Systematic Analysis of Publication Bias in Neurosurgery Meta-Analyses

Qi Sheng Phua, Lucy Lu, Marguerite Harding, Santosh Isaac Poonnoose, Alistair Jukes, Minh-Son To

Research output: Contribution to journalReview articlepeer-review

4 Citations (Scopus)


BACKGROUND: Statistically significant positive results are more likely to be published than negative or insignificant outcomes. This phenomenon, also termed publication bias, can skew the interpretation of meta-analyses. The widespread presence of publication bias in the biomedical literature has led to the development of various statistical approaches, such as the visual inspection of funnel plots, Begg test, and Egger test, to assess and account for it.

OBJECTIVE: To determine how well publication bias is assessed for in meta-analyses of the neurosurgical literature. 

METHODS: A systematic search for meta-analyses from the top neurosurgery journals was conducted. Data relevant to the presence, assessment, and adjustments for publication bias were extracted. 

RESULTS: The search yielded 190 articles. Most of the articles (n = 108, 56.8%) were assessed for publication bias, of which 40 (37.0%) found evidence for publication bias whereas 61 (56.5%) did not. In the former case, only 11 (27.5%) made corrections for the bias using the trim-and-fill method, whereas 29 (72.5%) made no correction. Thus, 111 meta-analyses (58.4%) either did not assess for publication bias or, if assessed to be present, did not adjust for it.

CONCLUSION: Taken together, these results indicate that publication bias remains largely unaccounted for in neurosurgical meta-analyses.

Original languageEnglish
Pages (from-to)262-269
Number of pages8
Issue number3
Publication statusPublished - Mar 2022


  • Neurosurgery
  • neurosurgical procedures
  • publication bias
  • research design


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