NATURALISTIC COURSE OF MAJOR DEPRESSIVE DISORDER PREDICTED BY CLINICAL AND STRUCTURAL NEUROIMAGING DATA: A 5-YEAR FOLLOW-UP.

Abstract

Despite its high recurrence rate, major depression disorder (MDD) still lacks neurobiological markers to optimize treatment selection. The aim of this study was to examine the prognostic potential of clinical and structural magnetic resonance imaging (sMRI) in the long-term MDD clinical outcomes (COs). Forty-nine MDD patients were grouped into one of four different CO categories according to their trajectory: recovery, partial remission, remission recurrence, and chronic depression. Regression models including baseline demographic, clinical, and sMRI data were used for predicting patients' COs and symptom severity 5 years later. The model including only clinical data explained 32.4% of the variance in COs and 55% in HDRS, whereas the model combining clinical and sMRI data increased up to 52/68%, respectively. A bigger volume of right anterior cingulate gyrus was the variable that best predicted COs. The findings suggest that the addition of sMRI brain data to clinical information in depressive patients can significantly improve the prediction of their COs. The dorsal part of the right anterior cingulate gyrus may act as a potential biomarker of long-term clinical trajectories.