信号检测在药物警戒中的应用:主观贝叶斯推理

Ashok Ranjan, A. Tripathi, A. Saurabh, Kalaiselvan, R. Gupta, Gupta Sk, Agrawal Ss
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引用次数: 3

摘要

本研究提出了一种新的统计方法来发现药物警戒系统中药物不良反应(ADR)对之间的关联。提出了一种与比例报告比(PRR)参数相对应的主观贝叶斯测度,用于定量信号检测。以四个Drug-ADR对为例,采用经典推理和贝叶斯推理方法进行分析。我们根据专家意见作出了先验信息。分析结果表明,贝叶斯推理比经典推理更可靠。本研究表明,在药物警戒系统中自发报告的情况下,主观贝叶斯推理较适用于小样本量的情况。
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Signal Detection in Pharmacovigilance: An Application of Subjective Bayesian Inference
The present study proposed a new statistical measure to find out the association between Drug-Adverse Drug Reaction (ADR) pair in the Pharmacovigilance system. The study proposed a subjective Bayesian measure corresponding to Proportional Reporting Ratio (PRR) parameter for quantitative signal detection. Classical and Bayesian inference procedure were used in analysis with four Drug-ADR pair as an example. We made prior information by expert opinion. The result of this analysis shows that Bayesian inference is more reliable as compared to classical inference. This study suggests that in case of spontaneous reporting in Pharmacovigilance system subjective Bayesian inference better to applying in case of small sample size.
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