Developing a data-driven algorithm for guiding selection between cognitive behavioral therapy, fluoxetine, and combination treatment for adolescent depression.

ABSTRACT: Treating adolescent depression effectively requires providing interventions that are optimally suited to patients' individual characteristics and needs. Therefore, we aim to develop an algorithm that matches patients with optimal treatment among cognitive-behavioral therapy (CBT), fluoxetine (FLX), and combination treatment (COMB). We leveraged data from a completed clinical trial, the Treatment for adolescents with depression study, where a wide range of demographic, clinical, and psychosocial measures were collected from adolescents diagnosed with major depressive disorder prior to treatment. Machine-learning techniques were employed to derive a model that predicts treatment response (week 12 children's depression rating scale-revised [CDRS-R]) to CBT, FLX, and COMB. The resulting model

SUBMITTER: Gunlicks-Stoessel M 

PROVIDER: S-EPMC7506003 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature