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An easily accessible Web-based minimization random allocation system for clinical trials
Lan Xiao1, Qiwen Huang, Veronica Yank
1Research Institute, Palo Alto Medical Foundation, Palo Alto, CA, United States.
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.
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