ANTI-CCP POSITIVE INDIVIDUALS AT RISK OF PROGRESSION TO INFLAMMATORY ARTHRITIS: WHAT HAPPENS TO BIOMARKERS PRIOR TO PROGRESSION?

Background: Although many predictors of progression to inflammatory arthritis (IA) have been identified at first visit in individuals at risk of developing IA, their fluctuation during follow-up is largely unknown. Objectives: To describe the changes in relevant biomarkers, which precede arthritis development in anti-CCP positive at risk individuals. Methods: In a single centre prospective observational cohort of anti-CCP positive individuals with new musculoskeletal symptoms but without clinical arthritis, 394 individuals with at least 3 available longitudinal datapoints including first, second and last records (progression excluded), were selected. Data on anti-CCP2 antibodies (CCP2), rheumatoid factor (RF), erythrocyte sedimentation rate (ESR), early morning stiffness duration (EMS), tender joint count on examination (TJC28), health assessment questionnaire (HAQ), absence from work in the last 3 months (sick days), and ultrasound power Doppler signal (PD) grade ≥ 1 in small joints, were assessed. Mixed model analysis on repeated measures (MANOVA) were performed, missing data were not imputed. Results: Of the 394 selected individuals, 82 (21%) progressed to IA. In those who progressed, last visit was at a mean (SD) of 6.1 (8) months prior to progression, and total follow-up duration was 33.7 months (26.7) versus 46.5 months (30.2) for those who did not. Within group analysis: in the progressor group there was a significant increase in the value of biomarkers at the visit prior progression for CCP2 +, RF +, EMS, HAQ, and the number of joints with a PD grade ≥ 1 ( Figure 1 , Table 1 ). For sick days from work prior last visit, the increase was non-significant. Table 1. Mixed model ANOVA on repeated measures: pairwise comparison Biomarker Mean (SD)at last visit Analysis between groups Analysis within groups P-value between groups at last visit P-value between second and last visit within the progressor group P-value between second and last visit within non- progressor group Within subject effect CCP2 NP: 71 (108) p<0.001 P=0.008 P=1.000 F(2/257)=3 P: 169 (131) Pŋ = 0.017 P=0.077 RF NP: 37 (73) P<0.001 P=0.012 P=0.973 F(2/304)=15 P: 185 (180) Pŋ = 0.084 P<0.001 ESR NP: 11 (9) p<0.001 P=1.000 P=0.614 F(2/580)=0.1 P: 22 (21) Pŋ < 0.001 P=0.877 EMS NP: 26 (68) P=0.010 P=0.006 P=1.000 F(2/710)=4 Pŋ = 0.018 P:58 (120) P=0.011 TJC28 NP: 0.5 (1.5) P<0.001 P=1.000 P<0.001 F(2/784)=10 P: 3 (5.5) Pŋ < 0.025 P<0.001 Number of joints PD ≥1 NP: 0.7 (2) P=0.020 P=0.001 P=0.055 F(2/318)=4 P: 1 (2) Pŋ = 0.025 P=0.014 HAQ NP: 0.5 (0.6) P=0.105 P=0.016 P=1.000 F(2/494)=2.5 P: 0.7 (0.8) Pŋ = 0.0.009 P=0.086 Number of sick days NP: 2 (6) P=0.204 P=0.457 P=0.492 F(2/360)=4 (Between visit 1 and 3: p=0.042 ) Pŋ = 0.021 P=0.021 P: 4 (13) NP: Non progressors, P: progressors, Pŋ : Partial ŋ + for these results the assumption of homogeneity of variance was violated, as assessed by Levene’s test for equality of variances . In the non-progressor group , only TJC28 and sick days showed significant decrease between first and last visit. Between groups analysis showed significant differences at last visit for the following biomarkers -CCP2 +, RF +, ESR, EMS, TJC28, and number of joints PD grade ≥ 1. The difference in HAQ and sick days was non-significant ( Figure 1 , Table 1 ). A significant difference was also shown in all visits for CCP2 + and RF +, and at the second visit for TJC28. For PD grade ≥ 1, differences at last visit within progressor group and between groups were only significant after selection of last visits < 3 months before progression. Conclusion: These results show for the first time significant changes in relevant biomarkers prior to progression to IA with individual biomarkers having different trajectories. Clinical markers (EMS, TJC28, and HAQ) and ultrasound changed late, whilst immunological (CCP2 and RF values) and inflammation biomarkers (ESR) were different from baseline. These data provide valuable information for longitudinal monitoring of biomarkers, further analysis will show if these changes have predictive value for imminent progression to IA. Disclosure of Interests: Laurence Duquenne: None declared, Kate Harnden: None declared, Leticia Garcia-Montoya: None declared, Navkiran Sidhu: None declared, Jacqueline Nam: None declared, Kulveer Mankia Speakers bureau: AbbVie, Lilly, UCB, Grant/research support from: Gilead, Lilly, Paul Emery Speakers bureau: AbbVie, Gilead, Lilly, Novartis, Consultant of: BMS, AbbVie, MSD, Pfizer, Novartis, Roche, Grant/research support from: Abbvie, BMS, Lilly, Samsung. Citation: , volume 81, supplement 1, year 2022, page 524Session: Rheumatoid arthritis - prognosis, predictors and outcome (POSTERS only)