Rheumatoid arthritis (RA) is an example of human chronic inflammatory pain. Modern treatments suppress inflammation, yet pain remains a major problem for many people with RA. We hypothesised that discrete RA subgroups might display favourable or unfavourable pain trajectories when receiving treatment, and that baseline characteristics will predict trajectory allocation.
Growth Mixture Modelling was used to identify discrete trajectories of SF36-Bodily Pain scores during 3 years in 3 RA cohorts (Early RA Network (ERAN); n=683, British Society for Rheumatology Biologics Register Biologics (n=7090) and Non-Biologics (n=1720) cohorts. Logistic regression compared baseline predictor variables between trajectories. The role of inflammation was examined in a subgroup analysis of people with normal levels of inflammatory markers after 3 years.
Mean SF36-Bodily Pain scores in each cohort improved but remained throughout 3y follow up >1 SD worse than the UK general population average. Discrete Persistent Pain (59% to 79% of cohort participants) and Resolving Pain (19% to 27%) trajectories were identified in each cohort. In ERAN, a third trajectory displaying persistently Low Pain (23%) was also identified. In people with normal levels of inflammatory markers after 3 years, 65% of them were found to follow a Persistent Pain trajectory. When trajectories were compared, greater disability (aORs 2.3-2.5 per unit baseline Health Assessment Questionnaire score) and smoking history (aORs 1.6-1.8) were risk factors for Persistent Pain trajectories in each cohort.
In conclusion, distinct trajectories indicate patient subgroups with very different pain prognosis during RA treatment. Inflammation does not fully explain the pain trajectories, and non-inflammatory factors as well as acute phase response predict which trajectory an individual will follow. Targeted treatments additional to those which suppress inflammation might reduce the long term burden of arthritis pain.