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Clustering patients by depression symptoms to predict venlafaxine ER antidepressant efficacy: Individual patient data analysis.
Journal of Psychiatric Research ( IF 4.8 ) Pub Date : 2020-07-09 , DOI: 10.1016/j.jpsychires.2020.06.011
Masaki Kato 1 , Yuko Asami 2 , Dalia B Wajsbrot 3 , Xuemei Wang 4 , Matthieu Boucher 5 , Rita Prieto 6 , Elizabeth Pappadopulos 3
Affiliation  

Objective

To identify clusters of patients with major depressive disorder (MDD) based on the baseline 17-item Hamilton Rating Scale for Depression (HAM-D17) items and to evaluate the efficacy of venlafaxine extended release (VEN) vs placebo, and the potential effect of dose on efficacy, in each cluster.

Methods

Cluster analysis was performed to identify clusters based on standardized HAM-D17 item scores of individual patient data at baseline from 9 double-blind, placebo-controlled studies of VEN for MDD. Change from baseline in HAM-D17 total score was analyzed using a mixed-effects model for repeated measures for each cluster; response and remission rates at week 8 were analyzed using logistic regression. Discontinuation rates were also evaluated in each cluster.

Results

In 2599 patients, 3 patient clusters were identified, characterized as High modified Core (mCore) Symptoms/High Anxiety (cluster 1), High mCore Symptoms/Medium Anxiety (cluster 2), and Medium mCore Symptoms/Medium Anxiety (cluster 3). Significant effects of VEN vs placebo were observed on change from baseline in HAM-D17 total score at week 8 for both clusters 1 and 2 (both P < 0.001), but not for cluster 3. In cluster 3, a significant treatment effect of VEN was observed at week 8 in the lower-dose subgroup but not in the higher-dose subgroup. All-cause discontinuation rates were significantly higher in placebo than VEN in each cluster.

Conclusions

Three unique clusters of patients were identified differing in baseline mCore symptoms and anxiety. Cluster membership may predict efficacy outcomes and contribute to dose effects in patients treated with VEN.

Clinical trials registration

NCT01441440; other studies included in this analysis were conducted before the requirement to register clinical studies took effect.



中文翻译:

通过抑郁症状将患者分组以预测文拉法辛ER抗抑郁药的疗效:个体患者数据分析。

目的

基于基线的17个项汉密尔顿抑郁量表(HAM-D 17)项目,确定重度抑郁症(MDD)患者群,并评估文拉法辛缓释(VEN)与安慰剂的疗效及潜在影响各组中剂量对功效的影响。

方法

进行聚类分析以根据标准HAM-D 17项个体患者数据在基线的基线项目得分进行分组,该评分来自9项VEN对MDD的双盲,安慰剂对照研究。使用混合效应模型分析HAM-D 17总得分中与基线相比的变化,以对每个聚类进行重复测量。使用逻辑回归分析第8周的缓解和缓解率。还评估了每个集群的停产率。

结果

在2599名患者中,确定了3个患者群,其特征为高修饰核心(mCore)症状/高焦虑症(第1组),高mCore症状/中度焦虑症(第2组)和中mCore症状/中度焦虑症(第3组)。对于第1组和第2组,在第8周,观察到VEN与安慰剂对HAM-D 17总评分相对于基线的变化的显着影响(均P  <0.001),但对第3组则没有。在第3组中,低剂量亚组在第8周观察到VEN,但高剂量亚组未观察到VEN。在每个组中,安慰剂的全因停药率显着高于VEN。

结论

确定了三组独特的患者,其基线mCore症状和焦虑有所不同。集群成员可以预测疗效结果,并有助于接受VEN治疗的患者的剂量效应。

临床试验注册

NCT01441440; 在注册临床研究的要求生效之前,进行了此分析中包括的其他研究。

更新日期:2020-07-24
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