Biomarkers of erosive arthritis in systemic lupus erythematosus: Application of machine learning models.

ABSTRACT:

Objective

Limited evidences are available on biomarkers to recognize Systemic Lupus erythematosus (SLE) patients at risk to develop erosive arthritis. Anti-citrullinated peptide antibodies (ACPA) have been widely investigated and identified in up to 50% of X-ray detected erosive arthritis; conversely, few studies evaluated anti-carbamylated proteins antibodies (anti-CarP). Here, we considered the application of machine learning models to identify relevant factors in the development of ultrasonography (US)-detected erosive damage in a large cohort of SLE patients with joint involvement.

Methods

We enrolled consecutive SLE patients with arthritis/arthralgia. All patients underwent joint (DAS28, STR) and laboratory assessment (detection of ACPA, anti-CarP, Rheumatoid Factor, SL

SUBMITTER: Ceccarelli F 

PROVIDER: S-EPMC6279013 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature