Evidence map›Paper›PMID 24849843›Full record

ArticleStatistics in medicine2014

Managing competing demands in the implementation of response-adaptive randomization in a large multicenter phase III acute stroke trial.

Wenle Zhao, Valerie Durkalski

Abstract read
In one paragraph

Article in Statistics in medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Trial
  4. Article
  5. Response-adaptive randomization in clinical trials: from myths to practical considerations.Statistical science : a review journal of the Institute of Mathematical Statistics · 2023
    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

2 authors.

Wenle ZhaoDepartment of Public Health Science, Medical University of South Carolina, 135 Cannon Street, Charleston, SC 29425, U.S.A.
Valerie Durkalski

Funding

The Stroke Hyperglycemia Insulin Network Effort (SHINE) TrialU01NS069498 · NINDS · UNIVERSITY OF VIRGINIA · PI BRUNO, ASKIEL, HALL, CHRISTIANA · 2011 to 2017
$27.7M
Neurological Emergencies Treatment Trials Network Statistical and Data ManagementU01NS059041 · NINDS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI DURKALSKI, VALERIE L, PALESCH, YUKO Y · 2006 to 2015
$9.1M
NINDS NIH HHS U01 NS059041NINDS NIH HHS U01 NS069498
6 · The paper itself

Abstract

It is well known that competing demands exist between the control of important covariate imbalance and protection of treatment allocation randomness in confirmative clinical trials. When implementing a response-adaptive randomization algorithm in confirmative clinical trials designed under a frequentist framework, additional competing demands emerge between the shift of the treatment allocation ratio and the preservation of the power. Based on a large multicenter phase III stroke trial, we present a patient randomization scheme that manages these competing demands by applying a newly developed minimal sufficient balancing design for baseline covariates and a cap on the treatment allocation ratio shift in order to protect the allocation randomness and the power. Statistical properties of this randomization plan are studied by computer simulation. Trial operation characteristics, such as patient enrollment rate and primary outcome response delay, are also incorporated into the randomization plan.

Indexed as

Bayes TheoremChi-Square DistributionClinical Trials, Phase III as TopicComputer SimulationHumansMulticenter Studies as TopicPatient SelectionRandomized Controlled Trials as TopicStrokeallocation randomnessallocation ratiocovariate balancingminimal sufficient balanceresponse-adaptive randomization

Identifiers

PMID24849843
PMCPMC4159417

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.