Research and Diagnostic Algorithmic Rules (RADAR) and RADAR plots for the first episode of major depressive disorder: effects of childhood and recent adverse experiences on suicidal behaviors, neurocognition and phenome features

Abstract

AbstractThis study was performed to ascertain whether a) a valid precision model and valid Research and Diagnostic Algorithmic Rules (RADAR) scores can be computed in patients experiencing first-episode depression; and b) adverse childhood experiences (ACEs) and negative life events (NLEs) are associated with suicidal behavior (SBs), cognitive impairment, and phenome RADAR scores.This study recruited 90 patients with major depressive disorder (MDD) in an acute phase, of whom 71 showed a first-episode MDD (FEM), and 40 controls. We constructed RADAR scores for ACEs, NLEs encountered the last year, SBs and severity of depression, anxiety, chronic fatigue and physiosomatic symptoms using the Hamilton Depression and Anxiety Rating scales and the Fibro-Fatigue scale.Partial least squares analysis showed that in FEM, one latent vector (labelled the phenome of FEM) could be extracted from depressive, anxiety, fatigue, physiosomatic, melancholia, and insomnia symptoms, SBs, and cognitive impairments. The latter were conceptualized as a latent vector extracted from the Verbal Fluency Test, Mini Mental State Examination, and ratings of memory and judgment, indicating a generalized cognitive decline (G-CoDe). We found that 60.8% of the variance in the FEM phenome was explained by the cumulative effects of NLEs and ACEs, in particular emotional neglect and, to a lesser extent, physical abuse, and by the interaction between ACEs and physical abuse, whereby the latter attenuates the effects of NLEs.In conclusion, not the binary diagnosis of MDD (DSM/ICD) should be used in research and clinical settings but the RADAR scores and plots constructed here.