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Model-based approach and signal detection theory to evaluate the performance of recruitment centers in clinical trials with antidepressant drugs.

机译:基于模型的方法和信号检测理论来评估招聘中心在抗抑郁药临床试验中的表现。

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摘要

The objective of this study was to characterize the performance of each recruitment center in multicenter clinical trials and to provide criteria to discriminate between informative and noninformative centers using the signal detection approach. Data were derived from the GlaxoSmithKline Clinical Trial database on paroxetine and bupropion, totaling 4,016 subjects with major depressive disorders (MDDs) across nine trials. The probability of observing clinically relevant difference of active treatment from placebo was estimated in each center as a function of the placebo Hamilton Depression Rating Scale (HAMD-17) scores at baseline and at week 8. The center's performance was defined using the posterior probability (PP) of detecting a signal of a treatment effect. Only 60% of the centers were classified as informative. In these centers, the signal of treatment effect increased by approximately 80%. The signal detection approach appears to be a useful methodology to rank the performance of recruitment centers and to classify each center as informative or not in respect of detection of clinically relevant signals of efficacy. A further analysis indicated that a minimal sample of four subjects is required in order to predict the typical placebo response in each center.
机译:这项研究的目的是表征每个招聘中心在多中心临床试验中的表现,并提供使用信号检测方法区分信息中心和非信息中心的标准。数据来自葛兰素史克临床试验数据库中有关帕罗西汀和安非他酮的数据,在9项试验中,共有4,016名患有严重抑郁症(MDD)的受试者。根据基线和第8周时的安慰剂汉密尔顿抑郁评估量表(HAMD-17)得分,估计了每个中心观察到的与安慰剂有临床相关差异的概率,这是安慰剂汉密尔顿抑郁量表(HAMD-17)得分的函数。 PP)检测治疗效果的信号。只有60%的中心被归类为信息丰富的中心。在这些中心,治疗效果的信号增加了大约80%。信号检测方法似乎是一种有用的方法,可以对招聘中心的绩效进行排名,并且可以将每个中心归类为对临床相关功效信号的检测是否有用。进一步的分析表明,为了预测每个中心的典型安慰剂反应,需要最少四个样本的样本。

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