Fornaro Michele, Fusco Andrea, Novello Stefano, Mosca Pierluigi, Anastasia Annalisa, De Blasio Antonella, Iasevoli Felice, de Bartolomeis Andrea
Laboratory of Molecular and Translational Psychiatry, Unit of Treatment-Resistant Psychosis, Section of Psychiatry, University of Naples Federico II, Naples, Italy.
Polyedra Research Group, Teramo, Italy.
Front Psychiatry. 2020 May 15;11:438. doi: 10.3389/fpsyt.2020.00438. eCollection 2020.
Treatment-resistant depression (TRD) and treatment-resistant bipolar depression (TRBD) poses a significant clinical and societal burden, relying on different operational definitions and treatment approaches. The detection of clinical predictors of resistance is elusive, soliciting clinical subtyping of the depressive episodes, which represents the goal of the present study.
A hundred and thirty-one depressed outpatients underwent psychopathological evaluation using major rating tools, including the Hamilton Rating Scale for Depression, which served for subsequent principal component analysis, followed-up by cluster analysis, with the ultimate goal to fetch different clinical subtypes of depression.
The cluster analysis identified two clinically interpretable, yet distinctive, groups among 53 bipolar (resistant cases = 15, or 28.3%) and 78 unipolar (resistant cases = 20, or 25.6%) patients. Among the MDD patients, cluster "1" included the following components: "Psychic symptoms, depressed mood, suicide, guilty, insomnia" and "genitourinary, gastrointestinal, weight loss, insight". Altogether, with broadly defined "mixed features," this latter cluster correctly predicted treatment outcome in 80.8% cases of MDD. The same "broadly-defined" mixed features of depression (namely, the standard Diagnostic and Statistical Manual for Mental Disorders, Fifth Edition-DSM-5-specifier plus increased energy, psychomotor activity, irritability) correctly classified 71.7% of BD cases, either as TRBD or not.
Small sample size and high rate of comorbidity.
Although relying on different operational criteria and treatment history, TRD and TRBD seem to be consistently predicted by broadly defined mixed features among different clinical subtypes of depression, either unipolar or bipolar cases. If replicated by upcoming studies to encompass also biological and neuropsychological measures, the present study may aid in precision medicine and informed pharmacotherapy.
难治性抑郁症（TRD）和难治性双相抑郁症（TRBD）带来了重大的临床和社会负担，它们依赖于不同的操作定义和治疗方法。耐药临床预测因素的检测难以捉摸，这促使对抑郁发作进行临床亚型分类，这也是本研究的目标。
131名门诊抑郁症患者使用主要评分工具进行了精神病理学评估，包括汉密尔顿抑郁量表，该量表用于后续的主成分分析，随后进行聚类分析，最终目标是得出不同的抑郁症临床亚型。
聚类分析在53例双相情感障碍患者（耐药病例 = 15例，占28.3%）和78例单相情感障碍患者（耐药病例 = 20例，占25.6%）中确定了两个具有临床可解释性但又截然不同的组。在重度抑郁症（MDD）患者中，聚类“1”包括以下成分：“精神症状、情绪低落、自杀、内疚、失眠”和“泌尿生殖系统、胃肠道、体重减轻、洞察力”。总的来说，具有广义定义的“混合特征”，后一个聚类在80.8%的MDD病例中正确预测了治疗结果。相同的广义定义的抑郁症“混合特征”（即《精神疾病诊断与统计手册》第五版-DSM-5-说明符加上精力增加、精神运动性活动、易怒）正确分类了71.7%的双相情感障碍病例，无论是否为难治性双相抑郁症。
样本量小和合并症发生率高。
尽管依赖于不同的操作标准和治疗史，但广义定义的混合特征似乎能一致地预测单相或双相抑郁症不同临床亚型中的TRD和TRBD。如果未来的研究能够重复本研究并纳入生物学和神经心理学测量，本研究可能有助于精准医学和明智的药物治疗。
