Literature DB >> 20060500

The use of minimization in clinical trials.

Donald R Taves1.   

Abstract

Since its introduction in 1974 the use of the term Minimization has been broadened to include other algorithms. All algorithms use patient characteristics to determine the assignment that produces the best overall balance between treatment groups. They differ in whether or not they use all of the data from each previously assigned subject to assign subsequent subjects so the methods are classified as complete or partial minimization. PubMed, Citation Index and Cochrane searches determined the frequency of articles using these types of minimization and a subset was selected for detailed review regarding the adequacy of the usage and reporting of minimization. In the past 10 years usage has increased three fold over the previous decade but is still less than 2% of clinical trials. None of the studies makes maximum use of minimization and they are not following good reporting practices. Concerns about the use of minimization have involved selection bias and statistical analysis. Several modifications to minimization are suggested to reduce the possibility of selection bias so that adding randomization will rarely be required. Separating primary and secondary analyses can avoid the statistical problems that minimization poses. The two types of analyses are distinguished by opposite limiting signs, providing reliable, simplified statistical results. This will improve data utilization and make clinical trials more reproducible. Minimization should be the method of choice in assigning subjects in all clinical trials. Copyright 2009 Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 20060500     DOI: 10.1016/j.cct.2009.12.005

Source DB:  PubMed          Journal:  Contemp Clin Trials        ISSN: 1551-7144            Impact factor:   2.226


  27 in total

1.  Minimization, by its nature, precludes allocation concealment, and invites selection bias.

Authors:  Vance W Berger
Journal:  Contemp Clin Trials       Date:  2010-05-10       Impact factor: 2.226

2.  A pilot randomized trial to prevent sexual dysfunction in postmenopausal breast cancer survivors starting adjuvant aromatase inhibitor therapy.

Authors:  Pragati Advani; Abenaa M Brewster; George P Baum; Leslie R Schover
Journal:  J Cancer Surviv       Date:  2017-02-22       Impact factor: 4.442

3.  Statistical properties of minimal sufficient balance and minimization as methods for controlling baseline covariate imbalance at the design stage of sequential clinical trials.

Authors:  Steven D Lauzon; Viswanathan Ramakrishnan; Paul J Nietert; Jody D Ciolino; Michael D Hill; Wenle Zhao
Journal:  Stat Med       Date:  2020-05-04       Impact factor: 2.373

4.  Validity and power of minimization algorithm in longitudinal analysis of clinical trials.

Authors:  Hua Weng; Randall Bateman; John C Morris; Chengjie Xiong
Journal:  Biostat Epidemiol       Date:  2017-06-13

5.  A better alternative to stratified permuted block design for subject randomization in clinical trials.

Authors:  Wenle Zhao
Journal:  Stat Med       Date:  2014-07-14       Impact factor: 2.373

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

Authors:  Jianhua Hu; Hongjian Zhu; Feifang Hu
Journal:  J Am Stat Assoc       Date:  2015-04-22       Impact factor: 5.033

7.  Michigan Initiative for Anterior Cruciate Ligament Rehabilitation (MiACLR): A Protocol for a Randomized Clinical Trial.

Authors:  Kazandra Rodriguez; Steven A Garcia; Cathie Spino; Lindsey K Lepley; Yuxi Pang; Edward Wojtys; Asheesh Bedi; Mike Angelini; Bethany Ruffino; Tyler Bolley; Corey Block; Jessica Kellum; Andrew Swartout; Riann M Palmieri-Smith
Journal:  Phys Ther       Date:  2020-12-07

8.  Effectiveness Guidance Document (EGD) for acupuncture research - a consensus document for conducting trials.

Authors:  Claudia M Witt; Mikel Aickin; Trini Baca; Dan Cherkin; Mary N Haan; Richard Hammerschlag; Jason Jishun Hao; George A Kaplan; Lixing Lao; Terri McKay; Beverly Pierce; David Riley; Cheryl Ritenbaugh; Kevin Thorpe; Sean Tunis; Jed Weissberg; Brian M Berman
Journal:  BMC Complement Altern Med       Date:  2012-09-06       Impact factor: 3.659

Review 9.  Allocation techniques for balance at baseline in cluster randomized trials: a methodological review.

Authors:  Noah M Ivers; Ilana J Halperin; Jan Barnsley; Jeremy M Grimshaw; Baiju R Shah; Karen Tu; Ross Upshur; Merrick Zwarenstein
Journal:  Trials       Date:  2012-08-01       Impact factor: 2.279

10.  Investigating the relationship between predictability and imbalance in minimisation: a simulation study.

Authors:  Gladys C McPherson; Marion K Campbell; Diana R Elbourne
Journal:  Trials       Date:  2013-03-27       Impact factor: 2.279

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