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

Abstract

IntroductionDepression 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.MethodsThe 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.ResultsThe 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).DiscussionOur 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.

An Exploratory Graphical Analysis of the Montgomery-Åsberg Depression Rating Scale Pre- and Post-Treatment using Pooled Antidepressant Trial Secondary Data

“…For example, a network analysis of 88 outpatient clinic attendees showed that duloxetine may result in better outcomes, in terms of efficacy and tolerability, for patients with high levels of depressed mood. This study also showed that high centrality of anxiety interfered with depression treatment outcomes (Maciaszek et al 2023). In other words, Maciaszek et al found that depression presenting with higher levels of depressed mood and lower levels of anxiety might respond better to treatment with duloxetine.…”

“…These indices can be used to identify the most central symptoms in a network model, with the aim of developing treatment interventions targeted at these specific symptoms (Borsboom 2017;Borsboom & Cramer 2013). Studies using clinical trial data support this contention (Park et al 2021;Bringmann et al 2015, Maciaszek et al 2023. For example, a network analysis of 88 outpatient clinic attendees showed that duloxetine may result in better outcomes, in terms of efficacy and tolerability, for patients with high levels of depressed mood.…”

“…While existing research (Park et al 2021;Bringmann et al 2015, Maciaszek et al 2023 provides support for the assertion that NA can be used to inform targeted treatment plans (Borsboom 2017;Borsboom & Cramer 2013;Maciaszek et al 2023), these studies have some critical limitations. For example, Whiston et al ( 2022) and An et al (2019) only examined pre-treatment data, at one time-point.…”

The Impact of the CYP2D6 and CYP1A2 Gene Polymorphisms on Response to Duloxetine in Patients with Major Depression

“…The exclusion criteria were a lifetime diagnosis of schizophrenia, bipolar disorder, dementia, substance use disorders (except of nicotine dependence), severe or unstable somatic conditions, and noncompliance with duloxetine monotherapy. The patients participated in regular psychiatric consultations every 4 weeks, during which the dosage was adjusted according to the protocol described in detail in the previous publication [18]. The study was approved by the Ethics Committee at Wroclaw Medical University (approval number: 606/2017).…”