Predictors of rituximab efficacy in systemic sclerosis-associated interstitial lung disease: machine-learning analysis of the DESIRES trial.

ABSTRACT:

Objectives

Rituximab is emerging as a promising therapeutic option for systemic sclerosis-associated interstitial lung disease (SSc-ILD). However, little is known about factors that predict the efficacy of rituximab in SSc-ILD.

Methods

A post-hoc analysis was performed on prospective data from 48 patients with SSc-ILD in the double-blind, randomized, placebo-controlled DESIRES trial. A total of 28 baseline factors were selected as candidates to predict the efficacy of rituximab on the percentage of predicted forced vital capacity (ppFVC) at 24 weeks. A machine learning causal tree algorithm was used to explore the combination of predictors to identify subpopulations with a good response to rituximab.

Results

Serum levels of C-reactive protein (CRP) and Krebs von den L

SUBMITTER: Kuzumi A 

PROVIDER: S-EPMC12695043 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature