Hunter Aimee M, Cook Ian A, Leuchter Andrew F
Laboratory of Brain, Behavior, and Pharmacology, 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, USA.
Psychiatr Clin North Am. 2007 Mar;30(1):105-24. doi: 10.1016/j.psc.2006.12.002.
Recent studies have shown overall accuracy rates of 72% and 88% using baseline and/or 1-week change in QEEG biomarkers to predict clinical outcome to treatment with various antidepressant medications. In some cases, findings have been replicated across academic institutions and have been studied in the context of randomized, placebo-controlled trials. Recent EEG findings are corroborated by studies that use techniques with greater spatial resolution (eg, PET, MEG) in localizing brain regions pertinent to clinical response. As such, EEG measurements increasingly are validated by other physiologic measurements that have the ability to assess deeper brain structures. Continued progress along these lines may lead to the realized promise of QEEG biomarkers as predictors of antidepressant treatment outcome in routine clinical practice. In the larger context, use of QEEG technology to predict antidepressant response in major depression may mean that more patients will achieve response and remission with less of the trial-and-error approach that currently accompanies antidepressant treatment.
最近的研究表明，使用定量脑电图生物标志物的基线和/或1周变化来预测各种抗抑郁药物治疗的临床结果，总体准确率分别为72%和88%。在某些情况下，研究结果已在多个学术机构得到重复验证，并在随机、安慰剂对照试验的背景下进行了研究。最近的脑电图研究结果得到了一些研究的证实，这些研究使用具有更高空间分辨率的技术（如正电子发射断层扫描、脑磁图）来定位与临床反应相关的脑区。因此，脑电图测量越来越多地通过其他能够评估更深层脑结构的生理测量来验证。沿着这些方向持续取得进展，可能会实现定量脑电图生物标志物在常规临床实践中作为抗抑郁治疗结果预测指标的前景。从更广泛的背景来看，使用定量脑电图技术预测重度抑郁症的抗抑郁反应，可能意味着更多患者将通过减少目前抗抑郁治疗中伴随的试错方法来实现反应和缓解。
