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本文引用的文献

1
Network Analysis Reveals Which Negative Symptom Domains Are Most Central in Schizophrenia vs Bipolar Disorder.网络分析揭示了精神分裂症与双相情感障碍中哪些阴性症状领域最为核心。
Schizophr Bull. 2019 Oct 24;45(6):1319-1330. doi: 10.1093/schbul/sby168.
2
Robustness and replicability of psychopathology networks.精神病理学网络的稳健性与可重复性。
World Psychiatry. 2018 Jun;17(2):143-144. doi: 10.1002/wps.20515.
3
Using network analysis for the prediction of treatment dropout in patients with mood and anxiety disorders: A methodological proof-of-concept study.应用网络分析预测心境和焦虑障碍患者的治疗脱落:方法学概念验证研究。
Sci Rep. 2018 May 18;8(1):7819. doi: 10.1038/s41598-018-25953-0.
4
The brief negative symptom scale (BNSS): Sensitivity to treatment effects.简短阴性症状量表(BNSS):对治疗效果的敏感性。
Schizophr Res. 2018 Jul;197:269-273. doi: 10.1016/j.schres.2017.11.031. Epub 2017 Dec 21.
5
Efficacy and Safety of MIN-101: A 12-Week Randomized, Double-Blind, Placebo-Controlled Trial of a New Drug in Development for the Treatment of Negative Symptoms in Schizophrenia.MIN-101 的疗效和安全性:一种新型药物治疗精神分裂症阴性症状的 12 周随机、双盲、安慰剂对照试验。
Am J Psychiatry. 2017 Dec 1;174(12):1195-1202. doi: 10.1176/appi.ajp.2017.17010122. Epub 2017 Jul 28.
6
A network theory of mental disorders.精神障碍的网络理论。
World Psychiatry. 2017 Feb;16(1):5-13. doi: 10.1002/wps.20375.
7
A review of reward processing and motivational impairment in schizophrenia.精神分裂症中奖励处理与动机障碍的综述。
Schizophr Bull. 2014 Mar;40 Suppl 2(Suppl 2):S107-16. doi: 10.1093/schbul/sbt197. Epub 2013 Dec 27.
8
Network analysis: an integrative approach to the structure of psychopathology.网络分析:精神病理学结构的综合方法。
Annu Rev Clin Psychol. 2013;9:91-121. doi: 10.1146/annurev-clinpsy-050212-185608.
9
Dissociation of hedonic reaction to reward and incentive motivation in an animal model of the negative symptoms of schizophrenia.在精神分裂症阴性症状的动物模型中,对奖赏的愉悦反应与激励动机的分离。
Neuropsychopharmacology. 2012 Jun;37(7):1699-707. doi: 10.1038/npp.2012.15. Epub 2012 Mar 14.
10
Goal representations and motivational drive in schizophrenia: the role of prefrontal-striatal interactions.精神分裂症中的目标表示和动机驱动:前额叶-纹状体相互作用的作用。
Schizophr Bull. 2010 Sep;36(5):919-34. doi: 10.1093/schbul/sbq068. Epub 2010 Jun 21.

网络分析表明,动力缺乏是成功治疗阴性症状的最核心领域:来自罗匹尼罗随机临床试验的证据。

Network Analysis Indicates That Avolition Is the Most Central Domain for the Successful Treatment of Negative Symptoms: Evidence From the Roluperidone Randomized Clinical Trial.

机构信息

Department of Psychology, University of Georgia, Athens, GA.

Department of Systems Science and Industrial Engineering & Center for Collective Dynamics of Complex Systems, Binghamton University, Binghamton, NY.

出版信息

Schizophr Bull. 2020 Jul 8;46(4):964-970. doi: 10.1093/schbul/sbz141.

DOI:10.1093/schbul/sbz141
PMID:31989151
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7342174/
Abstract

A recent conceptual development in schizophrenia is to view its manifestations as interactive networks rather than individual symptoms. Negative symptoms, which are associated with poor functional outcome and reduced rates of recovery, represent a critical need in schizophrenia therapeutics. MIN101 (roluperidone), a compound in development, demonstrated efficacy in the treatment of negative symptoms in schizophrenia. However, it is unclear how the drug achieved its effect from a network perspective. The current study evaluated the efficacy of roluperidone from a network perspective. In this randomized clinical trial, participants with schizophrenia and moderate to severe negative symptoms were randomly assigned to roluperidone 32 mg (n = 78), 64 mg (n = 83), or placebo (N = 83). Macroscopic network properties were evaluated to determine whether roluperidone altered the overall density of the interconnections among symptoms. Microscopic properties were evaluated to examine which individual symptoms were most influential (ie, interconnected) on other symptoms in the network and are responsible for successful treatment effects. Participants receiving roluperidone did not differ from those randomized to placebo on macroscopic properties. However, microscopic properties (degree and closeness centrality) indicated that avolition was highly central in patients receiving placebo and that roluperidone reduced this level of centrality. These findings suggest that decoupling the influence of motivational processes from other negative symptom domains is essential for producing global improvements. The search for pathophysiological mechanisms and targeted treatment development should be focused on avolition, with the expectation of improvement in the entire constellation of negative symptoms if avolition is effectively treated.

摘要

精神分裂症的一个最新概念发展是将其表现视为相互作用的网络,而不是单个症状。阴性症状与较差的功能结果和较低的恢复率相关,是精神分裂症治疗的一个关键需求。MIN101(罗鲁培酮)是一种正在开发的化合物,已被证明在治疗精神分裂症的阴性症状方面有效。然而,从网络角度来看,药物如何实现其效果尚不清楚。本研究从网络角度评估了罗鲁培酮的疗效。在这项随机临床试验中,患有精神分裂症和中度至重度阴性症状的参与者被随机分配接受罗鲁培酮 32mg(n=78)、64mg(n=83)或安慰剂(n=83)。评估宏观网络特性,以确定罗鲁培酮是否改变了症状之间相互联系的整体密度。评估微观特性,以检查哪些单个症状在网络中对其他症状最具影响力(即相互关联),并负责治疗效果的成功。接受罗鲁培酮治疗的参与者与随机分配接受安慰剂的参与者在宏观特性上没有差异。然而,微观特性(度数和接近中心性)表明,在接受安慰剂的患者中,意志减退是高度中心的,而罗鲁培酮降低了这种中心性水平。这些发现表明,从其他阴性症状领域解耦动机过程的影响对于产生整体改善至关重要。寻找病理生理机制和靶向治疗开发应该集中在意志减退上,如果有效地治疗意志减退,预计整个阴性症状群体会得到改善。