Biomarker-based subtyping of depression and anxiety disorders using Latent Class Analysis. A NESDA study.

ABSTRACT:

Background

Etiological research of depression and anxiety disorders has been hampered by diagnostic heterogeneity. In order to address this, researchers have tried to identify more homogeneous patient subgroups. This work has predominantly focused on explaining interpersonal heterogeneity based on clinical features (i.e. symptom profiles). However, to explain interpersonal variations in underlying pathophysiological mechanisms, it might be more effective to take biological heterogeneity as the point of departure when trying to identify subgroups. Therefore, this study aimed to identify data-driven subgroups of patients based on biomarker profiles.

Methods

Data of patients with a current depressive and/or anxiety disorder came from the Netherlands Study of Depression and Anxi

SUBMITTER: Beijers L 

PROVIDER: S-EPMC6393228 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature