Antidepressant response trajectories and quantitative electroencephalography (QEEG) biomarkers in major depressive disorder
Antidepressant response trajectories and quantitative electroencephalography (QEEG) biomarkers in major depressive disorder
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DOI：
10.1016/j.jpsychires.2009.06.006
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发表时间：
2010-01-01
影响因子：
4.8
通讯作者：
Leuchter, Andrew F.
中科院分区：
文献类型：
--
作者：
Hunter, Aimee M.;Muthen, Bengt O.;Leuchter, Andrew F.
重度抑郁症（MDD）患者在抗抑郁治疗期间症状变化的速率、幅度和稳定性各不相同。生长混合模型（GMM）可用于识别症状严重程度随时间的变化模式。治疗第一周内的定量脑电图（QEEG）一致性与终点临床结局相关，但尚未检查与症状变化模式的关系。94名MDD成人患者随机接受为期8周的氟西汀20 mg或文拉法辛150 mg（n = 49）或安慰剂（n = 45）双盲治疗。探索性随机效应GMM应用于11个时间点的汉密尔顿抑郁量表（Ham-D-17）评分。线性混合模型检查48小时。和1周的变化，QEEG中线和右额叶（MRF）一致性的受试者在GMM轨迹类。在药物治疗受试者中，估计62%的受试者被归类为应答者，21%为无应答者，17%为挥发性药物-即，呈现出一个交替改善和恶化的过程。MRF一致性显示了显著的类别-时间相互作用（F-（2，F-41）= 6.82，p = 0.003）;正如假设的那样，与无应答者相比，应答者显示了显著更大的1周一致性下降（平均差异=-0.76，Std.误差= 34，df = 73，p = 0.03），但不稳定的受试者。具有不稳定症状变化过程的受试者可能值得特殊的临床考虑，并且从研究的角度来看，可能混淆典型二元终点结局的解释。需要诸如GMM的统计方法来识别临床相关的症状反应轨迹。(C)2009爱思唯尔有限公司保留所有权利。
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 20 mg or venlafaxine 150 mg (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,F-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. (C) 2009 Elsevier Ltd. All rights reserved.