POS0877 DIFFERENCES IN REPORTED PREVALENCE OF RHEUMATIC DISEASES IN OUTPATIENT CLINIC: RESULTS FROM A UK TERTIARY EARLY INFLAMMATORY ARTHRITIS CLINIC
Authors: R. M. Hum, M. S. Aleem, Z. Mobarak, F. Saqib, K. Hasanein, A. Barton, P. Ho
Journal: Annals of the Rheumatic Diseases (2024)

<h3>Background:</h3> Polygenic risk scores to aid diagnosis have been developed and applied in research settings and limited real-world settings. For example, the G-PROB tool has been shown to perform well in excluding certain diagnoses, when used in cohorts of patients enriched for inflammatory arthritis. However, the performance of these tools can be affected by the prevalence of the conditions and, therefore, it is important to obtain accurate prevalence estimates of inflammatory arthritis diagnoses in real-world, early arthritis clinics.<sup>[1, 2]</sup> <h3>Objectives:</h3> The aim of this study was to determine the prevalence of rheumatic diseases in a real-world cohort of patients newly referred to a UK tertiary early inflammatory arthritis (EIA) clinic over 1 year and to determine the proportion of patients who are "misdiagnosed" on first presentation and have their diagnosis revised at follow-up. <h3>Methods:</h3> Patients were referred to the EIA clinic by primary care if they had clinical symptoms and physical examination findings suggestive of inflammatory arthritis. In EIA clinic, patients were seen by a rheumatologist, an initial diagnosis was made, and treatment was initiated if appropriate. Patients were followed up in EIA clinic and a final diagnosis was made. Routine clinical data was collected from electronic patient records and tabulated. Clinical diagnoses were grouped into six categories (rheumatoid arthritis (RA), psoriatic arthritis (PsA), axial spondylarthritis (SpA), systemic lupus erythematosus (SLE), and other) to enable comparisons with previously published cohorts in which polygenic risk score approaches (G-PROB platform) have been applied. <h3>Results:</h3> Over 12-months, 164 new patients were seen in the EIA clinic, where the mean age was 47 (SD 17), 64% (n=105) were of female sex, 65% (n=90) were of non-white ethnicity, and 42% (n=69) were current or ex-smokers. The vast majority had peripheral joint symptoms (n=154, 94%), whilst 23% (n=37) had axial symptoms, 15% (n=25) had psoriasis, 5% (n=8) had inflammatory bowel disease, and 4% (n=6) had uveitis. In terms of treatment, 9% (n=16) of patients received corticosteroids, and 12% (n=19) were started on a DMARD. In terms of laboratory results, 9% (n=14) were ACPA-positive, 17% (n=28) were RF-positive, and mean ESR and CRP was 17 (SD 17) and 10 (SD 21) respectively. Proportions of clinical diagnoses were different in the EIA cohort compared to previously published cohorts; non-inflammatory conditions such as chronic pain syndromes and simple musculoskeletal pain were more frequently diagnosed and prevalent in the EIA clinic. However, of the rheumatic diseases, RA was the most prevalent in all cohorts. (Table 1) Seventeen patients (10%) had their diagnosis changed at follow-up in EIA clinic: 7 patients initially diagnosed with a chronic pain syndrome had their diagnosis changed to RA (n=2), PsA (n=1), Gout (n=2), reactive arthritis (n=1), and undifferentiated connective tissue disease (UCTD) (n=1); 4 patients diagnosed with RA changed to PsA (n=1), dermatomyositis (n=1), polymyalgia rheumatica (n=1), UCTD (n=1); 1 patient with PsA changed to Dupilumab-induced arthritis; 2 patients with gout changed to RA and PsA; 2 patients with primary Raynaud's changed to RA and UCTD; and 1 patient with UCTD changed to sarcoidosis. <h3>Conclusion:</h3> Disease prevalence is context-specific, where prevalence estimates in the intended setting should be determined prior to implementation of prediction tools such as polygenic risk scores. In contrast to observational studies and registries, in this real-world cohort we significantly found higher prevalence of non-inflammatory diseases such as chronic pain syndromes. Ten percent of patients were "misdiagnosed" and may have benefitted from novel diagnostic tools such as G-PROB to aid earlier and more accurate diagnosis. <h3>REFERENCES:</h3> [1] Knevel R et al. Using genetics to prioritize diagnoses for rheumatology outpatients with inflammatory arthritis. Sci Transl Med. 2020. [2] Hum RM et al. Using polygenic risk scores to aid diagnosis of patients with early inflammatory arthritis: results from the Norfolk Arthritis Register. Arthritis Rheumatol. 2023. <b>Table 1.</b> Prevalence of rheumatic diseases <h3>Acknowledgements:</h3> Muhammad Saad Aleem &amp; Zina Mobarak have contributed equally and are regarded as joint first authors. Pauline Ho and Ryan Malcolm Hum contributed equally and are regarded as joint last authors. <h3>Disclosure of Interests:</h3> <b>None declared.</b>