Identification of trajectories of radiographic damage in rheumatoid arthritis (RA) by clustering patients according to the shape of their curve of Sharp-van der Heijde scores (SHSs) over time. Developing models to predict their progression cluster from baseline characteristics.
Patient-level data over a 2-year period from five large randomised controlled trials on tumour necrosis factor inhibitors in RA were used. SHSs were clustered in a shape-respecting manner to identify distinct clusters of radiographic progression. Characteristics of patients within different progression clusters were compared at baseline and over time. Logistic regression models were developed to predict trajectory of radiographic progression using information at baseline.
In total, 1887 patients with 7738 X-rays were used for cluster analyses. We identified four distinct clusters with characteristic shapes of radiographic progression: one with a stable SHS over the whole 2-year period (C0/lowChange; 86%); one with relentless progression (C1/rise; 5.8%); one with decreasing SHS (C2/improvement; 6.9%); one going up and down (C3/bothWays; 1.4%) of the SHS. Robustness of clusters were confirmed using different clustering methods. Regression models identified disease duration, baseline C-reactive protein (CRP) and SHS and treatment status as predictors for cluster assignment.
We were able to identify and partly characterise four different clusters of radiographic progression over time in patients with RA, most remarkably one with relentless progression and another one with amelioration of joint damage over time, suggesting the existence of distinct patterns of joint damage accrual in RA.