An Easily Accessible Web-Based Minimization Random Allocation System for Clinical Trials

BACKGROUND Minimization as an adaptive allocation technique has been recommended in the literature for use in randomized clinical trials. However, it remains uncommonly used due in part to a lack of easily accessible implementation tools. OBJECTIVE To provide clinical trialists with a robust, flexible, and readily accessible tool for implementing covariate-adaptive biased-coin randomization. METHODS We developed a Web-based random allocation system, MinimRan, that applies Pocock-Simon (for trials with 2 or more arms) and 2-way (currently limited to 2-arm trials) minimization methods for trials using only categorical prognostic factors or the symmetric Kullback-Leibler divergence minimization method for trials (currently limited to 2-arm trials) using continuous prognostic factors with or without categorical factors, in covariate-adaptive biased-coin randomization. RESULTS In this paper, we describe the system's essential statistical and computer programming features and provide as an example the randomization results generated by it in a recently completed trial. The system can be used in single- and double-blind trials as well as single-center and multicenter trials. CONCLUSIONS We expect the system to facilitate the translation of the 3 validated random allocation methods into broad, efficient clinical research practice.

[1]  Isao Yoshimura,et al.  Minimization method for balancing continuous prognostic variables between treatment and control groups using Kullback-Leibler divergence. , 2006, Contemporary clinical trials.

[2]  S. Pocock,et al.  Sequential treatment assignment with balancing for prognostic factors in the controlled clinical trial. , 1975, Biometrics.

[3]  Kouhei Akazawa,et al.  An easily customized, random allocation system using the minimization method for multi-Institutional clinical trials , 2000, Comput. Methods Programs Biomed..

[4]  Kerenza Hood,et al.  Balance algorithm for cluster randomized trials , 2008, BMC medical research methodology.

[5]  P van den Broek,et al.  The choice of a balanced allocation method for a clinical trial in otitis media with effusion. , 1990, Statistics in medicine.

[6]  B. Efron Forcing a sequential experiment to be balanced , 1971 .

[7]  Yasuo Ohashi,et al.  Statistical comparison of random allocation methods in cancer clinical trials. , 2004, Controlled clinical trials.

[8]  P. Lavori,et al.  Translating the Diabetes Prevention Program Lifestyle Intervention for Weight Loss into Primary Care a Randomized Trial , 2022 .

[9]  D. Taves Minimization does not by its nature preclude allocation concealment and invite selection bias, as Berger claims. , 2011, Contemporary clinical trials.

[10]  Leonard W. D'Avolio,et al.  A point-of-care clinical trial comparing insulin administered using a sliding scale versus a weight-based regimen , 2011, Clinical Trials (London, England).

[11]  Hong Wei Cai,et al.  Implementation and experience of a web-based allocation system with Pocock and Simon's minimization methods. , 2010, Contemporary clinical trials.

[12]  International conference on harmonisation; guidance on statistical principles for clinical trials; availability--FDA. Notice. , 1998, Federal register.

[13]  Marion K Campbell,et al.  The method of minimization for allocation to clinical trials. a review. , 2002, Controlled clinical trials.

[14]  Wen-Chung Lee,et al.  Two-Way Minimization: A Novel Treatment Allocation Method for Small Trials , 2011, PloS one.

[15]  Kenneth F Schulz,et al.  Blinding in randomised trials: hiding who got what , 2002, The Lancet.

[16]  Yongping Yan,et al.  A generic minimization random allocation and blinding system on web , 2006, J. Biomed. Informatics.

[17]  Mahmoud Saghaei,et al.  Implementation of an open-source customizable minimization program for allocation of patients to parallel groups in clinical trials , 2011 .

[18]  Damian McEntegart,et al.  The Pursuit of Balance Using Stratified and Dynamic Randomization Techniques: An Overview , 2003 .

[19]  Leonidas J. Guibas,et al.  The Earth Mover's Distance as a Metric for Image Retrieval , 2000, International Journal of Computer Vision.