Evidence map›Paper›PMID 29057573›Full record

ArticleResearch synthesis methods2018

Practical guidance for using multiple data sources in systematic reviews and meta-analyses (with examples from the MUDS study).

Evan Mayo-Wilson, Tianjing Li, Nicole Fusco, Kay Dickersin, MUDS investigators

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Research synthesis methods, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 18 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 18 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

42 citing papers in PubMed, 18 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

5 authors.

Evan Mayo-WilsonDepartment of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD, 21205, USA.ORCID http://orcid.org/0000-0001-6126-2459
Tianjing LiDepartment of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD, 21205, USA.
Nicole FuscoDepartment of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD, 21205, USA.ORCID http://orcid.org/0000-0002-6355-4604
Kay DickersinDepartment of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD, 21205, USA.ORCID http://orcid.org/0000-0002-4604-7459
MUDS investigators

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Data for individual trials included in systematic reviews may be available in multiple sources. For example, a single trial might be reported in 2 journal articles and 3 conference abstracts. Because of differences across sources, source selection can influence the results of systematic reviews. We used our experience in the Multiple Data Sources in Systematic Reviews (MUDS) study, and evidence from previous studies, to develop practical guidance for using multiple data sources in systematic reviews. We recommend the following: (1) Specify which sources you will use. Before beginning a systematic review, consider which sources are likely to contain the most useful data. Try to identify all relevant reports and to extract information from the most reliable sources. (2) Link individual trials with multiple sources. Write to authors to determine which sources are likely related to the same trials. Use a modified Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) flowchart to document both the selection of trials and the selection of sources. (3) Follow a prespecified protocol for extracting trial characteristics from multiple sources. Identify differences among sources, and contact study authors to resolve differences if possible. (4) Prespecify outcomes and results to examine in the review and meta-analysis. In your protocol, describe how you will handle multiple outcomes within each domain of interest. Look for outcomes using all eligible sources. (5) Identify which data sources were included in the review. Consider whether the results might have been influenced by data sources used. (6) To reduce bias, and to reduce research waste, share the data used in your review.

Indexed as

Meta-Analysis as TopicReview Literature as TopicAminesBipolar DisorderClinical Trials as TopicCyclohexanecarboxylic AcidsData CollectionGabapentingamma-Aminobutyric AcidHumansInformation Storage and RetrievalNeuralgiaQuetiapine FumarateResearch ReportTreatment OutcomeAminesCyclohexanecarboxylic AcidsGabapentingamma-Aminobutyric AcidQuetiapine Fumaratemeta-analysismultiple data sourcesreporting biasrisk of bias assessmentselective outcome reporting

Identifiers

PMID29057573
PMCPMC5888128

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.