Evidence map›Paper›PMID 32164791›Full record

SynthesisSystematic reviews2020

Journal impact factor, trial effect size, and methodological quality appear scantly related: a systematic review and meta-analysis.

Michael Saginur, Dean Fergusson, Tinghua Zhang, Karen Yeates, Tim Ramsay, George Wells, David Moher

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Systematic reviews, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 4 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

19 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. EJHP's impact factor moves on up.European journal of hospital pharmacy : science and practice · 2022
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
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

7 authors.

Michael SaginurMontfort Research Institute, 713 Montreal Road, Ottawa, Canada. misaginur@rogers.com.ORCID 0000-0002-6277-9924
Dean FergussonOttawa Hospital Research Institute, 501 Smyth Road, Ottawa, K1H 8L6, Canada.
Tinghua ZhangOttawa Hospital Research Institute, 501 Smyth Road, Ottawa, K1H 8L6, Canada.
Karen YeatesDepartment of Medicine, Queen's University, 76 Stuart Street, Kingston, K7L 2V7, Canada.
Tim RamsayOttawa Hospital Research Institute, 501 Smyth Road, Ottawa, K1H 8L6, Canada.
George WellsUniversity of Ottawa Heart Institute, 40 Ruskin St, Ottawa, ON, K1Y 4W7, Canada.
David MoherOttawa Hospital Research Institute, 501 Smyth Road, Ottawa, K1H 8L6, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs systematic reviews' limited coverage of the medical literature necessitates decision-making based on unsystematic review, we investigated a possible advantage of systematic review (aside from dataset size and systematic analysis): does systematic review avoid potential bias in sampling primary studies from high impact factor journals? If randomized controlled trials (RCTs) reported in higher-impact journals present different treatment benefits than RCTs reported in lower-impact journals, readers who focus on higher-impact journals for their rapid literature reviews may introduce bias which could be mitigated by complete, systematic sampling.

methodsWe randomly sampled Cochrane Library (20 July 2005) treatment reviews that measured mortality as a binary outcome, published in English or French, with at least five RCTs with one or more deaths. Our domain-based assessment of risk of bias included funding source, randomness of allocation sequence, blinding, and allocation concealment. The primary analysis employed logistic regression by a generalized linear model with a generalized estimating equation to estimate the association between various factors and publication in a journal with a high journal impact factor (JIF).

resultsFrom the 29 included systematic reviews, 189 RCTs contributed data. However, in the primary analyses comparing RCT results within meta-analyses, there was no statistically significant association: unadjusted odds of greater than 50% mortality protection in high-JIF (> 5) journals were 1.4 (95% CI 0.42, 4.4) and adjusted, 2.5 (95% CI 0.6, 10). Elements of study quality were weakly, inconsistently, and not statistically significantly correlated with journal impact factor.

conclusionsJournal impact factor may have little to no association with study results, or methodological quality, but the evidence is very uncertain.

Indexed as

Journal Impact FactorBiasHumansClinical trialJournal impact factorMeta-analysisPublication biasResearch designSystematic review

Identifiers

PMID32164791
PMCPMC7069162

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.