ABS0602 SACROILIITIS RATE IN PATIENTS WITH PSORIASIS BASED ON MRI FINDINGS AND THE ASAS DEFINITION FOR ACTIVE SACROILIITIS
Bibliographic record
Abstract
Background: The 2009 Assessment of Spondylarthritis International Society (ASAS) classification criteria are frequently employed to assess axial involvement in individuals with spondylarthritis. While psoriasis is included as one of these criteria, the frequency of confirmed sacroiliitis in this group remains largely undetermined. Several investigations have indicated that individuals with psoriatic arthritis may exhibit a high occurrence of sacroiliitis on MRI, with a considerable number being asymptomatic. However, data on MRI-detected sacroiliitis in patients with psoriasis experiencing back pain remains scarce with a variable prevalence ranging between (10% - 25%) [1, 2]. Objectives: To determine the frequency of sacroiliitis detected by MRI in a cohort of patients with psoriasis experiencing back pain. Methods: The Dermatology Database at Hamad Medical Corporation was used to identify all psoriasis patients from January 2016 to November 30, 2023. This dataset was then electronically filtered to select patients who had undergone MRI examinations of the sacroiliac joint (SIJ). A retrospective review of these patients' electronic medical records was conducted to extract demographic and clinical information. Additionally, two musculoskeletal (MSK) radiologists, designated as reader A and B, independently evaluated the MRI scans without knowledge of the clinical data. These radiologists were trained to interpret MRI scans according to the ASAS definition for active sacroiliitis using validated calibration modules aimed at standardization recommended by the ASAS MRI working group. ASAS electronic case report form was used for evaluation of the MRI lesions in the SIJ. Results: A total of 113 psoriasis patients underwent MRI SIJ, with 38 excluded due to non-compliance with ASAS protocol for sacroiliitis evaluation. The remaining 75 subjects were analyzed. Among the participants, 45 (60%) were female. The average age was 42 years (SD ±11.9). Regarding ethnicity, 54 (72%) were Arab, 16 (21.3%) were East Asian, and 5 (6.7%) were from various other backgrounds. On average, patients had psoriasis for 9.8 years (SD ±8.7) before their MRI. MRI scan readers identified 7 subjects (9.3%) as having sacroiliitis, (3 subjects had combined structural and inflammatory lesions, 2 had isolated inflammatory lesions and 2 had isolated structural lesions). Out of the 7 subjects, 3 (4%) met the ASAS MRI definition for active sacroiliitis. Both MRI readers showed complete agreement in diagnosing sacroiliitis via MRI. Conclusion: In psoriasis patients with symptomatic back pain, MRI-detected sacroiliitis shows a low occurrence (9.3%), which decreases further when ASAS MRI definition for active sacroiliitis is applied. The utility of MRI of the sacroiliac joint needs to be further explored in a larger prospective cohort of patients with psoriasis. REFERENCES: [1] Fabian, Proft., S., Lüders., Tony, Hunter., Gonzalo, Luna., Valeria, Rios, Rodriguez., Mikhail, Protopopov., K., Meier., George, N., Kokolakis., Kamran, Ghoreschi., Denis, Poddubnyy. (2022). Pos1445 early detection of axial psoriatic arthritis in patients with psoriasis: a prospective, multicenter study. Annals of the Rheumatic Diseases, 81(Suppl 1):1067.1-1067. doi: 10.1136/annrheumdis-2022-eular.4375. [2] Vlad, A., Bratu., Peter, Häusermann., Ulrich, A., Walker., Thomas, Daikeler., Veronika, Zubler., Veronika, K., Jaeger., Ulrich, Weber., Ueli, Studler. (2019). Do Patients With Skin Psoriasis Show Subclinical Axial Inflammation on Magnetic Resonance Imaging of the Sacroiliac Joints and Entire Spine. Arthritis Care and Research, 71(8):1109-1118. doi: 10.1002/ACR.23767. Table 1The clinical characteristics of patients with psoriasis who were diagnosed with sacroiliitis by MRI compared to patients who did not show sacroiliitis by MRI.Sacroiliitis by MRI 7No sacroiliitis 68P valuePsoriatic nails n (%)3 (42.9%)19 (27.9%)0.412Arthritis n (%)1 (14.3%)9 (13.2%)1.000Enthesitis n (%)019 (27.9)0.181Dactylitis n (%)01 (1.5%)1.000Uveitis n (%)05 (7.4%)1.000Inflammatory bowel disease n (%)02 (2.9%)1.000Inflammatory back pain n (%)5 (71.4%)32 (47.1%)0.262Biology before MRI n (%)3 (42.9%)19 (27.9%)0.412 Acknowledgements: NIL . Disclosure of Interests: None declared . © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".