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Verification of the “Upward Variation in the Reporting Odds Ratio Scores” to Detect the Signals of Drug–Drug Interactions
Pharmaceutics ( IF 5.4 ) Pub Date : 2021-09-22 , DOI: 10.3390/pharmaceutics13101531
Yoshihiro Noguchi 1 , Shunsuke Yoshizawa 1 , Keisuke Aoyama 1 , Satoaki Kubo 1 , Tomoya Tachi 1 , Hitomi Teramachi 1
Affiliation  

The reporting odds ratio (ROR) is easy to calculate, and there have been several examples of its use because of its potential to speed up the detection of drug–drug interaction signals by using the “upward variation of ROR score.” However, since the validity of the detection method is unknown, this study followed previous studies to investigate the detection trend. The statistics models (the Ω shrinkage measure and the “upward variation of ROR score”) were compared using the verification dataset created from the Japanese Adverse Drug Event Report database (JADER). The drugs registered as “suspect drugs” in the verification dataset were considered as the drugs to be investigated, and the target adverse event in this study was Stevens–Johnson syndrome (SJS), as in previous studies. Of 3924 pairs that reported SJS, the number of positive signals detected by the Ω shrinkage measure and the “upward variation of ROR score” (Model 1, the Susuta Model, and Model 2) was 712, 2,112, 1758, and 637, respectively. Furthermore, 1239 positive signals were detected when the Haldane–Anscombe 1/2 correction was applied to Model 2, the statistical model that showed the most conservative detection trend. This result indicated the instability of the positive signal detected in Model 2. The ROR scores based on the frequency-based statistics are easily inflated; thus, the use of the “upward variation of ROR scores” to search for drug–drug interaction signals increases the likelihood of false-positive signal detection. Consequently, the active use of the “upward variation of ROR scores” is not recommended, despite the existence of the Ω shrinkage measure, which shows a conservative detection trend.

中文翻译:

验证“报告优势比分数的向上变化”以检测药物-药物相互作用的信号

报告优势比 (ROR) 很容易计算,并且有几个使用它的例子,因为它有可能通过使用“ROR 分数的向上变化”来加速药物相互作用信号的检测。然而,由于检测方法的有效性尚不清楚,因此本研究遵循先前的研究来调查检测趋势。使用从日本不良药物事件报告数据库 (JADER) 创建的验证数据集比较了统计模型(Ω 收缩度量和“ROR 分数的向上变化”)。在验证数据集中注册为“可疑药物”的药物被视为待研究药物,本研究中的目标不良事件是史蒂文斯-约翰逊综合征(SJS),与以往的研究一样。在报告 SJS 的 3924 对中,Ω 收缩测量和“ROR 分数的向上变化”(模型 1、Susuta 模型和模型 2)检测到的阳性信号数量分别为 712、2,112、1758 和 637。此外,当 Haldane-Anscombe 1/2 校正应用于模型 2 时,检测到 1239 个阳性信号,模型 2 是显示最保守检测趋势的统计模型。这一结果表明模型 2 中检测到的正信号不稳定。基于频率统计的 ROR 分数很容易被夸大;因此,使用“ROR 分数的向上变化”来搜索药物-药物相互作用信号增加了假阳性信号检测的可能性。因此,不建议积极使用“ROR 分数的向上变化”,尽管存在 Ω 收缩度量,
更新日期:2021-09-22
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