Evidence map›Paper›PMID 31138319›Full record

ArticleTrials2019

Choosing an imbalance metric for covariate-constrained randomization in multiple-arm cluster-randomized trials.

Jody D Ciolino, Alicia Diebold, Jessica K Jensen, Gerald W Rouleau, Kimberly K Koloms, Darius Tandon

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Trials, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02979444 (Comparing the Effectiveness of Clinicians and Paraprofessionals to Reduce Disparities in Perinatal Depression), which is not on this map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.7field-weighted citation impact, top 14% 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.

NCT02979444 nacompletednot on this map

Comparing the Effectiveness of Clinicians and Paraprofessionals to Reduce Disparities in Perinatal Depression

TypeinterventionalSponsorNorthwestern UniversityRan2016 to 2020Enrolled874ConditionsPerinatal Depression, PostPartum DepressionArmsMothers and Babies Groups
3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 16 citations in OpenAlex.

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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

6 authors at 3 institutions in 1 country.

Jody D CiolinoDepartment of Preventive Medicine, Division of Biostatistics, Feinberg School of Medicine, Northwestern University, 680 N Lake Shore Drive, Suite 1400, Chicago, IL, 60611, USA. jody.ciolino@northwestern.edu.ORCID http://orcid.org/0000-0002-9060-5657
Alicia DieboldCenter for Community Health, Institute for Public Health and Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Jessica K JensenCenter for Community Health, Institute for Public Health and Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Gerald W RouleauCollege of Medicine, University of Cincinnati, Cincinnati, OH, USA.
Kimberly K KolomsHill-Rom Inc., Chicago, IL, USA.
Darius TandonCenter for Community Health, Institute for Public Health and Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Northwestern University · USHillrom (United States) · USUniversity of Cincinnati Medical Center · US

Funding

Northwestern University Clinical and Translational Science Institute (NUCATS)UL1TR001422 · NCATS · NORTHWESTERN UNIVERSITY AT CHICAGO · PI D'AQUILA, RICHARD · 2015 to 2023
$56.8M
NCATS NIH HHS UL1 TR001422Patient-Centered Outcomes Research Institute AD-1507-31473
6 · The paper itself

Abstract

backgroundIn cluster-randomized controlled trials (C-RCTs), covariate-constrained randomization (CCR) methods efficiently control imbalance in multiple baseline cluster-level variables, but the choice of imbalance metric to define the subset of "adequately balanced" possible allocation schemes for C-RCTs involving more than two arms and continuous variables is unclear. In an ongoing three-armed C-RCT, we chose the min(three Kruskal-Wallis [KW] test P values) > 0.30 as our metric. We use simulation studies to explore the performance of this and other metrics of baseline variable imbalance in CCR.

methodsWe simulated three continuous variables across three arms under varying allocation ratios and assumptions. We compared the performance of min(analysis of variance [ANOVA] P value) > 0.30, min(KW P value) > 0.30, multivariate analysis of variance (MANOVA) P value > 0.30, min(nine possible t test P values) > 0.30, and min(Wilcoxon rank-sum [WRS] P values) > 0.30.

resultsPairwise comparison metrics (t test and WRS) tended to be the most conservative, providing the smallest subset of allocation schemes (10%-13%) meeting criteria for acceptable balance. Sensitivity of the min(t test P values) > 0.30 for detecting non-trivial imbalance was 100% for both hypothetical and resampled simulation scenarios. The KW criterion maintained higher sensitivity than both the MANOVA and ANOVA criteria (89% to over 99%) but was not as sensitive as pairwise criteria.

conclusionsOur criterion, the KW P value > 0.30, to signify "acceptable" balance was not the most conservative, but it appropriately identified imbalance in the majority of simulations. Since all are related, CCR algorithms involving any of these imbalance metrics for continuous baseline variables will ensure robust simultaneous control over multiple continuous baseline variables, but we recommend care in determining the threshold of "acceptable" levels of (im)balance.

trial registrationThis trial is registered on ClinicalTrials.gov (initial post: December 1, 2016; identifier: NCT02979444 ).

Indexed as

Random AllocationAlgorithmsCluster AnalysisComputer SimulationHumansRandomized Controlled Trials as TopicCluster randomizationCluster-randomized controlled trialContinuous covariateCovariate-constrained randomizationImbalance

Identifiers

PMID31138319
PMCPMC6537428
OpenAlexW2947482359

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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.