Evidence map›Paper›PMID 25985892›Full record

ReviewJournal of clinical epidemiology2015

Many multicenter trials had few events per center, requiring analysis via random-effects models or GEEs.

Brennan C Kahan, Michael O Harhay

Abstract readReview
In one paragraph

Review in Journal of clinical epidemiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 2 pooled it
–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

32 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

2 authors.

Brennan C KahanPragmatic Clinical Trials Unit, Centre for Primary Care and Public Health, Queen Mary University of London, 58 Turner Street, London E1 2AB, UK. Electronic address: b.kahan@qmul.ac.uk.
Michael O HarhayDivision of Epidemiology, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, 708 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19146, USA.

Funding

Comparative Efficacy, Acceptance and Effectiveness of Health Incentive StructuresR01CA159932 · NCI · UNIVERSITY OF PENNSYLVANIA · PI HALPERN, SCOTT D · 2010 to 2014
$3.0M
Methods to improve the detection of treatment effects in ARDS clinical trialsF31HL127947 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI HARHAY, MICHAEL OSCAR · 2015 to 2016
$71k
NCI NIH HHS R01 CA159932NCI NIH HHS R01CA159932NHLBI NIH HHS F31 HL127947NHLBI NIH HHS F31HL127947
6 · The paper itself

Abstract

objectivesAdjustment for center in multicenter trials is recommended when there are between-center differences or when randomization has been stratified by center. However, common methods of analysis (such as fixed-effects, Mantel-Haenszel, or stratified Cox models) often require a large number of patients or events per center to perform well. STUDY DESIGN AND

settingWe reviewed 206 multicenter randomized trials published in four general medical journals to assess the average number of patients and events per center and determine whether appropriate methods of analysis were used in trials with few patients or events per center.

resultsThe median number of events per center/treatment arm combination for trials using a binary or survival outcome was 3 (interquartile range, 1-10). Sixteen percent of trials had less than 1 event per center/treatment combination, 50% fewer than 3, and 63% fewer than 5. Of the trials which adjusted for center using a method of analysis which requires a large number of events per center, 6% had less than 1 event per center-treatment combination, 25% fewer than 3, and 50% fewer than 5. Methods of analysis that allow for few events per center, such as random-effects models or generalized estimating equations (GEEs), were rarely used.

conclusionMany multicenter trials contain few events per center. Adjustment for center using random-effects models or GEE with model-based (non-robust) standard errors may be beneficial in these scenarios.

Indexed as

Data Interpretation, StatisticalModels, StatisticalBiasData CollectionHumansMulticenter Studies as TopicPatient Outcome AssessmentPeriodicals as TopicRandomized Controlled Trials as TopicSample SizeStatistics as TopicCenter effectsCovariate adjustmentGeneralized estimating equationsMulticenter trialRandom-effects modelsRandomized controlled trial

Identifiers

PMID25985892
PMCPMC4845666

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.