Cluster analysis of people with axial spondyloarthritis using TNFi identified two distinctive clinical phenotypes. These clusters were found to have different clinical characteristics, treatment responses, disease activity, and TNFi drug survival probabilities.

A study was conducted for classifying the distinct group of people with axial spondyloarthritis on tumor necrosis factor-alpha inhibitors (TNFi) as per the baseline characteristics with the aid of a clustering algorithm.

Evaluation of the clinical characteristics and demographic data of axial spondyloarthritis people incorporated in the Korean College of Rheumatology Biologics and Targeted Therapy (KOBIO) registry was done. With the aid of divisive hierarchical cluster assessment, the patterns of disease manifestations were investigated. Following clustering, the clinical characteristics of people and the drug survival of TNFi between the classified groups were examined.

Overall, 1042 people were investigated. The cluster assessment segregated people into 2 groups: (i) The axial group (n = 828) primarily demonstrating isolated axial manifestations, and (ii) Extra-axial group more frequently demonstrating extra-axial symptoms (n = 214). Compared to the axial group, almost all extra-axial symptoms (psoriasis, peripheral arthritis, uveitis, enthesitis) were more frequently reported in the extra-axial group.

Furthermore, the extra-axial group exhibited greater disease activity, later disease onset, and a shorter duration of disease when compared to the axial group. Following one year of TNFi therapy, the two groups demonstrated similar disease activity. When compared to the axial group, the extra-axial group displayed a lower drug survival probability with TNFi, as shown in Figure 1:

The cluster analysis of axial spondyloarthritis people treated with TNFi revealed 2 groups. One group is characterized by isolated axial disorder with longer disease duration and earlier disease onset while the other group is characterized by more frequent peripheral spondyloarthritis features.