Evidence map›Paper›PMID 26772804›Full record

ReviewBMC medical research methodology2016

Assessing variability in results in systematic reviews of diagnostic studies.

Christiana A Naaktgeboren, Eleanor A Ochodo, Wynanda A Van Enst, Joris A H de Groot, Lotty Hooft, Mariska M G Leeflang, Patrick M Bossuyt, Karel G M Moons, Johannes B Reitsma

Abstract readReview
In one paragraph

Review in BMC medical research methodology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 11 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 11 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

17 citing papers in PubMed, 11 syntheses or guidelines pooled it.

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  8. C-reactive protein for diagnosing late-onset infection in newborn infants.The Cochrane database of systematic reviews · 2019
    Pooled it
  9. Use of risk assessment instruments to predict violence in forensic psychiatric hospitals: a systematic review and meta-analysis.European psychiatry : the journal of the Association of European Psychiatrists · 2018
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  12. Evaluation of the clinical utility of medical tests in chronic urticaria.The journal of allergy and clinical immunology. Global · 2026
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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

9 authors.

Christiana A NaaktgeborenJulius Center for Health Sciences and Primary Care, University Medical Center, Universiteitsweg 100, Utrecht, 3584 CG, The Netherlands. c.naaktgeboren@umcutrecht.nl.
Eleanor A OchodoDepartment of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, Amsterdam, The Netherlands.
Wynanda A Van EnstDepartment of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, Amsterdam, The Netherlands.
Joris A H de GrootJulius Center for Health Sciences and Primary Care, University Medical Center, Universiteitsweg 100, Utrecht, 3584 CG, The Netherlands.
Lotty HooftDutch Cochrane Centre, Academic Medical Center, Amsterdam, The Netherlands.
Mariska M G LeeflangDepartment of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, Amsterdam, The Netherlands.
Patrick M BossuytDutch Cochrane Centre, Academic Medical Center, Amsterdam, The Netherlands.
Karel G M MoonsJulius Center for Health Sciences and Primary Care, University Medical Center, Universiteitsweg 100, Utrecht, 3584 CG, The Netherlands.
Johannes B ReitsmaJulius Center for Health Sciences and Primary Care, University Medical Center, Universiteitsweg 100, Utrecht, 3584 CG, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo describe approaches used in systematic reviews of diagnostic test accuracy studies for assessing variability in estimates of accuracy between studies and to provide guidance in this area.

methodsMeta-analyses of diagnostic test accuracy studies published between May and September 2012 were systematically identified. Information on how the variability in results was investigated was extracted.

resultsOf the 53 meta-analyses included in the review, most (n=48; 91%) presented variability in diagnostic accuracy estimates visually either through forest plots or ROC plots and the majority (n=40; 75%) presented a test or statistical measure for the variability. Twenty-eight reviews (53%) tested for variability beyond chance using Cochran's Q test and 31 (58%) reviews quantified it with I(2). 7 reviews (13%) presented between-study variance estimates (τ(2)) from random effects models and 3 of these presented a prediction interval or ellipse to facilitate interpretation. Half of all the meta-analyses specified what was considered a significant amount of variability (n=24; 49%).

conclusionsApproaches to assessing variability in estimates of accuracy varied widely between diagnostic test accuracy reviews and there is room for improvement. We provide initial guidance, complemented by an overview of the currently available approaches.

Indexed as

Meta-Analysis as TopicReview Literature as TopicAnalysis of VarianceDiagnostic Tests, RoutineHumansPublicationsReproducibility of ResultsROC Curve

Identifiers

PMID26772804
PMCPMC4714528

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.