학술논문
The successes and challenges of harmonising juvenile idiopathic arthritis (JIA) datasets to create a large-scale JIA data resource.
Document Type
Article
Author
Lawson-Tovey, Saskia; Smith, Samantha Louise; Geifman, Nophar; Shoop-Worrall, Stephanie; Ng, Sandra; Barnes, Michael R.; Wedderburn, Lucy R.; Hyrich, Kimme L.; CLUSTER consortium; Kartawinata, Melissa; Wanstall, Zoe; Jebson, Bethany R.; McNeece, Alyssia; Ralph, Elizabeth; Alexiou, Vasiliki; Dekaj, Fatjon; Kimonyo, Aline; Merali, Fatema; Sumner, Emma; Robinson, Emily
Source
Subject
*JUVENILE idiopathic arthritis
*YOUNG adults
*MISSING data (Statistics)
*INDIVIDUALIZED medicine
*CONSORTIA
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Language
ISSN
1546-0096
Abstract
Background: 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. Methods: 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. Results: 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. Conclusions: 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. [ABSTRACT FROM AUTHOR]