Evidence map›Paper›PMID 24456965›Full record

ArticleTrials2014

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

Darong Wu, Elie A Akl, Gordon H Guyatt, Philip J Devereaux, Romina Brignardello-Petersen, Barbara Prediger, Krupesh Patel, Namrata Patel, Taoying Lu, Yuan Zhang and 6 more

Abstract read
In one paragraph

Article in Trials, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Darong Wu
Elie A Akl
Gordon H Guyatt
Philip J Devereaux
Romina Brignardello-Petersen
Barbara Prediger
Krupesh Patel
Namrata Patel
Taoying Lu
Yuan Zhang
Maicon Falavigna
Nancy Santesso
Reem A Mustafa
Qi Zhou
Matthias Briel
Holger J SchünemannDepartment of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, ON, Canada. schuneh@mcmaster.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough 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.

methodsWe 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. DISCUSSION: 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.

Indexed as

Research DesignHumansInformed ConsentJournal Impact FactorLinear ModelsPatient SelectionPeriodicals as TopicRandomized Controlled Trials as TopicSample Size

Identifiers

PMID24456965
PMCPMC3902027

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.