Skip to main content

The changing profile of ankylosing spondylitis in the biologic era



To compare disease characteristics, comorbidities, and medication utilization of 1141 patients with ankylosing spondylitis (AS) with short (< 20 years) and long (≥ 20 years) disease duration enrolled in the Prospective Study of Outcomes in AS (PSOAS) study over three different periods of time and followed longitudinally.


Study visits were carried out every 6 months examining disease activity (Bath AS Disease Activity Index (BASDAI), C-reactive protein, erythrocyte sedimentation rate), functional impairment, depression, and medication utilization as well as radiographic severity. Groups were compared with regression models using generalized estimating equation, linear, and Poisson regressions after adjusting for sites and for patients withdrawing from the study at less than 2 years follow-up.


Overall, AS patients with long disease duration were more likely to be married, white, receiving disability, and to be with higher functional impairment and radiographic severity, more uveitis, diabetes, hypertension, cardiovascular disease, and osteoporosis, and with less nonsteroidal anti-inflammatory drug (NSAID) and more opioid use than those with short disease duration. Current smoking decreased between 2002 and 2019 regardless of disease duration. Lower baseline NSAID and methotrexate/sulfasalazine use and higher TNF inhibitor usage were seen only in those with shorter disease duration, though NSAID use and functional impairment decreased over time in both groups. Disease activity, depression scores, and NSAID use decreased and anti-TNF use increased in those followed > 8 years.


Patients with AS enrolling in this multicenter longitudinal cohort have different disease profiles and medication utilization over time, perhaps reflecting innovations in treatment and increasing disease awareness.

Key Points
• The use of NSAIDs, nonbiologic DMARDs, and prednisone has decreased over the past 16 years in patients with AS.
• The use of anti-TNF agents has dramatically increased.
• In treated patients, disease activity, depression scores, and functional impairment have decreased over time.

This is a preview of subscription content, access via your institution.


  1. 1.

    Baraliakos X, Haibel H, Listing J, Sieper J, Braun J (2014) Continuous long-term anti-TNF therapy does not lead to an increase in the rate of new bone formation over 8 years in patients with ankylosing spondylitis. Ann Rheum Dis 7:710–715

    Article  Google Scholar 

  2. 2.

    Haroon N, Inman RD, Learch TJ, Weisman MH, Lee M, Rahbar MH et al (2013) The impact of TNF-inhibitors on radiographic progression in ankylosing spondylitis. Arthritis Rheum 65:2645–2654

    CAS  PubMed  PubMed Central  Google Scholar 

  3. 3.

    van der Heijde D, Ramiro S, Landewé R, Baraliakos X, Van den Bosch F et al (2017) 2016 update of the ASAS-EULAR management recommendations for axial spondyloarthritis. Ann Rheum Dis 76:978–991

    Article  Google Scholar 

  4. 4.

    Ward MM, Deodhar A, Gensler LS, Dubreuil M, Yu D, Khan MA, Haroon N, Borenstein D, Wang R, Biehl A, Fang MA, Louie G, Majithia V, Ng B, Bigham R, Pianin M, Shah AA, Sullivan N, Turgunbaev M, Oristaglio J, Turner A, Maksymowych WP, Caplan L (2019) 2019 update of the American College of Rheumatology/Spondylitis Association of America/Spondyloarthritis Research and Treatment Network recommendations for the treatment of ankylosing spondylitis and nonradiographic axial spondyloarthritis. Arthritis Rheum 71:1599–1613

    Article  Google Scholar 

  5. 5.

    WTCCC and TASC (2007) Association scan of 14,500 nsSNPs in four common diseases identifies variants involved in autoimmunity. Nat Genet 39:1329–1337

    Article  Google Scholar 

  6. 6.

    Reveille JD, Sims AM, Danoy P, Evans DM, Leo P, Jin R et al (2010) Genome-wide association study of ankylosing spondylitis identifies multiple non-MHC susceptibility loci. Nat Genet 42:123–127

    CAS  Article  Google Scholar 

  7. 7.

    Evans DM, Spencer CCA, Pointon JJ, Su Z, Harvey D, Kochan G, Oppermann U, Dilthey A, Pirinen M, Stone MA, Appleton L, Moutsianas L, Leslie S, Wordsworth T, Kenna TJ, Karaderi T, Thomas GP, Ward MM, Weisman MH, Farrar C, Bradbury LA, Danoy P, Inman RD, Maksymowych W, Gladman D, Rahman P, Spondyloarthritis Research Consortium of Canada (SPARCC), Morgan A, Marzo-Ortega H, Bowness P, Gaffney K, Gaston JS, Smith M, Bruges-Armas J, Couto AR, Sorrentino R, Paladini F, Ferreira MA, Xu H, Liu Y, Jiang L, Lopez-Larrea C, Díaz-Peña R, López-Vázquez A, Zayats T, Band G, Bellenguez C, Blackburn H, Blackwell JM, Bramon E, Bumpstead SJ, Casas JP, Corvin A, Craddock N, Deloukas P, Dronov S, Duncanson A, Edkins S, Freeman C, Gillman M, Gray E, Gwilliam R, Hammond N, Hunt SE, Jankowski J, Jayakumar A, Langford C, Liddle J, Markus HS, Mathew CG, McCann O, McCarthy M, Palmer CN, Peltonen L, Plomin R, Potter SC, Rautanen A, Ravindrarajah R, Ricketts M, Samani N, Sawcer SJ, Strange A, Trembath RC, Viswanathan AC, Waller M, Weston P, Whittaker P, Widaa S, Wood NW, McVean G, Reveille JD, Wordsworth BP, Brown MA, Donnelly P, Australo-Anglo-American Spondyloarthritis Consortium (TASC), Wellcome Trust Case Control Consortium 2 (WTCCC2) (2011) Genome-wide association study in ankylosing spondylitis identifies further non-MHC associations, and demonstrates that the ERAP1 association is restricted to HLA-B27 positive cases implicating peptide presentation as the likely mechanism underlying the association of HLA-B27 with the disease. Nat Genet 43:761–767

    CAS  Article  Google Scholar 

  8. 8.

    Cortes A, Hadler J, Pointon JP, Robinson PC, Karaderi T, Leo P et al (2013) Identification of multiple risk variants for ankylosing spondylitis through high-density genotyping of immune-related loci. Nat Genet 45:730–738

    CAS  Article  Google Scholar 

  9. 9.

    Robinson PC, Costello ME, Leo P, Bradbury LA, Hollis K, Cortes A, Lee S, Joo KB, Shim SC, Weisman M, Ward M, Zhou X, Garchon HJ, Chiocchia G, Nossent J, Lie BA, Førre Ø, Tuomilehto J, Laiho K, Jiang L, Liu Y, Wu X, Elewaut D, Burgos-Vargas R, Gensler LS, Stebbings S, Haroon N, Mulero J, Fernandez-Sueiro JL, Gonzalez-Gay MA, Lopez-Larrea C, Bowness P, Gafney K, Gaston JSH, Gladman DD, Rahman P, Maksymowych WP, Xu H, van der Horst-Bruinsma IE, Chou CT, Valle-Oñate R, Romero-Sánchez MC, Hansen IM, Pimentel-Santos FM, Inman RD, Martin J, Breban M, Evans D, Reveille JD, Kim TH, Wordsworth BP, Brown MA (2015) ERAP2 is associated with ankylosing spondylitis in HLA-B27-positive and HLA-B27-negative patients. Ann Rheum Dis 74:1627–1629

    CAS  Article  Google Scholar 

  10. 10.

    Cortes A, Maksymowych WP, Wordsworth BP, Inman RD, Danoy P, Rahman P, Stone MA, Corr M, Gensler LS, Gladman D, Morgan A, Marzo-Ortega H, Ward MM, SPARCC (Spondyloarthritis Research Consortium of Canada), TASC (Australo-Anglo-American Spondyloarthritis Consortium), Learch TJ, Reveille JD, Brown MA, Weisman MH (2015) Association study of genes related to bone formation and resorption and the extent of radiographic change in ankylosing spondylitis. Ann Rheum Dis 74:1387–1393

    CAS  Article  Google Scholar 

  11. 11.

    Robinson PC, Claushuis TA, Cortes A, Martin TM, Evans DM, Leo P et al (2015) (2015) genetic dissection of acute anterior uveitis reveals similarities and differences in associations observed with ankylosing spondylitis. Arthritis Rheum 67:140–151

    CAS  Article  Google Scholar 

  12. 12.

    Cortes A, Pulit SL, Leo PJ, Pointon JJ, Robinson PC, Weisman MH et al (2015) Major histocompatibility complex associations of ankylosing spondylitis are complex and involve further epistasis with ERAP1. Nat Commun 6:7146.

    Article  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Ellinghaus D, Jostins L, Spain SL, Cortes A, Bethune J, Han B et al (2016) Analysis of five chronic inflammatory diseases identifies 27 new associations and highlights disease-specific patterns at shared loci. Nat Genet 48:510–518

    CAS  Article  Google Scholar 

  14. 14.

    Reveille JD, Zhou X, Lee M, Weisman MH, Yi L, Gensler LS, Zou H, Ward MM, Ishimori ML, Learch TJ, He D, Rahbar MH, Wang J, Brown MA (2019) HLA class I and II alleles in susceptibility to ankylosing spondylitis. Ann Rheum Dis 78:66–73

    CAS  Article  Google Scholar 

  15. 15.

    van der Linden S, Valkenburg H, Cats A (1984) Evaluation of diagnostic criteria for ankylosing spondylitis. A proposal for modification of the New York criteria. Arthritis Rheum 27:361–388

    Article  Google Scholar 

  16. 16.

    Brionez TF, Assassi S, Reveille JD, Learch T, Diekman L, Ward MM et al (2009) Psychological correlates of self-reported functional limitation in patients with ankylosing spondylitis. Arthritis Res Ther 11:R182

    Article  Google Scholar 

  17. 17.

    Brionez TF, Assassi S, Reveille JD, Green C, Learch T, Diekman L et al (2010) Psychological Correlates of self-reported disease activity in ankylosing spondylitis. J Rheumatol 37:829–834

    Article  Google Scholar 

  18. 18.

    Jang JH, Green CE, Assassi S, Reveille JD, Ward MM, Weisman MH, Nicassio PM (2011) The contribution of disease activity on functional limitations over time through psychological mediators: a 12-month longitudinal study in patients with ankylosing spondylitis. Rheumatology (Oxford) 50:2087–2092

    Article  Google Scholar 

  19. 19.

    Dau JD, Lee MJ, Ward MM, Gensler LS, Brown MA, Learch TJ, Diekman LA, Tahanan A, Rahbar MH, Weisman MH, Reveille JD (2018) Opioid analgesic use in patients with Ankylosing spondylitis—an analysis of the PSOAS cohort. J Rheumatol 45:188–194

    CAS  Article  Google Scholar 

  20. 20.

    Garrett S, Jenkinson T, Kennedy LG, Whitelock H, Gaisford P, Calin A (1994) A new approach to defining disease status in ankylosing spondylitis: the Bath Ankylosing Spondylitis Disease Activity Index. J Rheumatol 21:2286–2291

    CAS  PubMed  Google Scholar 

  21. 21.

    Calin A, Farrett S, Whitelock H, Kennedy LG, O’Hea J, Mallorie P, Jenkinson T (1994) A new approach to defining functional ability in ankylosing spondylitis: the development of the Bath Ankylosing spondylitis functional index. J Rheumatol 21:2281–2285

    CAS  PubMed  Google Scholar 

  22. 22.

    Radloff LS (1977) The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas 1:385–401

    Article  Google Scholar 

  23. 23.

    Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG (2009) Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 42:377–381

    Article  Google Scholar 

  24. 24.

    Rahbar MH, Lee M, Hessabi M, Tahanan A, Brown MA, Learch TJ et al (2018) Harmonization, data management, and statistical issues related to prospective multicenter studies in ankylosing spondylitis (AS): Experience from the Prospective Study Of Ankylosing Spondylitis (PSOAS) cohort. Contemp Clin Trials Commun 11:127–135

    Article  Google Scholar 

  25. 25.

    Mackay K, Mack C, Brophy S, Calin A (1998) The Bath Ankylosing Spondylitis Radiology Index (BASRI): a new, validated approach to disease assessment. Arthritis Rheum 41:2263–2270

    CAS  Article  Google Scholar 

  26. 26.

    Creemers MC, Franssen MJ, van’t Hof MA, Gribnau FW, van de Putte LB, van Riel PL (2005) Assessment of outcome in ankylosing spondylitis: an extended radiographic scoring system. Ann Rheum Dis 64:127–129

    CAS  Article  Google Scholar 

  27. 27.

    Ward MM, Reveille JD, Learch TJ, Davis JC Jr, Weisman MH (2008) Occupational physical activities and long-term functional and radiographic outcomes in patients with ankylosing spondylitis. Arthritis Rheum 59:822–832

    Article  Google Scholar 

  28. 28.

    Essers I, Ramiro S, Stolwijk C, Blaauw M, Landewé R, van der Heijde D et al (2015) Characteristics associated with the presence and development of extra-articular manifestations in ankylosing spondylitis: 12-year results from OASIS. Rheumatology (Oxford) 54:633–640

    CAS  Article  Google Scholar 

  29. 29.

    Kim TJ, Sung IH, Lee S, Joo KB, Choi JH, Park DJ et al (2013) HLA-B27 homozygosity has no influence on radiographic damage in ankylosing spondylitis: Observation Study of Korean SpondyloArthropathy Registry (OSKAR) data. Joint Bone Spine 80:488–491

    CAS  Article  Google Scholar 

  30. 30.

    Wallis D, Thavaneswaran A, Haroon N, Ayearst R, Inman RD (2015) Tumour necrosis factor inhibitor therapy and infection risk in axial spondyloarthritis: results from a longitudinal observational cohort. Rheumatology (Oxford) 54:152–156

    CAS  Article  Google Scholar 

  31. 31.

    Poddubnyy D, Haibel H, Listing J, Märker-Hermann E, Zeidler H, Braun J, Sieper J, Rudwaleit M (2013) Cigarette smoking has a dose-dependent impact on progression of structural damage in the spine in patients with axial spondyloarthritis; results from the GErman SPondyloarthritis Inception Cohort (GESPIC). Ann Rheum Dis 72:1430–1432

    Article  Google Scholar 

  32. 32.

    van den Berg R, de Hooge M, van Gaalen F, Reijnierse M, Huizinga T, van der Heijde (2015) Percentage of patients with spondyloarthritis in patients referred because of chronic back pain and performance of classification criteria: experience from the spondyloarthritis caught early (SPACE) cohort. Rheumatology 52:1492–1499

    Article  Google Scholar 

  33. 33.

    Dougados M, d’Agostino M-A, Benessiano J, Berenbaum F, Breban M, Claudepierre P, Combe B, Dargent-Molina P, Daurès JP, Fautrel B, Feydy A, Goupille P, Leblanc V, Logeart I, Pham T, Richette P, Roux C, Rudwaleit M, Saraux A, Treluyer JM, van der Heijde D, Wendling D (2011) The DESIR cohort: a 10-year follow-up of early inflammatory back pain in France: study design and baseline characteristics of the 708 recruited patients. Joint Bone Spine 78:598–603

    Article  Google Scholar 

Download references


We acknowledge the support provided by the Biostatistics/ Epidemiology/ Research Design (BERD) component of the Center for Clinical and Translational Sciences (CCTS) for this project. CCTS is mainly funded by the NIH Centers for Translational Science Award (UL1TR000371) by the National Center for Advancing Translational Sciences (NCATS) and 2019 renewal (UL 1TR003167) by the NCATS. Also, we acknowledge that management of data for this study was done using REDCap, which was partly supported by a grant UL1 TR000445 from NCATS/NIH, awarded to Vanderbilt University. Dr. Michael Ward is supported by the Intramural Research Program, NIAMS, NIH. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH or the NCATS. This work was also supported by grants from the United States Department of Health and Human Services, National Institutes of Health (NIH), National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), P01-052915-06, and from the Spondylitis Association of America as well as from Janssen Pharmaceutical Division of Johnson and Johnson.

Author information



Corresponding author

Correspondence to John D. Reveille.

Ethics declarations

Each institution had the study approved by their respective institutional review boards (IRB), and each subject provided written informed consent to participate.



Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Reveille, J.D., Lee, M., Gensler, L.S. et al. The changing profile of ankylosing spondylitis in the biologic era. Clin Rheumatol 39, 2641–2651 (2020).

Download citation


  • Ankylosing spondylitis
  • Clinical features
  • Comorbidities
  • Disease progression
  • Drug therapy