Predictors of pharmacotherapy outcomes for body dysmorphic disorder: a machine learning approach.

ABSTRACT:

Background

Serotonin-reuptake inhibitors (SRIs) are first-line pharmacotherapy for the treatment of body dysmorphic disorder (BDD), a common and severe disorder. However, prior research has not focused on or identified definitive predictors of SRI treatment outcomes. Leveraging precision medicine techniques such as machine learning can facilitate the prediction of treatment outcomes.

Methods

The study used 10-fold cross-validation support vector machine (SVM) learning models to predict three treatment outcomes (i.e. response, partial remission, and full remission) for 97 patients with BDD receiving up to 14-weeks of open-label treatment with the SRI escitalopram. SVM models used baseline clinical and demographic variables as predictors. Feature importance analyses complement

SUBMITTER: Curtiss JE 

PROVIDER: S-EPMC9836197 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature