Machine learning to characterize bone biomarkers profile in rheumatoid arthritis.

ABSTRACT:

Background

Bone metabolism is disrupted in rheumatoid arthritis (RA); however, the bone metabolic signature of RA is poorly known. The objective of the study is to further characterize the bone metabolic profile of RA and compare it to psoriatic arthritis (PsA), systemic sclerosis (SSc) and healthy controls.

Methods

We did a cross-sectional case-control study on consecutively enrolled patients and age-matched controls. We collected clinical characteristics, serum biomarkers related to bone metabolism and Bone Mineral Density (BMD). A multiple correlation analysis using Spearman's rank correlation coefficient was conducted within the RA patient group to investigate associations between biomarker levels and clinical variables. Machine learning (ML) models and Principal Compone

SUBMITTER: Adami G 

PROVIDER: S-EPMC10665911 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature