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FRI0653 IMPROVING AND VALIDATING THE PREDICTIVE ACCURACY OF MRI DETECTED SUBCLINICAL INFLAMMATION FOR RHEUMATOID ARTHRITIS DEVELOPMENT IN CLINICALLY SUSPECT ARTHRALGIA

Background Presence of MRI-detected subclinical joint inflammation in clinically suspect arthralgia (CSA) is predictive for progression to Rheumatoid Arthritis. Despite high negative predictive values (94%); its positive predictive value (PPV) is moderate (∼31%). Objectives We studied if, in addition to the presence of inflammation, incorporating information on severity, number and combinations of MRI-inflammatory locations improves the predictive accuracy. Methods In the discovery cohort, 225 CSA-patients were followed on clinical arthritis development. Contrast-enhanced 1.5T MRIs were made of unilateral MCP(2-5), wrist and MTP(1-5)-joints at baseline and scored for synovitis, tenosynovitis and bone marrow edema. Severity, number and combination of locations (joint/tendon/bone) with subclinical inflammation were determined, with symptom-free controls of similar age category as reference. Cox regression was used for predictor selection. Predictive values were determined at 1-year follow-up. Results were validated in 266 CSA-patients. Results In both cohorts 15% developed arthritis <1-year. The number of locations with subclinical inflammation (1-2 locations HR 2.54 (1.11-5.82); ≥3 locations HR 3.75 (1.49-9.48)) and presence of MCP-extensor peritendinitis (HR 4.38 (2.07-9.25)) were independently predictive. Severity and combinations of inflammatory lesions were not. Based on these variables, five risk categories were defined: no subclinical inflammation, 1-2/≥3 locations, with/without MCP-extensor peritendinitis. PPVs ranged 5% (lowest category; NPV 95%) - 67% (highest category). Similar findings were obtained in the validation cohort; PPVs ranged 4% (lowest category; NPV 96%) - 63% (highest category). Conclusion Incorporation of the number of locations with subclinical inflammation and MCP-extensor peritendinitis in MRI-evaluation improved risk stratification, yielding PPVs up to 63-67%. This promotes optimal use of MRI-data in an evidence-based way. Disclosure of Interests Xanthe Matthijssen: None declared, Fenne Wouters: None declared, Debbie Boeters: None declared, Aleid Boer: None declared, Yousra Dakkak: None declared, Ellis Niemantsverdriet: None declared, Saskia Le Cessie: None declared, Annette van der Helm - van Mil Grant/research support from: The research leading to these results has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Starting grant, agreement No 714312) and from the Dutch Arthritis Foundation. The funding source had no role in the design and conduct of the study. Observed percentage of patients that developed clinical arthritis in the first year (PPVs in black) per risk category in the discovery and validation cohorts.