Baseline depressive symptoms as predictors of efficacy and tolerability of the treatment with duloxetine: a network analysis approach.

Introduction: Depression is considered one of the most prevalent and burdensome mental disorders. Only 50-60% of patients respond to first-line treatment. Individuals with depression might benefit from personalized treatment, tailored to the individual needs of the patient. In this study, we aimed to explore the baseline characteristics of depressive symptoms associated with a good response to duloxetine treatment using a network analysis. Additionally, the relationship between baseline psychopathological symptoms and treatment tolerability was assessed. Methods: The sample of 88 drug-free patients with active depressive episode, who started monotherapy with increasing doses of duloxetine were evaluated. The Hamilton Depression Rating Scale (HAM-D) was used to assess depression severity and the UKU side effect rating scale to monitor adverse drug reactions (ADRs). A network analysis that explored interactions of specific baseline depression symptoms, treatment efficacy and tolerability was performed. Results: The node representing duloxetine treatment efficacy was directly connected to the nodes representing the first HAM-D item ("depressed mood") (edge weight = 0.191) and duloxetine dose (edge weight = 0.144). The node representing ADRs was directly connected to only one node representing the baseline score of the HAM-D anxiety (psychic) item (edge weight = 0.263). Discussion: Our findings indicate that individuals with depression presenting greater levels of depressed mood and lower levels of anxiety symptoms might better respond to the treatment with duloxetine in terms of efficacy and tolerability.