Machine Learning Prediction of Treatment Response to Inhaled Corticosteroids in Asthma.

ABSTRACT:

Background

Although inhaled corticosteroids (ICS) are the first-line therapy for patients with persistent asthma, many patients continue to have exacerbations. We developed machine learning models to predict the ICS response in patients with asthma.

Methods

The subjects included asthma patients of European ancestry (n = 1371; 448 children; 916 adults). A genome-wide association study was performed to identify the SNPs associated with ICS response. Using the SNPs identified, two machine learning models were developed to predict ICS response: (1) least absolute shrinkage and selection operator (LASSO) regression and (2) random forest.

Results

The LASSO regression model achieved an AUC of 0.71 (95% CI 0.67-0.76; sensitivity: 0.57; specificity: 0.75) in an independ

SUBMITTER: Ong MS 

PROVIDER: S-EPMC10970828 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature