Published in

BMJ Publishing Group, Annals of the Rheumatic Diseases, 3(79), p. 324-331, 2020

DOI: 10.1136/annrheumdis-2019-216516

Links

Tools

Export citation

Search in Google Scholar

What is axial spondyloarthritis? A latent class and transition analysis in the SPACE and DESIR cohorts

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

Full text: Unavailable

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

ObjectivesTo gain expert-judgement-free insight into the Gestalt of axial spondyloarthritis (axSpA), by investigating its ‘latent constructs’ and to test how well these latent constructs fit the Assessment of SpondyloArthritis international Society (ASAS) classification criteria.MethodsTwo independent cohorts of patients with early onset chronic back pain (SPondyloArthritis Caught Early (SPACE)) or inflammatory back pain (IBP) (DEvenir des Spondylarthopathies Indifférenciées Récentes (DESIR)) were analysed. Latent class analysis (LCA) was used to estimate the (unobserved) potential classes underlying axSpA. The best LCA model groups patients into clinically meaningful classes with best fit. Each class was labelled based on most prominent features. Percentage fulfilment of ASAS axSpA, peripheral SpA (pSpA) (ignoring IBP) or both classification criteria was calculated. Five-year data from DESIR were used to perform latent transition analysis (LTA) to examine if patients change classes over time.ResultsSPACE (n=465) yielded four discernible classes: ‘axial’ with highest likelihood of abnormal imaging and HLA-B27 positivity; ‘IBP+peripheral’ with 100% IBP and dominant peripheral symptoms; ‘at risk’ with positive family history and HLA-B27 and ‘no SpA’ with low likelihood for each SpA feature. LCA in DESIR (n=576) yielded similar classes, except for the ‘no-SpA’. The ASAS axSpA criteria captured almost all (SPACE: 98%; DESIR: 93%) ‘axial’ patients, but the ‘IBP+peripheral’ class was only captured well by combining the axSpA and pSpA criteria (SPACE: 78%; DESIR: 89%). Only 4% of ‘no SpA’ patients fulfilled the axSpA criteria in SPACE. LTA suggested that 5-year transitions across classes were unlikely (11%).ConclusionThe Gestalt of axSpA comprises three discernible entities, only appropriately captured by combining the ASAS axSpA and pSpA classification criteria. It is questionable whether some patients with ‘axSpA at risk’ will ever develop axSpA.