Patient and physician assessment in difficult-to-treat rheumatoid arthritis: patterns of subjective perception at early stages of b/tsDMARD treatment

ObjectivesTo analyse the trajectories of Disease Activity Score 28 (DAS28), patient global assessment (PGA) and physician global assessment (PhGA) and to assess their predictive capabilities on difficult-to-treat rheumatoid arthritis (D2TRA) classification.MethodsLongitudinal study of patients with rheumatoid arthritis (RA) from 2020 to 2022. Based on the D2TRA EULAR (European Alliance of Associations for Rheumatology) definition, patients were classified as D2TRA according to biological or targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs) failure due to inefficacy (D2TRA-inefficacy) or other reasons (D2TRA-other). Patients who did not fulfil the D2TRA criteria were classified as NoD2TRA. DAS28, PGA and PhGA scores collected every 6 months during the first 24 months of b/tsDMARD treatment were used to identify different trajectories using latent class mixed models (LCMM).ResultsThe study population comprised 255 patients with RA, of whom 167 were NoD2TRA, 58 D2TRA-inefficacy and 30 D2TRA-other. LCMM stratified patients into two different trajectories for DAS28 and PhGA and three for PGA according to the most stable model. The most notable variation occurred during the first 6 months of treatment, thereafter remaining stable during the follow-up period. Most D2TRA-inefficacy patients fitted the trajectory, showing higher values of the studied parameters. NoD2TRA followed the trajectory with lower values, and D2TRA-other were distributed more homogeneously across all trajectories.ConclusionsThe assessment of disease activity, together with patients' and physicians' perceptions, form a key element in the correct discrimination of patients who are going to develop D2TRA-inefficacy. However, identifying those patients who will be D2TRA-other remains challenging, whether by subjective or objective parameters.

Automated summary

The study aims to analyze the trajectories of DAS28, PGA, and PhGA and assess their predictive capabilities for D2TRA classification.