Background: Calcium pyrophosphate deposition disease (CPPD) disease can mimic or interfere with the course of rheumatoid arthritis (RA). Previous studies suggest higher prevalence of Chondrocalcinosis (CC), a precursor of CPPD, in seronegative RA patients. However, no significant treatment disparities were described in RA patients with or without coexisting CC.

Objectives: Application of our novel AI-algorithm in a well characterized RA cohort in order to assess prevalence of CC and basic characteristics of affected patients.

Methods: We recently developed and validated a deep learning algorithm to classify the presence of chondrocalcinosis (CC) on hand radiographs, detecting the presence of CC at the TFCC, MCP-2, and MCP-3 sites with an accuracy of 0.86. In this study, we report the baseline characteristics of 1,344 RA patients of the Swiss Clinical Quality Management in Rheumatic Diseases (SCQM) registry who underwent CC assessment using this algorithm and number of therapy lines and with adequate quality of the radiographs to run the algorithm. A subgroup of patients was identified for whom the results of a clinical examination were available on the same date as the radiographs. In the event that radiographs of both hands were available, one was randomly selected. The following data were extracted: age, sex, seropositivity (RF, anti-CCP) status, number of therapy lines (four or more drugs vs. less), and DAS28 (CRP) (> 5.1 vs. below). Two multivariable logistic regression analyses were conducted to assess the association of CC presence on DAS28 scores and the number of current RA medications, with adjustments made for patients’ age, sex, and serostatus.

Results: The mean age of the participants was 56.2 years (standard deviation (SD) 13.9), 954/1344 (71.0%) were female, and 916/1344 (68.2%) were seropositive. CC was present in 310 patients (23.1%) and overall not associated with the serostatus. Overall, 46 patients (3.4%) were taking at least four medications, and 82 (6.1%) exhibited high disease activity with DAS28-CRP >5.1. Overall, no association was found between CC presence and disease activity (OR 1.09 (95% CI: 0.62-1.90); p=0.771). In multivariable analyses, CC+ patients were more likely to take at least four drugs (odds ratio (OR): 2.54 (95% confidence interval (CI): 1.21-5.32); p=0.014) and were significantly older (CC-: 54.0 SD (13.5), CC+ 63.0 SD (13.0), p<0.001).

Conclusion: In this cross-sectional analysis of baseline characteristics of a large cohort of patients with RA who underwent CC assessment, we found a fairly strong association between the presence of CC and high drug use. However, overall we did not find an association between the presence of CC and disease activity or serostatus. Additional analyses will be performed in subgroups based on e.g. age, disease duration and type of treatment.

REFERENCES: [1] Development of a deep learning model for automated detection of calcium pyrophosphate deposition in hand radiographs. Hügle T, Rosoux E, Fahrni G, Markham D, Manigold T, Becce F. Front Med (Lausanne). 2024 Oct 23;11:1431333. doi: 10.3389/fmed.2024.1431333. eCollection 2024.

Acknowledgements: NIL.

Disclosure of Interests: Tobias Manigold Roche, JJ, Roche, Roche, JJ, Sobi, Novartis, Lilly, Nicolas Bodmer: None declared, Elisabeth Rosoux: None declared, Guillaume Fahrni: None declared, Deborah Markham: None declared, Raphael Micheroli: None declared, Lucas M. Bachmann Medignition, Medignition, Jonas Brändli: None declared, Fabio Becce Horizon Therapeutics, Siemens Healthineers, Thomas Hügle AbbVie/Abbott, ATREON SA, GlaxoSmithKlein(GSK), Novartis, Roche.

© 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.