THU0246 DIAGNOSTIC CLUSTER PROFILING OF PATIENTS IN A REAL-WORLD DATA SET WITH SYSTEMIC LUPUS ERYTHEMATOSUS
Authors: Z. Touma, B. Hoskin, C. Atkinson, D. Bell, O. Massey, J. H. Lofland, P. Berry, C. Karyekar, K. Costenbader
Journal: Annals of the Rheumatic Diseases (2020)

Background: Previous systemic lupus erythematosus (SLE) studies have identified potential clusters of SLE clinical manifestations post diagnosis. Objectives: To describe the presentation of SLE at diagnosis across different cohorts of patients and describe management and outcomes after diagnosis within clusters. Methods: Cross-sectional study of 263 rheumatologists in the US and EU5. Data were collected from the Adelphi Real World 2015 Lupus Disease Specific Programme. Rheumatologists completed patient record forms (PRFs) for the next 5 prospectively consulting SLE patients; these patients completed patient self-completion (PSC) forms describing how SLE affected them. PRF data includes patient’s characteristics and management history. PSCs focused on similar data collection, including patient reported outcome measures on the humanistic burden. Age at diagnosis, symptoms at diagnosis, organ involvement at diagnosis, and severity at diagnosis were used as covariates in a latent cluster analysis. Results: Data were extracted from 1376 PRFs. Cluster analysis resulted in up to 6 clusters, and disease understanding led to the selection of a 4-cluster solution. Cluster 1 displayed the mildest disease, characterised by joint involvement, while cluster 2 displayed more skin involvement in conjunction with joint. Cluster 3 were characterised by renal involvement and cluster 4 had skin and joint involvement, but also high constitutional and haematological involvement at diagnosis (Table 1). Table 1 Cluster analysis Clusters Organ involvement at diagnosis, n (% ) Overall (n=1304) 1 (n=210) 2 (n=493) 3 (n=162) 4 (n=439) p-value Musculoskeletal 1145 (87.8) 174 (82.9) 444 (90.1) 134 (82.7) 393 (89.5) 0.0065 Mucocutaneous 898 (68.9) 5 (2.4) 397 (80.5) 95 (58.6) 401 (91.3) &lt;0.0001 Neuropsychiatric 87 (6.7) 19 (9.0) 9 (1.8) 16 (9.9) 43 (9.8) &lt;0.0001 Cardiorespiratory 176 (13.5) 36 (17.1) 14 (2.8) 22 (13.6) 104 (23.7) &lt;0.0001 Gastrointestinal 44 (3.4) 8 (3.0) 14 (2.8) 8 (4.9) 14 (3.2) 0.6115 Opthalmic 47 (3.6) 0 20 (4.1) 10 (6.2) 17 (3.9) 0.0102 Renal 213 (16.6) 15 (7.1) 9 (1.8) 162 (100) 27 (6.2) &lt;0.0001 Constitutional 425 (32.6) 45 (21.4) 89 (18.1) 55 (34.0) 236 (53.8) &lt;0.0001 Haematological 452 (34.7) 64 (30.5) 22 (4.5) 80 (49.4( 286 (65.1) &lt;0.0001 Severity at diagnosis, n (% ) Mild 209 (16.0) 55 (26.2) 99 (20.1) 1 (0.6) 54 (12.3) &lt;0.0001 Moderate 806 (61.8) 122 (58.1) 324 (65.7) 75 (46.3) 285 (64.9) Severe 289 (22.2) 33 (15.7) 70 (14.2) 86 (53.1) 100 (22.8) Significant between-cluster differences were observed when comparing outcomes; cluster 4 have been diagnosed longest (mean weeks diagnosed 354.6 v. 1: 232.6, 2: 228.7, 3: 338.2, p&lt;0.0001). Cluster 3 consulted more in the last 12 months (mean number of visits 7.9 vs. 1: 5.7, 2: 6.3, 4: 7.6). Significant differences were also observed between clusters in relation to current treatment proportions: corticosteroid (highest cluster 3: 78.4%), immunosuppressant (highest cluster 3: 75.3%), biologic DMARD (highest cluster 4: 17.8%) and antidepressant (highest cluster 4: 4.1%). Conclusion: This study demonstrates the heterogeneity of SLE at diagnosis and highlights four distinct presentations of the disease at diagnosis. Significant proportions of patients present with advanced disease, these clusters go on to present the greatest burden demonstrating the need for better diagnostic tools and novel earlier intervention. Study funded by Johnson and Johnson. Disclosure of Interests: Zahi Touma Consultant of: Consultant for Janssen, Ben Hoskin Consultant of: Consultant for Janssen, Christian Atkinson Consultant of: Consultant for Janssen, David Bell Consultant of: Janssen, Olivia Massey Consultant of: Janssen, Jennifer H. Lofland Employee of: Janssen, Pamela Berry Employee of: Janssen, Chetan Karyekar Shareholder of: Johnson &amp; Johnson, Consultant of: Janssen, Employee of: Janssen Global Services, LLC. Previously, Novartis, Bristol-Myers Squibb, and Abbott Labs., Karen Costenbader Grant/research support from: Merck, Consultant of: Astra-Zeneca