Which Residual Symptoms Predict Relapse in major Depression? A Scoping Review: Quels symptômes résiduels constituent des prédicteurs de rechute de dépression majeure? Un examen de la portée.

BackgroundPreventing relapse following a successful acute treatment of major depressive disorder (MDD) remains a clinical challenge. The presence of residual depressive symptoms seems to be a reliable predictor of relapse. However, few studies have systematically evaluated the relative contribution of specific residual symptoms to relapse risk.ObjectiveThis review synthesizes studies investigating the association between individual residual depressive symptoms and relapse risk following a successful acute treatment of MDD.MethodsA scoping review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines. A systematic literature search was performed using terms related to depression, residual symptoms and relapse.ResultsEleven studies were included. Residual sleep disturbance and anxiety showed a statistically significant association with increased relapse risk in most studies assessing these symptoms. Most studies assessing residual fatigue, appetite, weight change, depressed mood or diminished interest did not observe statistically significant associations with relapse risk. Findings regarding agitation or restlessness and decreased libido were mixed, with some studies reporting statistically significant associations while others did not. A variety of symptom rating scales was used to assess residual depressive symptoms, resulting in substantial heterogeneity.ConclusionSpecific residual depressive symptoms, notably sleep disturbance and anxiety, may serve as predictors of increased relapse risk and should alert clinicians. However, substantial heterogeneity across studies limits the consistency and generalizability of these findings. Standardized and multidimensional assessment strategies, integrating both clinician-rated and self-report instruments, are needed to comprehensively capture the residual symptom burden and improve relapse risk prediction.