POS0398 DEFINING OVERALL AND SEX-SPECIFIC BASDAI CUT-OFFS FOR DISEASE ACTIVITY STATES IN AXIAL SPONDYLARTHRITIS – RESULTS FROM THE EUROSPA COLLABORATION
Authors: S. Georgiadis, L. Midtbøll Ørnbjerg, B. Michelsen, T. K. Kvien, S. Horskjær Rasmussen, K. Pavelka, J. Zavada, B. Glintborg, A. G. Loft, A. M. Rodrigues, M. J. Santos, A. Ciurea, M. J. Nissen, L. Kuusalo, J. Rutanen, Z. Rotar, K. Perdan Pirkmajer, B. Gudbjornsson, O. Palsson, D. DI Giuseppe, M. Østergaard, M. Lund Hetland
Journal: Annals of the Rheumatic Diseases (2024)

<h3>Background:</h3> The Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) is used to classify patients with axial spondylarthritis (axSpA) according to disease activity states, particularly when Ankylosing Spondylitis Disease Activity Score (ASDAS) is unavailable. BASDAI values of &lt;2, &lt;4 and &gt;6 are often applied as cut-offs between remission, low (LDA), high (HDA) and very high (VHDA) disease activity, respectively, although this remains unvalidated. Further, sex-based differences in disease activity measures are expected. <h3>Objectives:</h3> We aimed to (i) identify BASDAI cut-offs for disease activity states against predefined external criteria, and (ii) investigate the impact of sex on BASDAI cut-offs. <h3>Methods:</h3> Real-world data from axSpA patients initiating a tumour necrosis factor inhibitor or an interleukin-17A inhibitor from registries participating in the EuroSpA collaboration were analysed. We applied the same approach as previously used to define the endorsed ASDAS cut-offs for disease activity states [1]. Follow-up data at 6 months were used to identify the cut-offs between remission and LDA and between LDA and HDA, while baseline data were identified to select the cut-off for VHDA. Receiver operating characteristic (ROC) were performed analyses to determine the optimal BASDAI values against external criteria (ASAS partial remission and, using thresholds as defined in [1], patient and physician global assessments). Moreover, we conducted separate ROC analyses to identify sex-specific BASDAI cut-offs. The level of agreement between disease activity states based on the estimated and the unvalidated BASDAI cut-offs was also assessed. <h3>Results:</h3> We analysed data from 2,791 patients, of whom 1,708 (61%) were men, from 7 registries with available data on BASDAI and the above-mentioned external criteria (0-10 scale). Mean (SD) BASDAI was 6.1 (1.9) and 3.0 (2.3) at baseline and 6 months, respectively. The optimal BASDAI values against external criteria were estimated to be &lt;1.4, &lt;2.8 and &gt;5.9 (Table 1). The estimated sex-specific BASDAI cut-offs were &lt;1.3, &lt;2.5 and &gt;5.9 for men and &lt;1.6, &lt;2.9 and &gt;5.9 for women, respectively. Figure 1 shows how patients classified in disease activity states according to the cut-offs &lt;2, &lt;4 and &gt;6 were distributed across disease activity states when classified according to the estimated cut-offs. Comparing the estimated and the unvalidated BASDAI cut-offs, 9.1% and 29.8% of patients changed disease activity states at baseline and 6 months, respectively, with corresponding weighted kappa values of 0.91 and 0.72. The level of agreement between disease activity states based on the estimated sex-specific and the unvalidated BASDAI cut-offs was better for women than for men. <h3>Conclusion:</h3> The BASDAI cut-offs for the disease activity states against predefined external criteria were &lt;1.4, &lt;2.8 and &gt;5.9. Our results suggested that sex-based differences in the assessment of disease activity could be considered in clinical practice. <h3>REFERENCES:</h3> [1] Machado et al. (2011). Ann Rheum Dis, 70(1), 47-53. <h3>Acknowledgements:</h3> Novartis Pharma AG and IQVIA for supporting the EuroSpA collaboration. <h3>Disclosure of Interests:</h3> Stylianos Georgiadis Novartis, Lykke Midtbøll Ørnbjerg Novartis, Brigitte Michelsen Novartis, Novartis, Tore K. Kvien Grünenthal, Sandoz, UCB, AbbVie, Amgen, Celltrion, Gilead, Novartis, Pfizer, Sandoz, UCB, AbbVie, Amgen, BMS, Galapagos, Novartis, Pfizer, UCB, Simon Horskjær Rasmussen Novartis, Karel Pavelka AbbVie, UCB, Pfizer, Eli Lilly, Celltrion, MSD, Novartis, Jakub Zavada Abbvie, Elli-Lilly, Sandoz, Novartis, Egis, UCB, Sanofi, Astra Zeneca, Sobi, Bente Glintborg Abbvie, BMS, Pfizer, Sandoz, Anne Gitte Loft Pfizer, AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, UCB, AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, UCB, Novartis, Ana Maria Rodrigues Abbvie, Amgen, Abbvie, Amgen, Amgen, Novartis, Pfizer, Maria José Santos Abbvie, AstraZeneca, Janssen, Lilly, Medac, Novartis, Pfizer, Adrian Ciurea: None declared, Michael J. Nissen AbbVie, Amgen, Eli Lilly, Janssens, Novartis, Pfizer, AbbVie, Eli Lilly, Janssens, Novartis, Pfizer, Novartis, Pfizer, Laura Kuusalo Abbvie, Lilly, Medac, Orion, Pfizer, UCB, Gilead, Pfizer, Jarno Rutanen: None declared, Ziga Rotar Abbvie, Amgen, Biogen, Eli Lilly, Janssen, Lek, MSD, Medis, Novartis, Pfizer, Sanofi, Abbvie, AstraZeneca, Eli Lilly, Janssen, Novartis, Pfizer, SOBI, Swixx BioPharma, Katja Perdan Pirkmajer Abbvie, Eli Lilly, Janssen, Lek, Medis, MSD, Novartis, Pfizer, Abbvie, Boehringer Ingelheim, Eli Lilly, Medis, Novartis, Pfizer, Bjorn Gudbjornsson Novartis, Nordic-Pharma, Novartis, Olafur Palsson: None declared, Daniela Di Giuseppe: None declared, Mikkel Østergaard Abbvie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, UCB, Abbvie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, UCB, Abbvie, BMS, Merck, Novartis, UCB, Merete Lund Hetland Pfizer, Medac, Sandoz, Abbvie, Abbvie, Biogen, BMS, Celltrion, Eli Lilly, Janssen Biologics B.V, Lundbeck Fonden, MSD, Medac, Pfizer, Roche, Samsung Biopies, Sandoz, Novartis, Nordforsk.