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The appropriateness of asymmetry tests for publication bias in meta-analyses: a large survey
Open accessAbstract
BACKGROUND: Statistical tests for funnel-plot asymmetry are common in meta-analyses. Inappropriate application can generate misleading inferences about publication bias. We aimed to measure, in a survey of meta-analyses, how frequently the application of these tests would be not meaningful or inappropriate. METHODS: We evaluated all meta-analyses of binary outcomes with é 3 studies in the Cochrane Database of Systematic Reviews (2003, issue 2). A separate, restricted analysis was confined to the largest meta-analysis in each of the review articles. In each meta-analysis, we assessed whether criteria to apply asymmetry tests were met: no significant heterogeneity, I2 < 50%, é 10 studies (with statistically significant results in at least 1) and ratio of the maximal to minimal variance across studies > 4. We performed a correlation and 2 regression asymmetry tests and evaluated their concordance. Finally, we sampled 60 meta-analyses from print journals in 2005 that cited use of the standard regression test. RESULTS: A total of 366 of 6873 (5%) and 98 of 846 meta-analyses (12%) in the wider and restricted Cochrane data set, respectively, would have qualified for use of asymmetry tests. Asymmetry test results were significant in 7%-18% of the meta-analyses. Concordance between the 3 tests was modest (estimated k 0.33-0.66). Of the 60 journal meta-analyses, 7 (12%) would qualify for asymmetry tests; all 11 claims for identification of publication bias were made in the face of large and significant heterogeneity. INTERPRETATION: Statistical conditions for employing asymmetry tests for publication bias are absent from most meta-analyses; yet, in medical journals these tests are performed often and interpreted erroneously.
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“However, publication bias tests might be problematic for IN-OT studies due to small sample sizes resulting in insufficient statistical power and sample size variability for the tests to yield reliable and significant results (26).”
From Statistical and Methodological Considerations for the Interpretation of Intranasal Oxytocin Studies (2016) · cites this paper as [26]
Experimental — accuracy not yet measuredIn the citing paper
“The small number of studies and presence of significant heterogeneity precluded formal testing for publication bias[35].”
From Daily Sitting Time and All-Cause Mortality: A Meta-Analysis (2013) · cites this paper as [35]
In the citing paper
“Of 60 meta-analyses in 24 articles published in 2005 in which formal assessments were reported, most were based on fewer than ten studies; most displayed statistically significant heterogeneity; and many reviewers misinterpreted the results of the tests employed [123].”
From The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration (2009) · cites this paper as [123]
In the citing paper
“Although evidence that smaller studies had larger estimated effects than large ones may suggest the possibility that the available evidence is biased, misinterpretation of such data is common [123].”
From The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration (2009) · cites this paper as [123]
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Citations
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“32”
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“In addition, we planned to conduct asymmetry testing for publication bias provided that there were >10 studies in the meta-analysis and if statistical heterogeneity was <50%.(11)”
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“50 Unfortunately, these tests are often not applied appropriately, thereby negating any potential benefit that these statistical procedures may provide”
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“None of our datasets contained enough studies (n ≥ 10) to appropriately test for publication bias (Ionnidis and Trikalinos, 2007), so the extent to which our dataset differs from the overall existing body of relevant literature is unknown.”
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“19 The trim-and-fill method was used to estimate the adjusted pooled effect size accounting for publication bias.”
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“In a large survey evaluating all Cochrane Database of Systematic Reviews meta-analyses of binary outcomes with three or more studies, Ioannidis and Trikalinos find that most medical journal meta-analyses that use publication bias tests make this mistake: "Statistical conditions for employing asymmetry tests for public…”
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“The significance of Egger’s regression test ( p -value < 0.10) was taken into account in the case of at least 10 included studies [18].”
MethodInfluentialCaution is needed when 90% of all possible estimates remain unpublished: a comment on Arct et al.
Forstmeier, W. (2015) · Behavioral Ecology · doi:10.1093/beheco/arv044 · Cited by 6
da Silva, F., Pabalan, N., Ekaratcharoenchai, N., Neto, A. S., Christofolini, D. M., de Oliveira, R., Bianco, B. A. V., & Barbosa, C. P. (2018) · Genetic Testing and Molecular Biomarkers · doi:10.1089/gtmb.2017.0233 · Cited by 6
“Publication bias was not investigated because of the low sensitivity of the qualitative and quantitative tests when the number of studies is lower than ten (Ioannidis and Trikalinos, 2007).”
Acute exercise effects on postprandial fat oxidation: meta-analysis and systematic review
Pearson, R. C., Olenick, A., Green, E. S., & Jenkins, N. T. (2020) · Applied Physiology, Nutrition, and Metabolism · doi:10.1139/apnm-2019-0917 · Cited by 6
Gao, S., Xu, T., Mao, C., Cheng, J., Xun, C., Liang, W., & Sheng, W. (2021) · Immunological Investigations · doi:10.1080/08820139.2020.1869253 · Cited by 6
Berntsen, C. F., Rootwelt, P., & Dahm, A. E. A. (2021) · Research and Practice in Thrombosis and Haemostasis · doi:10.1002/rth2.12507 · Cited by 6
Tharabenjasin, P., Pabalan, N., Jarjanazi, H., & Jinawath, N. (2021) · Osteoporosis International · doi:10.1007/s00198-021-06161-5 · Cited by 6
Liu, B., Wang, Y., Liu, Y., Wu, P., & Li, T. (2021) · Acta cardiologica. Supplementum · doi:10.1080/00015385.2021.1989837 · Cited by 6
“05 as the threshold to indicate a significant risk of publication bias [15].”
BackgroundHu, W., Zhou, H., Zeng, Y., Zeng, Q., Huang, Z., & Chao, W. (2023) · Medicine · doi:10.1097/md.0000000000034842 · Cited by 6
Statistische Methoden zur Detektion und Adjustierung von Publikationsbias
Schwarzer, G., & Rücker, G. (2010) · Zeitschrift für Evidenz Fortbildung und Qualität im Gesundheitswesen · doi:10.1016/j.zefq.2010.03.016 · Cited by 6
Régnaux, J.-P., Trinquart, L., Boutron, I., Nguyen, C., Brosseau, L., & Ravaud, P. (2012) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd010203 · Cited by 6
Cleach, L. L., Trinquart, L., Lebrun‐Vignes, B., Giraudeau, B., & Chosidow, O. (2011) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd009036 · Cited by 6
Cove, B., Chalmers, S., Nelson, M. J., Anderson, M., & Bennett, H. (2024) · Journal of science and medicine in sport · doi:10.1016/j.jsams.2024.12.005 · Cited by 5
Wong, R. S. H., Ram, T. M. S., Xia, Y., Heng, E. Y., Jayabaskaran, J., Lim, Y. H., Yeo, B. S. Y., See, A., & Lim, C. M. (2025) · Otolaryngology · doi:10.1002/ohn.70009 · Cited by 5
“22,23 A two ‐ sided P ‐ value < .05 was considered statistically signi fi cant for all hypothesis tests.”
Woodward, A., Mason‐Jones, A. J., Faires, M., Jones, V. M., & Beaumont, A. J. (2025) · Journal of Science in Sport and Exercise · doi:10.1007/s42978-025-00343-x · Cited by 7
“This result, in conjunction with the Egger’s test and visual inspection of the funnel plot suggest that while small-study effects were present, publication bias may not be the sole factor respon - sible for the asymmetry, especially where heterogeneity is present [62].”
Evidence of additive genetic variation for major milk proteins in dairy cows: A meta‐analysis
Hossein‐Zadeh, N. G. (2024) · Journal of Animal Breeding and Genetics · doi:10.1111/jbg.12850 · Cited by 5
Yu, L., Xue, X., Zheng, S., Tao, W., Li, Q., Wang, Y., Gu, X., Sun, Y., Wang, R., & Hua, Y. (2024) · Sports Medicine and Health Science · doi:10.1016/j.smhs.2024.05.004 · Cited by 5
“41 Future studies need to follow a consistent methodological checklist, making the future review have high-quality evidence to pool.”
Ding, S., Hong, Q., Yao, Y., Gu, M., Cui, J., Li, W., Zhang, J., Zhang, C., Jiang, J., & Hu, Y. (2024) · Food & Function · doi:10.1039/d4fo02561j · Cited by 5
Jenwitheesuk, A., Pabalan, N., Tapanadechopone, P., Jarjanazi, H., Arunphalungsanti, K., & Tharabenjasin, P. (2025) · Brain and Behavior · doi:10.1002/brb3.70359 · Cited by 5
Feo, E. D., Simone, B., Kamgaing, R. S., Gallì, P., Hamajima, N., Hu, Z., Li, G., Li, Y., Matsuo, K., Park, J. Y., et al. (2011) · Mutagenesis · doi:10.1093/mutage/ger065 · Cited by 5
Regulatory activity based risk model identifies survival of stage II and III colorectal carcinoma
Liu, G., Dong, C., Wang, X., Hou, G., Zheng, Y., Xu, H., Zhan, X., & Liu, L. (2017) · Oncotarget · doi:10.18632/oncotarget.21312 · Cited by 5
“Publication bias was not investigated when the number of studies was less than 10 because of the low sensitivity of the qualitative and quantitative tests [16].”
Zhao, Y., Liu, W., Sun, M., Miao, Q., Liu, Y., Tian, H., Su, Y., & Han, F. (2019) · Critical Reviews in Oncology/Hematology · doi:10.1016/j.critrevonc.2019.01.017 · Cited by 5
Prognostic factors associated with left ventricular non-compaction: A PRISMA-compliant meta-analysis
Yang, Z.-G., Liu, Z.-J., Zhang, X.-X., & Wang, L. (2022) · Medicine · doi:10.1097/md.0000000000030337 · Cited by 5
“Publication bias was tested using Egger test.[13]”
Maida, M. F., Rizzo, G. E. M., Traina, M., Karstensen, J. G., Voermans, R. P., Gornals, J. B., Jagtap, N., Ligresti, D., Carrozza, L., Rancatore, G., et al. (2025) · Endoscopy · doi:10.1055/a-2577-3814 · Cited by 5
“In fact, in spite of the assessment that the funnel plots did not show asymmetry ( Fig.1s ), this evaluation may be subjective and statistical methods to test for asymmetry of the plot may lack power [28,29].”
Exercise therapy for ankylosing spondylitis
Régnaux, J.-P., Lefèvre‐Colau, M., Palazzo, C., Poiraudeau, S., Ravaud, P., & Boutron, I. (2014) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd011321 · Cited by 5
Metadata
- Authors
- Ioannidis, J. P. A., & Trikalinos, T. A.
- Affiliations
- Tufts University (US)
- Venue
- Canadian Medical Association Journal
- Publisher
- CMA Joule Inc.
- Published
- 2007-04-10
- Volume
- 176
- Issue
- 8
- Pages
- 1091-1096
- ISSN
- 0820-3946 (ISSN-L)
- 1488-2329
- PMC
- PMC1839799
- OpenAlex
- W2164093802
- Cited by
- 1,052
- References
- 40
- Citations by year
- 2026: 49 · 2025: 48 · 2024: 64 · 2023: 49 · 2022: 81 · 2021: 73 · 2020: 83 · 2019: 81 · 2018: 73 · 2017: 55 · 2016: 62 · 2015: 64 · 2014: 68 · 2013: 38 · 2012: 39
- FWCI
- 31.66
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Canadian Medical Association Journal (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Social Sciences › Library and Information Sciences › scientometrics and bibliometrics research
- Keywords
- publication bias, funnel plot asymmetry, meta-analysis, heterogeneity, Cochrane Database of Systematic Reviews, binary outcomes, test concordance
- MeSH terms
- Data Interpretation, Statistical, Humans, Periodicals as Topic, Meta-Analysis as Topic, Databases, Bibliographic, Publication Bias
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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