The Tunisian Center of Early Intervention in Psychosis, Department of Psychiatry "Ibn Omrane", Razi hospital, Manouba, 2010, Tunisia.
Faculty of Medicine of Tunis, Tunis El Manar University, Tunis, Tunisia.
BMC Psychiatry. 2023 Aug 15;23(1):595. doi: 10.1186/s12888-023-05101-3.
Dissecting the heterogeneity of schizophrenia may help foster progress in understanding its etiology and lay the groundwork for the development of new treatment options for primary or enduring negative symptoms (NS). In this regard, the present study aimed to: (1) to use cluster analysis to identify subgroups of Lebanese patients diagnosed with either schizophrenia or schizoaffective disorder based on NS clusters, and (2) to relate the statistically-derived subgroups to clinically relevant external validators (including measures if state and trait depression, stigma, insight, loneliness, social support).
A total of 202 adult long-stay, chronic, and clinically remitted patients (166 diagnosed with schizophrenia and 36 with schizoaffective disorder) were enrolled. A cluster analysis approach was adopted to classify patients based on the five NS domains social withdrawal, emotional withdrawal, alogia, avolition and anhedonia.
A three-cluster solution was obtained based on unique NS profiles, and divided patients into (1) low NS (LNS; 42.6%) which characterized by the lowest mean scores in all NS domains, (2) moderate NS (MNS; 25.7%), and (3) high NS (HNS; 31.7%). Post-hoc comparisons showed that depression (state and trait), loneliness and social support could accurately distinguish the schizophrenia subgroups. Additionally, individuals in the HNS cluster had longer duration of illness, longer duration of hospitalization, and were given higher dosages of antipsychotic medication compared to those in the other clusters, but these differences did not achieve the statistical significance.
Findings provide additional support to the categorical model of schizophrenia by confirming the existence of three alternate subtypes based on NS. The determination of distinct NS subgroups within the broad heterogeneous population of people diagnosed with schizophrenia may imply that each subgroup possibly has unique underlying mechanisms and necessitates different treatment approaches.
剖析精神分裂症的异质性可能有助于增进我们对其病因的理解,并为原发性或持续性阴性症状(NS)的新治疗选择奠定基础。在这方面,本研究旨在:(1)使用聚类分析根据 NS 聚类来识别黎巴嫩被诊断为精神分裂症或分裂情感障碍的患者亚组;(2)将统计得出的亚组与临床相关的外部验证器(包括状态和特质抑郁、污名、洞察力、孤独感、社会支持的测量值)相关联。
共纳入 202 名长期住院的慢性缓解成年患者(166 名被诊断为精神分裂症,36 名被诊断为分裂情感障碍)。采用聚类分析方法根据 NS 的五个领域(社交退缩、情感退缩、寡言、意志缺失和快感缺失)对患者进行分类。
基于独特的 NS 特征,得到了一个三聚类解决方案,并将患者分为(1)低 NS(LNS;42.6%),其特点是所有 NS 领域的平均得分最低,(2)中度 NS(MNS;25.7%),和(3)高 NS(HNS;31.7%)。事后比较表明,抑郁(状态和特质)、孤独感和社会支持可以准确区分精神分裂症亚组。此外,与其他亚组相比,HNS 聚类中的个体的疾病持续时间更长、住院时间更长,并且接受的抗精神病药物剂量更高,但这些差异没有达到统计学意义。
研究结果通过确认基于 NS 的三种替代亚型的存在,为精神分裂症的分类模型提供了额外的支持。在被诊断为精神分裂症的广泛异质人群中确定不同的 NS 亚组可能意味着每个亚组可能具有独特的潜在机制,需要不同的治疗方法。