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评估用于描述安慰剂对重度抑郁症病程影响的结构模型。

Evaluation of structural models to describe the effect of placebo upon the time course of major depressive disorder.

作者信息

Shang Elizabeth Y, Gibbs Megan A, Landen Jaren W, Krams Michael, Russell Tanya, Denman Nicholas G, Mould Diane R

机构信息

Pfizer Global Research and Development, Pfizer Inc., New London, CT 06320, USA.

出版信息

J Pharmacokinet Pharmacodyn. 2009 Feb;36(1):63-80. doi: 10.1007/s10928-009-9110-3. Epub 2009 Feb 10.

DOI:10.1007/s10928-009-9110-3
PMID:19205853
Abstract

Major depressive disorder (MDD) is the leading cause of disability in many countries. Designing and evaluating clinical trials of antidepressants is difficult due to the pronounced and variable placebo response which is poorly defined and may be affected by trial design. Approximately half of recent clinical trials of commonly used antidepressants failed to show statistical superiority for the drug over placebo, which is partly attributable to a marked placebo response. These failures suggest the need for new tools to evaluate placebo response and drug effect in depression, as well as to help design more informative clinical trials. Disease progression modeling is a tool that has been employed for such evaluations and several models have been proposed to describe MDD. Placebo data from three clinical depression trials were used to evaluate three published models: the inverse Bateman (IBM), indirect response (IDR) and transit (TM) models. Each model was used to describe Hamilton Rating Scale for major depression (HAMD) data and results were evaluated. The IBM model had several deficiencies, making it unsuitable. The IDR and TM models performed well on most evaluations and appear suitable. Comparing the IDR and TM models showed less clear distinctions, although overall the TM was found to be somewhat better than the IDR model. Model based evaluation can provide a useful tool for evaluating the time course of MDD and detecting drug effect. However, the models used should be robust, with well estimated parameters.

摘要

重度抑郁症(MDD)是许多国家致残的主要原因。由于安慰剂反应明显且多变,难以明确界定且可能受试验设计影响,因此设计和评估抗抑郁药物的临床试验颇具难度。近期常用抗抑郁药物的临床试验中,约有一半未能显示出药物相对于安慰剂的统计学优势,这部分归因于显著的安慰剂反应。这些失败表明需要新的工具来评估抑郁症中的安慰剂反应和药物效果,以及帮助设计更具信息量的临床试验。疾病进展建模是一种用于此类评估的工具,并且已经提出了几种模型来描述MDD。来自三项临床抑郁症试验的安慰剂数据用于评估三种已发表的模型:反向贝特曼(IBM)模型、间接反应(IDR)模型和过渡(TM)模型。每个模型都用于描述重度抑郁汉密尔顿评定量表(HAMD)数据并对结果进行评估。IBM模型存在一些缺陷,不太适用。IDR模型和TM模型在大多数评估中表现良好,似乎较为适用。比较IDR模型和TM模型发现差异不太明显,不过总体而言,TM模型比IDR模型略胜一筹。基于模型的评估可为评估MDD的病程和检测药物效果提供有用的工具。然而,所使用的模型应稳健,参数估计良好。

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