基于似然比检验的R Package \pkg{pvLRT}药物安全性评价

IF 2.3 4区 计算机科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
R Journal Pub Date : 2023-08-26 DOI:10.32614/rj-2023-027
Saptarshi Chakraborty, Marianthi Markatou, Robert Ball
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引用次数: 0

摘要

医疗产品安全仍然是二十一世纪的一个关键问题。世界各地建立的几个自发不良事件报告数据库不断收集和归档各种医疗产品的不良事件数据。从这些大规模数据库中确定产品/不良事件对的非比例报告(SDR)信号需要使用有原则的统计技术。基于似然比检验(LRT)的方法在这方面特别值得注意,因为它们允许客观的SDR检测,而不需要特别的阈值。然而,由于分析的复杂性,它们的实现不是简单的,这就需要使用计算量大的方法。这里我们介绍R包pvLRT,它实现了一套LRT方法,以及各种后处理和图形摘要功能,以方便简化方法的使用。通过分析从公开的FDA FAERS和VAERS数据库中获得的三个真实产品安全数据集,提供了详细的示例来说明该软件包。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Likelihood Ratio Test-Based Drug Safety Assessment using R Package \pkg{pvLRT}
Medical product safety continues to be a key concern of the twenty-first century. Several spontaneous adverse events reporting databases established across the world continuously collect and archive adverse events data on various medical products. Determining signals of disproportional reporting (SDR) of product/adverse event pairs from these large-scale databases require the use of principled statistical techniques. Likelihood ratio test (LRT)-based approaches are particularly noteworthy in this context as they permit objective SDR detection without requiring ad hoc thresholds. However, their implementation is non-trivial due to analytical complexities, which necessitate the use of computation-heavy methods. Here we introduce R package pvLRT which implements a suite of LRT approaches, along with various post-processing and graphical summary functions, to facilitate simplified use of the methodologies. Detailed examples are provided to illustrate the package through analyses of three real product safety datasets obtained from publicly available FDA FAERS and VAERS databases.
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来源期刊
R Journal
R Journal COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-STATISTICS & PROBABILITY
CiteScore
2.70
自引率
0.00%
发文量
40
审稿时长
>12 weeks
期刊介绍: The R Journal is the open access, refereed journal of the R project for statistical computing. It features short to medium length articles covering topics that should be of interest to users or developers of R. The R Journal intends to reach a wide audience and have a thorough review process. Papers are expected to be reasonably short, clearly written, not too technical, and of course focused on R. Authors of refereed articles should take care to: - put their contribution in context, in particular discuss related R functions or packages; - explain the motivation for their contribution; - provide code examples that are reproducible.
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