Evidence map›Paper›PMID 23324166›Full record

ArticleTrials2013

Introduction to a generalized method for adaptive randomization in trials.

Zoë S J Hoare, Christopher J Whitaker, Rhiannon Whitaker

Open access · goldAbstract read
In one paragraph

Article in Trials, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 28% of its field
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

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Randomized Controlled Trials 1: Design.Methods in molecular biology (Clifton, N.J.) · 2021
    Article
  2. Article
  3. How to design a randomised controlled trial.British dental journal · 2017
    Article
  4. 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

3 authors at 1 institution in 1 country.

Zoë S J HoareNWORTH Bangor Clinical Trials Unit, Institute of Medical & Social Care Research, Y Wern, Holyhead Road, George Site, Bangor University, Bangor, LL57 2PZ, GwyneddUK. z.hoare@bangor.ac.uk
Christopher J Whitaker
Rhiannon Whitaker
Bangor University · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIdeally clinical trials should use some form of randomization for allocating participants to the treatment groups under trial. As an integral part of the process of assessing the effectiveness of these treatment groups, randomization performed well can reduce, if not eliminate, some forms of bias that can be evident in non-randomized trials. Given the vast set of possible randomization methods to choose from we demonstrate a method that incorporates many of the advantages of these other methods.

methodsA step-by-step introduction of how to use the adaptive randomization algorithm for conducting a clinical trial is given.

resultsThe implications, effects and capabilities of using the adaptive randomization algorithm are fully demonstrated and explained using simulated data and examples from actual trials.

conclusionsThis paper provides an introduction to a dynamic type of treatment allocation, which fulfills the CONSORT requirements of participants being randomly allocated whilst maintaining a level of control of the balances overall, within the stratification variables and within the strata simultaneously. Maintaining control of the imbalances within the groups is vital particularly if interim analyses are planned.

trial registrationCurrent controlled trials ISRCTN17551624, ISRCTN37558856, ISRCTN97185214.

Indexed as

Models, StatisticalRandom AllocationAlgorithmsBiasComputer SimulationFemaleHumansMaleRandomized Controlled Trials as TopicSex Factors

Identifiers

PMID23324166
PMCPMC3554542
OpenAlexW1970148349

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.