the nested nature of correlated patient-level data. A variety of restricted randomization methods have been proposed as way to minimize risk of imbalance. However, there is little guidance regarding how to best restrict randomization for any given C-RCT. The advantages and limitations of different allocation techniques, including stratification, matching, minimization, and covariate-constrained randomization are reviewed as they pertain to C-RCTs to provide investigators with guidance for choosing the best allocation technique for their trial.

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Section: Reviewmentioning

confidence: 99%

Allocation techniques for balance at baseline in cluster randomized trials: a methodological review

Ivers

Halperin

Barnsley

et al. 2012

Trials

186

206

View full text Add to dashboard Cite

show abstract

“…Many authors have proposed, and continue to propose, modifications to these algorithms (Wei, 1977; Begg and Iglewicz, 1990; Heritier et al , 2005; Perry et al , 2010). While some of these methods may modestly increase efficiency, most are rarely used.…”

Section: What Is Dynamic Allocation?mentioning

confidence: 99%

Statistical issues in the use of dynamic allocation methods for balancing baseline covariates

Pond

2011

Br J Cancer

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Background:The procedure for allocating patients to a treatment arm in comparative clinical trials is frequently chosen with only minor deliberation. This decision may, however, ultimately impact the trial inference, credibility, and even validity of the trial analysis. Cancer researchers are increasingly using dynamic allocation (DA) procedures, which balance treatment arms across baseline prognostic factors for clinical trials in place of historical methods such as simple randomisation or allocation via the random permuted blocks.Methods:This article gives an overview of DA methods, the statistical controversy that surrounds these procedures, and the potential impact on a clinical trial results.Results:Simple examples are provided to illustrate the use of DA methods and the inferential mistakes, notably on the P-value, if incorrect analyses are performed.Interpretation:The decision about which method to use for allocating patients should be given as much consideration as other aspects of a clinical trial. Appropriately choosing between methods can affect the statistical tests required and what inferences are possible, while affecting the trial credibility. Knowledge of the different methods is key to appropriate decision-making.

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“…Stratified permuted block (SPB) randomization and Pocock and Simon's design (1975) are the most popular CAR procedures. Other CAR designs have been developed by Taves (1974), Wei (1978), Nordle and Brantmark (1977), Signorini et al (1993), Heritier et al (2005), and Hu and Hu (2012). Clinical trials that use these designs include Iacono et al (2006), Jakob et al (2012), Anderson et al (2000), Gridelli et al (2003), Krueger et al (2007), Molander et al (2007, and Ohtori et al (2012).…”

Section: Introductionmentioning

confidence: 99%

Sequential Monitoring of Covariate-Adaptive Randomized Clinical Trials

Hu¹,

Hu²

2018

STAT SINICA

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The sequential monitoring of covariate-adaptive randomized clinical trials is standard in modern clinical studies. However, the validity of this sequential procedure is not well studied in the literature. Clinical trialists therefore implement the procedure and perform data analysis based on the theory of the sequential monitoring of fixed designs, and many clinical trials are open to question. In this paper, we study the theoretical properties of the sequential procedure and propose some important adjustments to classical statistical inference. Under different scenarios, we derive the asymptotic joint distribution of the sequential test statistics. Further, we estimate the decreased variability of the estimated treatment effect due to covariate-adaptive randomization, so that the sequential test statistics can be adjusted to be an asymptotic Brownian motion and the type I error rate can be controlled in real trials. Numerical results from simulation and the redesign of a clinical trial support our theoretical findings, showing that our procedure can control the type I error rate well, and also demonstrating the advantages of our method in terms of power and early stopping. Both theoretical and numerical results provide important guidance for future practical clinical trials using covariate-adaptive randomization procedures.

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Dynamic balancing randomization in controlled clinical trials

Cited by 58 publications

References 15 publications

Allocation techniques for balance at baseline in cluster randomized trials: a methodological review

Allocation techniques for balance at baseline in cluster randomized trials: a methodological review

Statistical issues in the use of dynamic allocation methods for balancing baseline covariates

Sequential Monitoring of Covariate-Adaptive Randomized Clinical Trials

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