Evidence map›Paper›PMID 29879464›Full record

ArticleJournal of clinical epidemiology2018

Inadequate diversity of information resources searched in US-affiliated systematic reviews and meta-analyses: 2005-2016.

Richeek Pradhan, Kyle Garnick, Bikramjit Barkondaj, Harmon S Jordan, Arlene Ash, Hong Yu

Abstract read
In one paragraph

Article in Journal of clinical epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

6 authors.

Richeek PradhanDepartment of Quantitative Health Sciences, UMass Medical School, Worcester, MA, USA.
Kyle GarnickDepartment of Quantitative Health Sciences, UMass Medical School, Worcester, MA, USA.
Bikramjit BarkondajDepartment of Pharmacology, ESI Medical College, Kolkata, West Bengal, India.
Harmon S JordanDepartment of Quantitative Health Sciences, UMass Medical School, Worcester, MA, USA.
Arlene AshDepartment of Quantitative Health Sciences, UMass Medical School, Worcester, MA, USA.
Hong YuDepartment of Computer Science, University of Massachusetts Lowell, Lowell, MA, USA; Department of Medicine, UMass Medical School, Worcester, MA, USA; Department of Computer Science, University of Massachusetts Amherst, Amherst, MA, USA; Center for Healthcare Organization & Implementation Research, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA, USA. Electronic address: hong_yu@uml.edu.

Funding

EHR Anticoagulants PharmacovigilanceR01HL125089 · NHLBI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI YU, HONG · 2015 to 2019
$4.9M
NHLBI NIH HHS R01 HL125089
6 · The paper itself

Abstract

objectiveSystematic reviews and meta-analyses (SRMAs) rely upon comprehensive searches into diverse resources that catalog primary studies. However, since what constitutes a comprehensive search is unclear, we examined trends in databases searched from 2005-2016, surrounding the publication of search guidelines in 2013, and associations between resources searched and evidence of publication bias in SRMAs involving human subjects. STUDY

designTo ensure comparability of included SRMAs over the 12 years in the face of a near 100-fold increase of international SRMAs (mainly genetic studies from China) during this period, we focused on USA-affiliated SRMAs, manually reviewing 100 randomly selected SRMAs from those published in each year. After excluding articles (mainly for inadequate detail or out-of-scope methods), we identified factors associated with the databases searched, used network analysis to see which resources were simultaneously searched, and used logistic regression to link information sources searched with a lower chance of finding publication bias.

resultsAmong 817 SRMA articles studied, the common resources used were Medline (95%), EMBASE (44%), and Cochrane (41%). Methods journal SRMAs were most likely to use registries and grey literature resources. We found substantial co-searching of resources with only published materials, and not complemented by searches of registries and the grey literature. The 2013 guideline did not substantially increase searching of registries and grey literature resources to retrieve primary studies for the SRMAs. When used to augment Medline, Scopus (in all SRMAs) and ClinicalTrials.gov (in SRMAs with safety outcomes) were negatively associated with publication bias.

conclusionsEven SRMAs that search multiple sources tend to search similar resources. Our study supports searching Scopus and CTG in addition to Medline to reduce the chance of publication bias.

Indexed as

Meta-Analysis as TopicSystematic Reviews as TopicBiasHumansPublication BiasResearch DesignEvidence synthesisGrey literatureLiterature databasesMeta-analysisPublication biasSystematic reviewTrial registries

Identifiers

PMID29879464
PMCPMC6250602

What OpenQuestion holds

Textmetadata
LicenceTDM
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.