RCSI University of Medicine and Health Sciences, School of Population Health, Dublin, Ireland.
Princess Margaret Cancer Centre, University Health Network, Ontario, Canada.
J Affect Disord. 2025 Jan 1;368:584-590. doi: 10.1016/j.jad.2024.09.087. Epub 2024 Sep 16.
The 10-item Montgomery-Åsberg Depression Rating Scale (MADRS) is a commonly used measure of depression in antidepressant clinical trials. Numerous studies have adopted classical test theory perspectives to assess the psychometric properties of this scale, finding generally positive results. However, its network configural structure and stability is unexplored across different time-points and treatment groups.
To assess the network structure and stability of the MADRS in clinical settings pre- and post-treatment, and to determine a configurally invariant and stable model across time-points and treatment groups (placebo and intervention).
Individual participant data for 6440 participants from 14 clinical trials of major depressive disorder was obtained from the data repository Vivli.org. Exploratory Graphical Analysis (EGA) was used to identify empirical models pre-treatment (baseline) and post-treatment (8-week outcome). Bootstrapping techniques were applied to obtain optimised configurally invariant models.
Empirical models presented with performance issues at baseline and for the placebo group at outcome. An abbreviated 8-item single-community model was found to be stable and configurally invariant across time-points and treatment groups. Symptoms such as low mood and lassitude showed most centrality across all models.
Metric invariance could not be explored due to research environment limitations.
An 8-item one-community variant of the MADRS may provide optimal performance when conducting network analyses of antidepressant clinical trial outcomes. Findings suggest that interventions targeting low mood and lassitude might be most efficacious in treating depression among clinical trial participants. Further considerations of the potential impact on trial design and analysis should be explored.
10 项蒙哥马利-Åsberg 抑郁评定量表（MADRS）是抗抑郁药临床试验中常用的抑郁测量工具。许多研究采用经典测试理论的观点来评估该量表的心理测量特性，得出了普遍积极的结果。然而，其网络结构和稳定性在不同的时间点和治疗组中尚未得到探索。
评估 MADRS 在临床环境中治疗前后的网络结构和稳定性，并确定在不同时间点和治疗组（安慰剂和干预组）之间具有配置不变性和稳定性的模型。
从 Vivli.org 数据存储库中获取了 14 项重度抑郁症临床试验的 6440 名参与者的个体参与者数据。探索性图形分析（EGA）用于在治疗前（基线）和治疗后（8 周结局）识别经验模型。应用引导技术获得优化的配置不变模型。
经验模型在基线时和安慰剂组在结局时表现出性能问题。发现一个简化的 8 项单社区模型在所有时间点和治疗组中具有稳定性和配置不变性。在所有模型中，情绪低落和疲倦等症状显示出最高的中心性。
由于研究环境的限制，无法探索度量不变性。
在对抗抑郁药临床试验结果进行网络分析时，MADRS 的 8 项单社区变体可能会提供最佳性能。研究结果表明，针对情绪低落和疲倦的干预措施可能对临床试验参与者的治疗最有效。应进一步探讨对试验设计和分析的潜在影响。
