Evidence map›Paper›PMID 40878807›Full record

ArticleJournal of evidence-based medicine2025

Examining and Interpreting Doi Plot Asymmetry in Meta-Analyses of Randomized Controlled Trials.

Luis Furuya-Kanamori, Xanthoula Rousou, Polychronis Kostoulas, Suhail A R Doi

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of evidence-based medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 7 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

16 citing papers in PubMed, 7 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

4 authors.

Luis Furuya-KanamoriUQ Centre for Clinical Research, Faculty of Health, Medicine and Behavioural Sciences, The University of Queensland, Herston, Australia.ORCID https://orcid.org/0000-0002-4337-9757
Xanthoula RousouLaboratory of Epidemiology, Applied Artificial Intelligence & Biostatistics, School of Health Sciences, Faculty of Public and One Health, University of Thessaly, Karditsa, Greece.
Polychronis KostoulasLaboratory of Epidemiology, Applied Artificial Intelligence & Biostatistics, School of Health Sciences, Faculty of Public and One Health, University of Thessaly, Karditsa, Greece.
Suhail A R DoiDepartment of Population Medicine, College of Medicine, QU Health, Qatar University, Doha, Qatar.

Funding

Qatar National Research Fund NPRP-BSRA01-0406-210030University of Queensland's Amplify Initiative
6 · The paper itself

Abstract

Systematic reviews and meta-analyses are considered the highest level of evidence, but their reliability can be undermined by publication bias. Traditional methods for assessing publication bias, such as funnel plots and p-value-based tests (e.g., Egger test), have notable limitations, including reliance on subjective interpretation and dependence on the number of studies included in a meta-analysis (k). The Doi plot and LFK index offer promising alternatives, providing improved visualization and quantification of plot asymmetry. This study revisits the application of the Doi plot and LFK index for detecting publication bias, addresses recent criticisms, and evaluates their performance compared to p-value-based methods using simulation study. Simulations included scenarios with varying study numbers (k = 5, 10, 20, 50), study sample sizes (small, large), and simulated bias level (ρ = 0, -0.3, -0.5, -0.9) generated using the Copas selection model. Diagnostic performance metrics (i.e., sensitivity and specificity) were estimated and compared for the LFK index and Egger test. The LFK index exhibited consistent higher sensitivity across varying k and simulated bias levels. In contrast, the Egger test was highly dependent on k, with sensitivity declining sharply in small meta-analyses (k < 20). Specificity of the LFK index adjusted with random error, while Egger test specificity remained fixed at ∼90%. The Doi plot and LFK index effectively address the limitations of traditional methods, offering robust k-independent performance and more reliable detection of publication bias. These findings support a transition to the Doi plot and LFK index for publication bias assessment in meta-analyses.

Indexed as

Meta-Analysis as TopicPublication BiasRandomized Controlled Trials as TopicData Interpretation, StatisticalHumansReproducibility of ResultsDoi plotEggers pfunnel plotLFK indexmeta‐analysispublication bias

Identifiers

PMID40878807
PMCPMC12506948

What Socratic holds

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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 Socratic graph.