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Lawson-Tovey, Saskia; Smith, Samantha Louise; Geifman, Nophar; Shoop-Worrall, Stephanie; Ng, Sandra; Barnes, Michael R.; Wedderburn, Lucy R.; Hyrich, Kimme L.; Kartawinata, Melissa; Wanstall, Zoe; Jebson, Bethany R.; McNeece, Alyssia; Ralph, Elizabeth; Alexiou, Vasiliki; Dekaj, Fatjon; Kimonyo, Aline; Merali, Fatema; Sumner, Emma; Robinson, Emily; Feilding, Freya L.; Dick, Andrew; Beresford, Michael W.; Carlsson, Emil; Fairlie, Joanna; [...]

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

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  • Media type: E-Article
  • Title: The successes and challenges of harmonising juvenile idiopathic arthritis (JIA) datasets to create a large-scale JIA data resource
  • Contributor: Lawson-Tovey, Saskia; Smith, Samantha Louise; Geifman, Nophar; Shoop-Worrall, Stephanie; Ng, Sandra; Barnes, Michael R.; Wedderburn, Lucy R.; Hyrich, Kimme L.; Kartawinata, Melissa; Wanstall, Zoe; Jebson, Bethany R.; McNeece, Alyssia; Ralph, Elizabeth; Alexiou, Vasiliki; Dekaj, Fatjon; Kimonyo, Aline; Merali, Fatema; Sumner, Emma; Robinson, Emily; Feilding, Freya L.; Dick, Andrew; Beresford, Michael W.; Carlsson, Emil; Fairlie, Joanna; [...]
  • imprint: Springer Science and Business Media LLC, 2023
  • Published in: Pediatric Rheumatology
  • Language: English
  • DOI: 10.1186/s12969-023-00839-2
  • ISSN: 1546-0096
  • Keywords: Immunology and Allergy ; Rheumatology ; Pediatrics, Perinatology and Child Health
  • Origination:
  • Footnote:
  • Description: <jats:title>Abstract</jats:title><jats:sec> <jats:title>Background</jats:title> <jats:p>CLUSTER 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.</jats:p> </jats:sec><jats:sec> <jats:title>Methods</jats:title> <jats:p>Four 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.</jats:p> </jats:sec><jats:sec> <jats:title>Results</jats:title> <jats:p>Of 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.</jats:p> </jats:sec><jats:sec> <jats:title>Conclusions</jats:title> <jats:p>Combining 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.</jats:p> </jats:sec>
  • Access State: Open Access