Identifying trajectories of radiographic spinal disease in ankylosing spondylitis: a 15-year follow-up study of the PSOAS cohort

Abstract

Objectives: Little is known with certainty about the natural history of spinal disease progression in ankylosing spondylitis (AS). Our objective was to discover if there were distinct patterns of change in vertebral involvement over time and to study associated clinical factors.

Methods: Data were analysed from the Prospective Study of Outcomes in Ankylosing Spondylitis (PSOAS) observational cohort. All patients met modified New York Criteria for AS and had ≥2 sets of radiographs scored by modified Stoke Ankylosing Spondylitis Spinal Score (mSASSS) by two independent readers between 2002 and 2017. Group-based trajectory modelling (GBTM) was used to classify patients into distinct groups of longitudinal mSASSS considering sociodemographic and clinical covariables. The optimal trajectory model and number of trajectories was selected using Nagin's Bayesian information criterion (BIC).

Results: A total of 561 patients with 1618 radiographs were analysed. The optimum number of trajectory groups identified was four (BIC -4062). These groups were subsequently categorized as: non-progressors (204 patients), late-progressors (147 patients), early-progressors (107 patients) and rapid-progressors (103 patients). Baseline predictors associated with higher spinal disease burden groups included: baseline mSASSS, male gender, longer disease duration, elevated CRP and smoking history. In addition, time-varying anti-TNF use per year was associated with decreased mSASSS progression only in the rapid-progressor group.

Conclusions: GBTM identified four distinct patterns of spinal disease progression in the PSOAS cohort. Male gender, longer disease duration, elevated CRP and smoking were associated with higher spinal disease groups. Independent confirmation in other AS cohorts is needed to confirm these radiographic patterns.

Keywords: ankylosing spondylitis; longitudinal modeling.