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


METHODS
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.


CONCLUSIONS
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.
Darong
D
Wu
Elie A
EA
Akl
Gordon H
GH
Guyatt
Philip J
PJ
Devereaux
Romina
R
Brignardello-Petersen
Barbara
B
Prediger
Krupesh
K
Patel
Namrata
N
Patel
Taoying
T
Lu
Yuan
Y
Zhang
Maicon
M
Falavigna
Nancy
N
Santesso
Reem A
RA
Mustafa
Qi
Q
Zhou
Matthias
M
Briel
Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, ON, Canada. schuneh@mcmaster.ca.
Holger J
HJ
Schünemann
D006801:Humans; D007258:Informed Consent; D055811:Journal Impact Factor; D016014:Linear Models; D018579:Patient Selection; D010506:Periodicals as Topic; D016032:Randomized Controlled Trials as Topic / Q000379:methods* / Q000706:statistics & numerical data; D012107:Research Design / Q000706:statistics & numerical data; D018401:Sample Size