Systemic lupus erythematosus damage risk index (SLE-DRI): a simple machine learning-based tool for identifying patients at risk for early organ damage.

ABSTRACT:

Objective

Organ damage is a key determinant of poor prognosis and increased mortality in systemic lupus erythematosus (SLE). However, no validated clinical tools for predicting damage accumulation currently exist. We sought to develop a machine learning-based model to predict early organ damage in patients with SLE.

Methods

Classification criteria (American College of Rheumatology (ACR)-1997, Systemic Lupus International Collaborating Clinics (SLICC)-2012, European League Against Rheumatism (EULAR)/ACR-2019) and non-criteria features of a cohort of 914 patients with SLE were analysed to predict damage (defined as SLICC/ACR Damage Index (SDI)) within 5 years since diagnosis. Feature selection and model construction were performed using the least absolute shrinkage and selecti

SUBMITTER: Garantziotis P 

PROVIDER: S-EPMC12496050 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature