Latent Class Trajectory Modeling of 2-Component Disease Activity Score in 28 Joints Identifies Multiple Rheumatoid Arthritis Phenotypes of Response to Biologic Disease-Modifying Antirheumatic Drugs

Objectives: To determine whether using a re‐weighted disease activity score that better reflects joint synovitis, the 2‐component DAS28 (2C‐DAS28), based on 28‐swollen joint count and C‐reactive protein, produces more clinically relevant treatment outcome trajectories compared with the standard 4 component DAS28 (4C‐DAS28). Methods: Latent class mixed modelling (LCMM) of response to biologic treatment was applied to 2,991 patients with RA about to commence bDMARD treatment from the Biologics in Rheumatoid Arthritis Genetics and Genomics Study Syndicate (BRAGGSS) cohort using both 4C‐DAS28 and 2C‐DAS28 as outcomes. Identified patient groups with similar trajectories were compared in terms of pre‐treatment baseline characteristics – including disability, comorbidities ‐ and follow‐up characteristics – including anti‐drug antibody (ADAb) events, adherence to treatments and blood drug levels, We compared the trajectories obtained using the 4C and 2C scores to determine which characteristics were better captured by the 2CDAS28 compared with the 4C‐DAS28 trajectories. Results: Using the 4C‐DAS28 we identified 3 trajectory groups, which is consistent with previous reports. We show that the 4C‐DAS28 captures information relating to depression. Using the 2C‐DAS28, 7 trajectory groups were identified; among them, distinct groups of non‐responders had a higher incidence of respiratory comorbidities and a higher proportion of ADAb events. We also identified a group of participants for which the 2C‐DAS28 disease activity score remained relatively low and which was enriched for patients who were non‐adherent to treatment. This highlights the utility of both the 4C and 2C‐DAS28 for monitoring different components of disease activity. Conclusions: Here we show that the 2C‐DAS28 modified disease activity score defines important biological and clinical phenotypes associated with treatment outcome in RA and characterizes important underlying response mechanisms to biologic drugs.