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Likelihood-Ratio-Test Methods for Drug Safety Signal Detection from Multiple Clinical Datasets

机译:从多个临床数据集中检测药物安全信号的似然比测试方法

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摘要

Pre- and postmarket drug safety evaluations usually include an integrated summary of results obtained using data from multiple studies related to a drug of interest. This paper proposes three approaches based on the likelihood ratio test (LRT), called the LRT methods, for drug safety signal detection from large observational databases with multiple studies, with focus on identifying signals of adverse events (AEs) from many AEs associated with a particular drug or inversely for signals of drugs associated with a particular AE. The methods discussed include simple pooled LRT method and its variations such as the weighted LRT that incorporates the total drug exposure information by study. The power and type-I error of the LRT methods are evaluated in a simulation study with varying heterogeneity across studies. For illustration purpose, these methods are applied to Proton Pump Inhibitors (PPIs) data with 6 studies for the effect of concomitant use of PPIs in treating patients with osteoporosis and to Lipiodol (a contrast agent) data with 13 studies for evaluating that drug's safety profiles.
机译:上市前和上市后的药物安全性评估通常包括对结果的综合总结,这些结果是使用与目标药物相关的多项研究得出的数据得出的。本文提出了三种基于似然比检验(LRT)的方法,称为LRT方法,用于从大型观察数据库中进行多次研究的药物安全信号检测,重点是从与AE相关的许多AE中识别不良事件(AE)信号。特定药物或相反地用于与特定AE相关的药物信号。所讨论的方法包括简单的合并LRT方法及其变体,例如加权LRT,它结合了通过研究得出的全部药物暴露信息。在模拟研究中评估了LRT方法的功效和I型误差,这些研究的异质性各不相同。为了说明目的,将这些方法应用于质子泵抑制剂(PPI)数据,其中有6项研究同时使用PPI在治疗骨质疏松症中的作用;而脂质体数据(造影剂),有13项研究,用于评估该药物的安全性。

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