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. 2024 Sep 30;10(3):e004584.
doi: 10.1136/rmdopen-2024-004584.

Change in different classes of chronic back pain suspicious of axial spondyloarthritis: a latent transition analysis of the SPACE cohort

Philipp Bosch  1   2   3 , Alexandre Sepriano  2   4 , Mary-Lucy Marques  2   5 , Désirée van der Heijde  2 , Robert Landewé  6   7 , Miranda van Lunteren  2 , Liese de Bruin  2 , Manouk de Hooge  8 , Caroline Bastiaenen  3 , Sofia Exarchou  9 , Roberta Ramonda  10 , Karen Minde Fagerli  11 , Floris A van Gaalen  2 , Sofia Ramiro  12   7
Affiliations

Change in different classes of chronic back pain suspicious of axial spondyloarthritis: a latent transition analysis of the SPACE cohort

Philipp Bosch et al. RMD Open. .

Abstract

Objectives: To follow up four previously identified classes 'pure axial spondyloarthritis' (axSpA) ('axial'), 'axSpA with peripheral signs' ('inflammatory back pain+peripheral'), 'axSpA at risk' and 'no spondyloarthritis' ('no SpA'). They reflect the expert-opinion-free construct or 'Gestalt' of chronic back pain suspicious of axSpA. The aim was to assess participants' transitions between these classes over time.

Methods: Participants with chronic back pain of ≤2 years duration, suspicious of axSpA from the SPondyloArthritis Caught Early cohort were analysed. Latent class (LCA) and latent transition analysis (LTA) using clinical, laboratory and imaging data at baseline and 2 years were calculated. Conditional and marginal probabilities were obtained, reflecting the probability of a spondyloarthritis feature in a class and the probability of the participant's class membership, respectively. Transitional probabilities were extracted revealing potential switches across classes. The analyses were performed in all participants using imputations for missing data and in participants with full data at baseline and 2 years.

Results: Baseline and 2 years LCA models were constructed for 702 participants, resulting in the same four-class model as previously described. LTA revealed only a 3% transition from the 'no SpA' to the 'at-risk' class from baseline to 2 years with all other participants remaining in their initially assigned class. Sensitivity analysis on 384 participants with complete data at both baseline and 2 years showed similar results, underlining the model's robustness.

Conclusions: Transitions between the four classes over 2 years were basically inexistent, highlighting the unlikelihood of developing new class-defining features of axSpA after an initial clinical workup.

Keywords: axial spondyloarthritis; epidemiology; magnetic resonance imaging; spondylitis, ankylosing; spondyloarthritis.

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Conflict of interest statement

Competing interests: PB has received travelling grants and adds board fees from Janssen, speaker fees from Janssen and AbbVie and projects grants from Pfizer; AS has received speaking and/or consulting fees from AbbVie, Novartis, UCB and Lilly. DvdH has received consulting fees from AbbVie, Argenx, BMS, Galapagos, Glaxo-Smith-Kline, Janssen, Lilly, Novartis, Pfizer, Takeda, UCB Pharma and is an associate editor of Annals Rheumatic Diseases, editorial board member of Journal of Rheumatology and RMD Open, Advisor Assessment of Axial Spondyloarthritis international Society and director of Imaging Rheumatology bv. RL has received honoraria for lectures and advisory boards from AbbVie, Galapagos, Janssen, Lilly, Novartis, Pfizer and UCB. RL is owner of Rheumatology Consultancy BV. MdH has received consultancy fees of UCB Pharma. SE has received consultancy fees from AbbVie, Amgen, Janssen, Novartis, UCB Pharma, Eli Lilly and research support from UCB Pharma. RR has received travelling grants, consulting and/or speaking fees, Advisory Boards fees from Abbvie, Novartis, Janssen, Lilly, MSD, Pfizer, and UCB. FvG reports research grants from Stichting vrienden van Sole Mio, Stichting ASAS, research grants and consultancy fees from Novartis, research grants from UCB, fees from MSD, consultancy fees from Abb Vie, fees from Bristol Myers Squibb and Eli Lilly, is a full time employee of the LUMC and member of the ASAS EC and the ASAS treasurer. SR has received grants from AbbVie, Galapagos, MSD, Novartis, Pfizer, UCB and consultancy fees from AbbVie, Eli Lilly, Galapagos, Janssen, MSD, Pfizer, UCB, Sanofi. The other authors have not declared any COI.

Figures

Figure 1
Figure 1. Graphical demonstration of the conditional and marginal probabilities of the 2-year latent transition analysis (LTA) model (n=702). The circles represent the conditional probability for a feature in a respective class, with a higher probability corresponding to a fuller circle. A full circle represents 100% and an empty circle 0% probability. The colours represent the four classes. The numerical values for conditional and marginal probabilities are reported in table 2. The numbers in the last row represent the marginal probabilities, that is, the percentage of participants that according to the LTA belong to one of the classes. ASAS, Assessment of SpondyloArthritis international Society; BME, bone marrow oedema; CRP, C reactive protein; IBP, inflammatory back pain; mNY, modified New York criteria; NSAID, non-steroidal anti-inflammatory drug; SIJ, sacroiliac joints; X-SIJ, radiograph of the sacroiliac joints; SpA, spondyloarthritis; X-Spine, radiograph of the spine.
Figure 2
Figure 2. Diagram showing class change over 2 years according to transitional probabilities (LTA analysis). Transitional probabilities were generated using the 4-class latent transition model with 702 patients. IBP, inflammatory back pain; LTA, latent class analysis; SpA, spondyloarthritis.
See this image and copyright information in PMC

References

    1. Sieper J, Poddubnyy D. Axial spondyloarthritis. Lancet. 2017;390:73–84. doi: 10.1016/S0140-6736(16)31591-4. - DOI - PubMed
    1. Rudwaleit M, Landewé R, van der Heijde D, et al. The development of Assessment of SpondyloArthritis international Society classification criteria for axial spondyloarthritis (part I): classification of paper patients by expert opinion including uncertainty appraisal. Ann Rheum Dis. 2009;68:770–6. doi: 10.1136/ard.2009.108217. - DOI - PubMed
    1. Rudwaleit M, van der Heijde D, Landewe R, et al. The development of Assessment of SpondyloArthritis international Society classification criteria for axial spondyloarthritis (part II): validation and final selection. Ann Rheum Dis. 2009;68:777–83. doi: 10.1136/ard.2009.108233. - DOI - PubMed
    1. Rudwaleit M, van der Heijde D, Landewé R, et al. The Assessment of SpondyloArthritis International Society classification criteria for peripheral spondyloarthritis and for spondyloarthritis in general. Ann Rheum Dis. 2011;70:25–31. doi: 10.1136/ard.2010.133645. - DOI - PubMed
    1. Lukas C, Cyteval C, Dougados M, et al. MRI for diagnosis of axial spondyloarthritis: major advance with critical limitations “Not everything that glisters is gold (standard).”. RMD Open. 2018;4:e000586. doi: 10.1136/rmdopen-2017-000586. - DOI - PMC - PubMed