The effectiveness of prefrontal theta cordance and early reduction of depressive symptoms in the prediction of antidepressant treatment outcome in patients with resistant depression: analysis of naturalistic data
The effectiveness of prefrontal theta cordance and early reduction of depressive symptoms in the prediction of antidepressant treatment outcome in patients with resistant depression: analysis of naturalistic data
复制标题
DOI：
10.1007/s00406-014-0506-8
复制
发表时间：
2015-02-01
影响因子：
4.7
通讯作者：
Hoeschl, Cyril
中科院分区：
文献类型：
--
作者：
Bares, Martin;Novak, Tomas;Hoeschl, Cyril
目前的研究表明，抑郁症状的早期改善和前额叶theta cordance值的降低可以预测抗抑郁药的后续反应。我们研究的目的是（1）比较早期临床改善的预测能力，早期临床改善定义为蒙哥马利和sberg抑郁评定量表（MADRS）总分在第1周和第2周降低千分之20%，难治性抑郁症患者第1周前额叶theta波的降低;（2）以评估单个预测因子的组合是否比单独的任一预测因子产生更稳健的预测能力。根据主治精神科医生的判断，对87名受试者进行了各种抗抑郁药物治疗（每千日元4周的一部分）。计算曲线下面积（AUC），以比较定义的单一预测因子（第1周和第2周MADRS总分降低20%的千分之一，以及第1周一致性降低）和组合预测模型的预测效果。所有三种预测因子的AUC均无统计学差异（成对比较）。组合所有预测因子的模型产生的AUC值0.91显著高于每个单独预测因子的AUC。结果表明，组合预测模型可能是一个有用的和临床意义的工具，用于预测抗抑郁药治疗难治性抑郁症患者的反应。
Current studies suggest that an early improvement of depressive symptoms and the reduction of prefrontal theta cordance value predict the subsequent response to antidepressants. The aim of our study was (1) to compare the predictive abilities of early clinical improvement defined as a parts per thousand yen20 % reduction in Montgomery and sberg Depression Rating Scale (MADRS) total score at week 1 and 2, and the decrease of prefrontal theta cordance at week 1 in resistant depressive patients and (2) to assess whether the combination of individual predictors yields more robust predictive power than either predictor alone. Eighty-seven subjects were treated (a parts per thousand yen4 weeks) with various antidepressants chosen according to the judgment of attending psychiatrists. Areas under curve (AUC) were calculated to compare predictive effect of defined single predictors (a parts per thousand yen20 % reduction in MADRS total score at week 1 and 2, and the decrease of cordance at week 1) and combined prediction models. AUCs of all three predictors were not statistically different (pair-wise comparison). The model combining all predictors yielded an AUC value 0.91 that was significantly higher than AUCs of each individual predictor. The results indicate that the combined predictor model may be a useful and clinically meaningful tool for the prediction of antidepressant response in patients with resistant depression.