Evidence map›Paper›PMID 27484923›Full record

ArticleBMC medical informatics and decision making2016

Searching for rare diseases in PubMed: a blind comparison of Orphanet expert query and query based on terminological knowledge.

N Griffon, M Schuers, F Dhombres, T Merabti, G Kerdelhué, L Rollin, S J Darmoni

Open access · goldAbstract read
In one paragraph

Article in BMC medical informatics and decision making, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.2field-weighted citation impact, top 36% of its field
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

5 citing papers in PubMed, 21 citations in OpenAlex.

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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

7 authors at 2 institutions in 1 country.

N GriffonDepartment of Biomedical Informatics, Rouen University Hospital, TIBS, LITIS EA 4108, Rouen University, 76031, Rouen Cedex, France. nicolas.griffon@chu-rouen.fr.ORCID 0000-0002-9602-6429
M SchuersDepartment of Biomedical Informatics, Rouen University Hospital, TIBS, LITIS EA 4108, Rouen University, 76031, Rouen Cedex, France.
F DhombresINSERM, U1142, LIMICS, 75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06 UMR_S 1142, LIMICS, 75006, Paris, France; Univ Paris 13, Sorbonne Paris Cité, LIMICS (UMR_S 1142), 93430, Villetaneuse, France.
T MerabtiDepartment of Biomedical Informatics, Rouen University Hospital, TIBS, LITIS EA 4108, Rouen University, 76031, Rouen Cedex, France.
G KerdelhuéDepartment of Biomedical Informatics, Rouen University Hospital, TIBS, LITIS EA 4108, Rouen University, 76031, Rouen Cedex, France.
L RollinDepartment of Biomedical Informatics, Rouen University Hospital, TIBS, LITIS EA 4108, Rouen University, 76031, Rouen Cedex, France.
S J DarmoniDepartment of Biomedical Informatics, Rouen University Hospital, TIBS, LITIS EA 4108, Rouen University, 76031, Rouen Cedex, France.
Laboratoire d'Informatique, du Traitement de l'Information et des Systèmes · FRInserm · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite international initiatives like Orphanet, it remains difficult to find up-to-date information about rare diseases. The aim of this study is to propose an exhaustive set of queries for PubMed based on terminological knowledge and to evaluate it versus the queries based on expertise provided by the most frequently used resource in Europe: Orphanet.

methodsFour rare disease terminologies (MeSH, OMIM, HPO and HRDO) were manually mapped to each other permitting the automatic creation of expended terminological queries for rare diseases. For 30 rare diseases, 30 citations retrieved by Orphanet expert query and/or query based on terminological knowledge were assessed for relevance by two independent reviewers unaware of the query's origin. An adjudication procedure was used to resolve any discrepancy. Precision, relative recall and F-measure were all computed.

resultsFor each Orphanet rare disease (n = 8982), there was a corresponding terminological query, in contrast with only 2284 queries provided by Orphanet. Only 553 citations were evaluated due to queries with 0 or only a few hits. There were no significant differences between the Orpha query and terminological query in terms of precision, respectively 0.61 vs 0.52 (p = 0.13). Nevertheless, terminological queries retrieved more citations more often than Orpha queries (0.57 vs. 0.33; p = 0.01). Interestingly, Orpha queries seemed to retrieve older citations than terminological queries (p < 0.0001).

conclusionThe terminological queries proposed in this study are now currently available for all rare diseases. They may be a useful tool for both precision or recall oriented literature search.

Indexed as

Bibliographies as TopicPubMedRare DiseasesTerminology as TopicVocabulary, ControlledHumansBibliography as topicPubMedRare diseasesTerminology as topic

Identifiers

PMID27484923
PMCPMC4970261
OpenAlexW2479639685

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.