Prediction of radiographic progression pattern in patients with ankylosing spondylitis using group-based trajectory modeling and decision trees.

ABSTRACT:

Objective

This study aimed to identify trajectories of radiographic progression of the spine over time and use them, along with associated clinical factors, to develop a prediction model for patients with ankylosing spondylitis (AS).

Methods

Data from the medical records of patients diagnosed with AS in a single center were extracted between 2001 and 2018. Modified Stoke Ankylosing Spondylitis Spinal Scores (mSASSS) were estimated from cervical and lumbar radiographs. Group-based trajectory modeling classified patients into trajectory subgroups using longitudinal mSASSS data. In multivariate analysis, significant clinical factors associated with trajectories were selected and used to develop a decision tree for prediction of radiographic progression. The most appropriate gro

SUBMITTER: Kang J 

PROVIDER: S-EPMC9631932 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature