Rabinoff M, Kitchen C M R, Cook I A, Leuchter A F
Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA.
Open Med Inform J. 2011;5:1-8. doi: 10.2174/1874431101105010001. Epub 2011 Feb 11.
The study objective was to evaluate the usefulness of Classification and Regression Trees (CART), to classify clinical responders to antidepressant and placebo treatment, utilizing symptom severity and quantitative EEG (QEEG) data. Patients included 51 adults with unipolar depression who completed treatment trials using either fluoxetine, venlafaxine or placebo. Hamilton Depression Rating Scale (HAM-D) and single electrodes data were recorded at baseline, 2, 7, 14, 28 and 56 days. Patients were classified as medication and placebo responders or non-responders. CART analysis of HAM-D scores showed that patients with HAM-D scores lower than 13 by day 7 were more likely to be treatment responders to fluoxetine or venlafaxine compared to non-responders (p=0.001). Youden's index γ revealed that CART models using QEEG measures were more accurate than HAM-D-based models. For patients given fluoxetine, patients with a decrease at day 2 in θ cordance at AF2 were classified by CART as treatment responders (p=0.02). For those receiving venlafaxine, CART identified a decrease in δ absolute power at day 7 at the PO2 region as characterizing treatment responders (p=0.01). Using all patients receiving medication, CART identified a decrease in δ absolute power at day 2 in the FP1 region as characteristic of nonresponse to medication (p=0.003). Optimal trees from the QEEG CART analysis primarily utilized cordance values, but also incorporated some δ absolute power values. The results of our study suggest that CART may be a useful method for identifying potential outcome predictors in the treatment of major depression.
本研究的目的是评估分类与回归树（CART）利用症状严重程度和定量脑电图（QEEG）数据对接受抗抑郁药和安慰剂治疗的临床反应者进行分类的有用性。患者包括51名患有单相抑郁症的成年人，他们完成了使用氟西汀、文拉法辛或安慰剂的治疗试验。在基线、第2、7、14、28和56天记录汉密尔顿抑郁量表（HAM-D）和单电极数据。患者被分类为药物和安慰剂反应者或无反应者。对HAM-D评分的CART分析表明，与无反应者相比，在第7天HAM-D评分低于13的患者更有可能是氟西汀或文拉法辛的治疗反应者（p = 0.001）。尤登指数γ显示，使用QEEG测量的CART模型比基于HAM-D的模型更准确。对于服用氟西汀的患者，CART将在第2天AF2处θ一致性降低的患者分类为治疗反应者（p = 0.02）。对于接受文拉法辛的患者，CART确定在第7天PO2区域δ绝对功率降低是治疗反应者的特征（p = 0.01）。使用所有接受药物治疗的患者，CART确定在第2天FP1区域δ绝对功率降低是对药物无反应的特征（p = 0.003）。QEEG CART分析的最优树主要利用一致性值，但也纳入了一些δ绝对功率值。我们的研究结果表明，CART可能是一种识别重度抑郁症治疗中潜在结果预测指标的有用方法。
