Identification of biomarkers by machine learning classifiers to assist diagnose rheumatoid arthritis-associated interstitial lung disease.

ABSTRACT:

Background

This study aimed to search for blood biomarkers among the profiles of patients with RA-ILD by using machine learning classifiers and probe correlations between the markers and the characteristics of RA-ILD.

Methods

A total of 153 RA patients were enrolled, including 75 RA-ILD and 78 RA-non-ILD. Routine laboratory data, the levels of tumor markers and autoantibodies, and clinical manifestations were recorded. Univariate analysis, least absolute shrinkage and selection operator (LASSO), random forest (RF), and partial least square (PLS) were performed, and the receiver operating characteristic (ROC) curves were plotted.

Results

Univariate analysis showed that, compared to RA-non-ILD, patients with RA-ILD were older (p < 0.001), had higher white blood cell (p 

SUBMITTER: Qin Y 

PROVIDER: S-EPMC9118651 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature