Resting-state EEG delta and alpha power predict response to cognitive behavioral therapy in depression: a Canadian biomarker integration network for depression study.
Resting-state EEG delta and alpha power predict response to cognitive behavioral therapy in depression: a Canadian biomarker integration network for depression study.
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DOI：
10.1038/s41598-023-35179-4
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发表时间：
2023-05-24
影响因子：
4.6
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中科院分区：
文献类型：
--
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认知行为疗法（CBT）通常被推荐作为抑郁症的一线治疗方法。然而，获得CBT的机会仍然有限，高达50%的患者没有从这种治疗中获益。识别能够预测哪些患者会对CBT有反应的生物标志物可能有助于设计最佳的治疗分配策略。在加拿大抑郁症生物标志物整合网络（CAN-BIND）研究中，招募了41名成年抑郁症患者进行为期16周的CBT疗程，其中30人在基线和治疗第2周时记录静息状态脑电图（EEG）。对CBT的成功临床反应定义为Montgomery-Åsberg抑郁评定量表（MADRS）评分从基线到治疗后完成降低50%或以上。在基线、第2周以及从基线到第2周的早期变化时分析EEG相对功率谱测量。在基线时，应答者观察到较低的相对δ (0.5-4 Hz)功率。这一差异预示着CBT的成功临床反应。此外，与无反应者相比，反应者表现出相对δ功率的早期增加和相对α (8-12 Hz)功率的降低。这些变化也被发现是对治疗反应的良好预测指标。这些发现表明静息状态脑电图在预测CBT结果方面的潜在效用。它们还进一步加强了基于脑电图的临床决策工具的前景，以支持每位患者的治疗决策。
Cognitive behavioral therapy (CBT) is often recommended as a first-line treatment in depression. However, access to CBT remains limited, and up to 50% of patients do not benefit from this therapy. Identifying biomarkers that can predict which patients will respond to CBT may assist in designing optimal treatment allocation strategies. In a Canadian Biomarker Integration Network for Depression (CAN-BIND) study, forty-one adults with depression were recruited to undergo a 16-week course of CBT with thirty having resting-state electroencephalography (EEG) recorded at baseline and week 2 of therapy. Successful clinical response to CBT was defined as a 50% or greater reduction in Montgomery-Åsberg Depression Rating Scale (MADRS) score from baseline to post-treatment completion. EEG relative power spectral measures were analyzed at baseline, week 2, and as early changes from baseline to week 2. At baseline, lower relative delta (0.5–4 Hz) power was observed in responders. This difference was predictive of successful clinical response to CBT. Furthermore, responders exhibited an early increase in relative delta power and a decrease in relative alpha (8–12 Hz) power compared to non-responders. These changes were also found to be good predictors of response to the therapy. These findings showed the potential utility of resting-state EEG in predicting CBT outcomes. They also further reinforce the promise of an EEG-based clinical decision-making tool to support treatment decisions for each patient.
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