Evidence map›Paper›PMID 37438749›Full record

ArticlePediatric rheumatology online journal2023

The successes and challenges of harmonising juvenile idiopathic arthritis (JIA) datasets to create a large-scale JIA data resource.

Saskia Lawson-Tovey, Samantha Louise Smith, Nophar Geifman, Stephanie Shoop-Worrall, Sandra Ng, Michael R Barnes, Lucy R Wedderburn, Kimme L Hyrich, CLUSTER consortium

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Pediatric rheumatology online journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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. Review
  2. Review
  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

9 authors.

Saskia Lawson-ToveyCentre for Genetics and Genomics Versus Arthritis, The University of Manchester, Manchester, UK. saskia.lawson-tovey@manchester.ac.uk.ORCID http://orcid.org/0000-0002-8611-162X
Samantha Louise SmithCentre for Genetics and Genomics Versus Arthritis, The University of Manchester, Manchester, UK.ORCID http://orcid.org/0000-0002-4108-8497
Nophar GeifmanSchool of Health Sciences, Faculty of Health and Medical Sciences, The University of Surrey, Guildford, UK.ORCID http://orcid.org/0000-0003-2956-6676
Stephanie Shoop-WorrallCentre for Epidemiology Versus Arthritis, The University of Manchester, Manchester, UK.ORCID http://orcid.org/0000-0002-9441-5535
Sandra NgCentre for Translational Bioinformatics, William Harvey Research Institute, Bart's and the London School of Medicine and Dentistry, Queen Mary University London, London, UK.ORCID http://orcid.org/0000-0003-4524-6058
Michael R BarnesCentre for Translational Bioinformatics, William Harvey Research Institute, Bart's and the London School of Medicine and Dentistry, Queen Mary University London, London, UK.ORCID http://orcid.org/0000-0001-9097-7381
Lucy R WedderburnCentre for Adolescent Rheumatology Versus Arthritis at UCL, University College London Hospitals and Great Ormond Street Hospital, London, UK.ORCID http://orcid.org/0000-0002-7495-1429
Kimme L HyrichNational Institute of Health Research Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.ORCID http://orcid.org/0000-0001-8242-9262
CLUSTER consortium

Funding

Medical Research Council MR/M004600/1Medical Research Council MR/R013926/1Versus Arthritis 22084
6 · The paper itself

Abstract

backgroundCLUSTER is a UK consortium focussed on precision medicine research in JIA/JIA-Uveitis. As part of this programme, a large-scale JIA data resource was created by harmonizing and pooling existing real-world studies. Here we present challenges and progress towards creation of this unique large JIA dataset.

methodsFour real-world studies contributed data; two clinical datasets of JIA patients starting first-line methotrexate (MTX) or tumour necrosis factor inhibitors (TNFi) were created. Variables were selected based on a previously developed core dataset, and encrypted NHS numbers were used to identify children contributing similar data across multiple studies.

resultsOf 7013 records (from 5435 individuals), 2882 (1304 individuals) represented the same child across studies. The final datasets contain 2899 (MTX) and 2401 (TNFi) unique patients; 1018 are in both datasets. Missingness ranged from 10 to 60% and was not improved through harmonisation.

conclusionsCombining data across studies has achieved dataset sizes rarely seen in JIA, invaluable to progressing research. Losing variable specificity and missingness, and their impact on future analyses requires further consideration.

Indexed as

Arthritis, JuvenileChildHumansMethotrexatePrecision MedicineTumor Necrosis Factor InhibitorsMethotrexateTumor Necrosis Factor InhibitorsChildren and young peopleData harmonisationJIA

Identifiers

PMID37438749
PMCPMC10339614

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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.