Semel Institute for Neuroscience and Human Behavior at UCLA, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA 90024-1759, United States.
J Psychiatr Res. 2010 Jan;44(2):90-8. doi: 10.1016/j.jpsychires.2009.06.006. Epub 2009 Jul 24.
Individuals with Major Depressive Disorder (MDD) vary regarding the rate, magnitude and stability of symptom changes during antidepressant treatment. Growth mixture modeling (GMM) can be used to identify patterns of change in symptom severity over time. Quantitative electroencephalographic (QEEG) cordance within the first week of treatment has been associated with endpoint clinical outcomes but has not been examined in relation to patterns of symptom change. Ninety-four adults with MDD were randomized to eight weeks of double-blinded treatment with fluoxetine 20mg or venlafaxine 150mg (n=49) or placebo (n=45). An exploratory random effect GMM was applied to Hamilton Depression Rating Scale (Ham-D(17)) scores over 11 timepoints. Linear mixed models examined 48-h, and 1-week changes in QEEG midline-and-right-frontal (MRF) cordance for subjects in the GMM trajectory classes. Among medication subjects an estimated 62% of subjects were classified as responders, 21% as non-responders, and 17% as symptomatically volatile-i.e., showing a course of alternating improvement and worsening. MRF cordance showed a significant class-by-time interaction (F((2,41))=6.82, p=.003); as hypothesized, the responders showed a significantly greater 1-week decrease in cordance as compared to non-responders (mean difference=-.76, Std. Error=.34, df=73, p=.03) but not volatile subjects. Subjects with a volatile course of symptom change may merit special clinical consideration and, from a research perspective, may confound the interpretation of typical binary endpoint outcomes. Statistical methods such as GMM are needed to identify clinically relevant symptom response trajectories.
患有重性抑郁障碍（MDD）的个体在抗抑郁治疗期间的症状变化速度、幅度和稳定性各不相同。增长混合建模（GMM）可用于识别症状严重程度随时间的变化模式。治疗开始后第一周内的定量脑电图（QEEG）一致性与终点临床结局相关，但尚未与症状变化模式相关联进行检查。94 名 MDD 成年人被随机分配至接受氟西汀 20mg 或文拉法辛 150mg （n=49）或安慰剂（n=45）为期 8 周的双盲治疗。对汉密尔顿抑郁评定量表（Ham-D(17)）的 11 个时间点的评分进行了探索性随机效应 GMM 分析。线性混合模型检查了 GMM 轨迹类别的受试者的 48 小时和 1 周 QEEG 中线和右额（MRF）一致性变化。在药物治疗组中，估计有 62%的受试者被归类为反应者，21%为非反应者，17%为症状波动者，即表现出交替改善和恶化的病程。MRF 一致性显示出显著的类-时间交互作用（F((2,41))=6.82，p=.003）；正如假设的那样，与非反应者相比，反应者的一致性在 1 周内显著下降（平均差异=-.76，标准误差=.34，df=73，p=.03），但不稳定者则没有。症状变化具有波动性的患者可能需要特别的临床关注，并且从研究角度来看，可能会混淆典型的二元终点结局的解释。需要使用 GMM 等统计方法来识别具有临床意义的症状反应轨迹。
