Evidence map›Paper›PMID 39522026›Full record

ArticleBMC medical research methodology2024

The optimal approach for retrieving systematic reviews was achieved when searching MEDLINE and Epistemonikos in addition to reference checking: a methodological validation study.

Lena Heinen, Käthe Goossen, Carole Lunny, Julian Hirt, Livia Puljak, Dawid Pieper

Abstract readValidation Study
In one paragraph

Article in BMC medical research methodology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

  1. Pooled it
  2. Article
  3. Article
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.

Lena HeinenInstitute for Health Economics and Clinical Epidemiology (IGKE), School of Medicine, University of Cologne, Cologne, Germany.
Käthe GoossenInstitute for Research in Operative Medicine (IFOM), Faculty of Health, School of Medicine, Witten/Herdecke University, Ostmerheimer Str. 200, 51109, Cologne, Germany. kaethe.goossen@uni-wh.de.ORCID 0000-0002-1436-1144
Carole LunnyKnowledge Translation Program, Unity Health Toronto and the Cochrane Hypertension Review Group, St Michael's Hospital, University of British Columbia, Vancouver, Canada.ORCID 0000-0002-7825-6765
Julian HirtDepartment of Health, Eastern Switzerland University of Applied Sciences, St. Gallen, Switzerland.ORCID 0000-0001-6589-3936
Livia PuljakCenter for Evidence-Based Medicine and Healthcare, Catholic University of Croatia, Zagreb, Croatia.ORCID 0000-0002-8467-6061
Dawid PieperFaculty of Health Sciences Brandenburg, Brandenburg Medical School (Theodor Fontane), Institute for Health Services and Health System Research, Rüdersdorf, Germany.ORCID 0000-0002-0715-5182

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSystematic reviews (SRs) are used to inform clinical practice guidelines and healthcare decision making by synthesising the results of primary studies. Efficiently retrieving as many relevant SRs as possible is challenging with a minimum number of databases, as there is currently no guidance on how to do this optimally. In a previous study, we determined which individual databases contain the most SRs, and which combination of databases retrieved the most SRs. In this study, we aimed to validate those previous results by using a different, larger, and more recent set of SRs.

methodsWe obtained a set of 100 Overviews of Reviews that included a total of 2276 SRs. SR inclusion was assessed in MEDLINE, Embase, and Epistemonikos. The mean inclusion rates (% of included SRs) and corresponding 95% confidence intervals were calculated for each database individually, as well as for combinations of MEDLINE with each other database and reference checking. Features of SRs not identified by the best database combination were reviewed qualitatively.

resultsInclusion rates of SRs were similar in all three databases (mean inclusion rates in % with 95% confidence intervals: 94.3 [93.9-94.8] for MEDLINE, 94.4 [94.0-94.9] for Embase, and 94.4 [93.9-94.9] for Epistemonikos). Adding reference checking to MEDLINE increased the inclusion rate to 95.5 [95.1-96.0]. The best combination of two databases plus reference checking consisted of MEDLINE and Epistemonikos (98.1 [97.7-98.5]). Among the 44/2276 SRs not identified by this combination, 34 were published in journals from China, four were other journal publications, three were health agency reports, two were dissertations, and one was a preprint. When discounting the journal publications from China, the SR inclusion rate in the recommended combination (MEDLINE, Epistemonikos and reference checking) was even higher than in the previous study (99.6 vs. 99.2%).

conclusionsA combination of databases and reference checking was the best approach to searching for biomedical SRs. MEDLINE and Epistemonikos, complemented by checking the references of the included studies, was the most efficient and produced the highest recall. However, our results point to the presence of geographical bias, because some publications in journals from China were not identified. STUDY REGISTRATION: https://doi.org/10.17605/OSF.IO/R5EAS (Open Science Framework).

Indexed as

Information Storage and RetrievalDatabases, BibliographicHumansMEDLINESystematic Reviews as TopicDatabasesEvidence synthesisGeographical biasInformation specialistOverview of reviewReview methodsSearch strategySystematic reviewsUmbrella review

Identifiers

PMID39522026
PMCPMC11549827

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.