Open Access Open Badges Study protocol

Methodological survey of designed uneven randomization trials (DU-RANDOM): a protocol

Darong Wu13, Elie A Akl234, Gordon H Guyatt3, Philip J Devereaux3, Romina Brignardello-Petersen56, Barbara Prediger7, Krupesh Patel8, Namrata Patel4, Taoying Lu1, Yuan Zhang3, Maicon Falavigna39, Nancy Santesso3, Reem A Mustafa10, Qi Zhou3, Matthias Briel11 and Holger J Schünemann3*

Author Affiliations

1 Department of Clinical Epidemiology, 2nd Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China

2 Departments of Internal Medicine, American University of Beirut, Beirut, Lebanon

3 Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, ON, Canada

4 Departments of Medicine, State University of New York at Buffalo, Buffalo, NY, USA

5 Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada

6 Faculty of Dentistry, University of Chile, Santiago, Chile

7 Department of Medical Biometry and Statistics, Albert-Ludwigs-University, Freiburg, Germany

8 Department of Biology (Physiology Specialization), McMaster University, Hamilton, ON, Canada

9 Epidemiology and Health Technology Assessment Institute, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil

10 Department of Internal Medicine, Division of Nephrology, University of Missouri Kansas City, Kansas City, MO, USA

11 Basel Institute for Clinical Epidemiology & Biostatistics, University Hospital Basel, Basel, CH, Switzerland

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Trials 2014, 15:33  doi:10.1186/1745-6215-15-33

Published: 23 January 2014



Although even randomization (that is, approximately 1:1 randomization ratio in study arms) provides the greatest statistical power, designed uneven randomization (DUR), (for example, 1:2 or 1:3) is used to increase participation rates. Until now, no convincing data exists addressing the impact of DUR on participation rates in trials. The objective of this study is to evaluate the epidemiology and to explore factors associated with DUR.


We will search for reports of RCTs published within two years in 25 general medical journals with the highest impact factor according to the Journal Citation Report (JCR)-2010. Teams of two reviewers will determine eligibility and extract relevant information from eligible RCTs in duplicate and using standardized forms. We will report the prevalence of DUR trials, the reported reasons for using DUR, and perform a linear regression analysis to estimate the association between the randomization ratio and the associated factors, including participation rate, type of informed consent, clinical area, and so on.


A clearer understanding of RCTs with DUR and its association with factors in trials, for example, participation rate, can optimize trial design and may have important implications for both researchers and users of the medical literature.

Participation rate; Designed uneven randomization trials; Trial participation