心理治疗与药物治疗或其组合在慢性抑郁症中的有效性:使用汇总和个人患者数据进行系统审查和网络元分析的研究方案
Elisabeth Schramm1, Moritz Elsaesser2, Julia Müller2
1Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany elisabeth.schramm@uniklinik-freiburg.de.
BMJ open
|February 19, 2025
概括
这项研究是第一个使用个人和总体患者数据进行网络元分析,以比较慢性抑郁症的治疗方法. 它旨在确定最有效的疗法和治疗成功的预测因素.
科学领域:
- 精神病学和心理健康 精神病学和心理健康
- 临床心理学 临床心理学
- 基于证据的医学基于证据的医学.
背景情况:
- 慢性抑郁症是一种普遍而使人衰弱的疾病.
- 关于慢性抑郁症治疗方法的现有研究包括心理,药物和联合方法.
- 需要全面综合证据来指导临床实践.
研究的目的:
- 通过个人患者数据 (IPD) 和汇总数据 (AD) 来进行慢性抑郁症治疗的首次总体系统审查和网络元分析 (NMA).
- 为了比较各种心理,药物和综合治疗方案的有效性和可接受性,用于所有慢性抑郁症亚型.
- 调查预测或缓解治疗结果的个体人口和临床特征.
主要方法:
- 在多个数据库 (Cochrane Library,MEDLINE,PsycINFO,Web of Science,metapsy) 进行系统的文献搜索,没有语言限制.
- 将包括随机对照试验 (RCT),调查心理治疗与药物治疗或慢性抑郁症的组合,但不包括基于互联网的治疗.
- 一个NMA将使用贝叶斯框架进行,将IPD纳入可用的IPD和AD,用于不提供IPD的研究. 网络元回归将用于估计个性化治疗效果.
主要成果:
- 主要结局是抑郁症的严重程度,在治疗后6个月 (范围为3-12个月) 测量在持续观察者评级尺度上.
- 偏差风险将使用Cochrane RoB 2工具进行评估.
- 分析将利用所有可用的证据,将IPD和AD纳入分析,以加强证据基础.
结论:
- 这项研究将提供对慢性抑郁症不同治疗策略的可靠比较.
- 通过确定治疗结果的预测因素,研究结果将为个性化治疗方法提供信息.
- 结果将通过同行评审的出版物和科学会议传播.
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