Kautzky Alexander, Bartova Lucie, Dold Markus, Souery Daniel, Montgomery Stuart, Zohar Joseph, Mendlewicz Julien, Fabbri Chiara, Serretti Alessandro, Tretiakov Evgenii, Rujescu Dan, Harkany Tibor, Kasper Siegfried
Department of Psychiatry and Psychotherapy, Clinical Division of General Psychiatry, Medical University of Vienna, Vienna, Austria.
Department of Clinical Neurosciences, Division of Insurance Medicine, Stockholm, Sweden.
Eur Psychiatry. 2025 May 27;68(1):e61. doi: 10.1192/j.eurpsy.2025.2454.
Heterogeneous symptoms in major depression contribute to unsuccessful antidepressant treatment, termed treatment-resistant depression (TRD). Psychometric network modeling conceptualizes depression as interplay of symptoms with potential benefits for treatment; however, a knowledge gap exists regarding networks in TRD.
Symptoms from 1,385 depressed patients, assessed by the Montgomery-Åsberg-depression rating scale (MADRS) as part of the "TRD-III" cohort of the multinational research consortium "Group for the Studies of Resistant Depression," were used for Gaussian graphical network modeling. Networks were estimated for two timepoints, pretreatment and posttreatment, after the establishment of outcomes response, non-response, and TRD. Applying the network-comparison test, edge weights, and symptom centrality was assessed by bootstrapping. Applying the network-comparison test, outcome groups were compared cross-sectionally and longitudinally regarding the networks' global strength, invariance, and centrality.
Pretreatment networks did not differ in global strength, but outcome groups showed distinct symptom connections. For both response and TRD, global strength was reduced posttreatment, leading to significant differences between each pair of networks posttreatment. Sadness, lassitude, inability-to-feel, and pessimistic thoughts ranked most centrally in unfavorable outcomes, while reduced-appetite and suicidal thoughts were more densely connected in response. Connections between central symptoms increased in strength following unsuccessful treatment, particularly regarding links involving pessimistic thoughts in TRD.
Treatment reduced global network strength across outcome groups. However, distinct symptom networks were found in patients showing response to treatment, non-response, and TRD. More easily targetable symptoms such as reduced-appetite were central to networks in patients with response, while pessimistic thoughts may be a key symptom upholding disease burden in TRD.
重度抑郁症的异质性症状导致抗抑郁治疗效果不佳,即治疗抵抗性抑郁症(TRD)。心理测量网络模型将抑郁症概念化为症状之间的相互作用,这对治疗可能有益;然而,关于TRD中的网络存在知识空白。
来自1385名抑郁症患者的症状,通过蒙哥马利-Åsberg抑郁量表(MADRS)进行评估,作为跨国研究联盟“抵抗性抑郁症研究小组”的“TRD-III”队列的一部分,用于高斯图形网络建模。在确定结局为缓解、未缓解和TRD后,对治疗前和治疗后两个时间点的网络进行估计。应用网络比较测试,通过自抽样评估边权重和症状中心性。应用网络比较测试,对结局组在网络的全局强度、不变性和中心性方面进行横断面和纵向比较。
治疗前网络在全局强度上没有差异,但结局组显示出不同的症状联系。对于缓解和TRD,治疗后全局强度均降低,导致治疗后每对网络之间存在显著差异。悲伤、疲倦、无法感受和悲观想法在不良结局中排名最核心,而食欲减退和自杀念头在缓解方面联系更紧密。治疗失败后,核心症状之间的联系强度增加,特别是在TRD中涉及悲观想法的联系。
治疗降低了各结局组的全局网络强度。然而,在显示治疗缓解、未缓解和TRD的患者中发现了不同的症状网络。更容易靶向治疗的症状如食欲减退在缓解患者的网络中处于核心地位,而悲观想法可能是维持TRD疾病负担的关键症状。