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基于日本药物不良反应报告数据库分析草药所致药物性间质性肺病。

Analysis of drug-induced interstitial lung disease caused by herbal medicine using the Japanese Adverse Drug Event Report database.

机构信息

Laboratory of Drug Informatics, Gifu Pharmaceutical University, 1-25-4, Daigaku-Nishi, Gifu, 501-1196, Japan.

Kaneichi Pharmaceutical, Company, Limited, Osaka, Japan.

出版信息

BMC Complement Med Ther. 2024 Mar 14;24(1):121. doi: 10.1186/s12906-024-04428-y.

DOI:10.1186/s12906-024-04428-y
PMID:38486172
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10938654/
Abstract

BACKGROUND

Drug-induced interstitial lung disease (DIILD) is a severe adverse event leading to morbidity and mortality. This study evaluated the adverse event indicators of DIILD and time-to-onset profiles following the daily intake of herbal drugs (Scutellariae radix ["ogon" in Japanese], Bupleuri radix ["saiko" in Japanese], and Pinelliae tuber ["hange" in Japanese]) using the Japanese Adverse Drug Event Report database. DIILD was defined in accordance with the Medical Dictionary for Regulatory Activities.

METHODS

The Japanese Adverse Drug Event Report database contained 830,079 reports published between April 2004 and April 2023. The association between herbal medicines and DILLD was evaluated using the pharmacovigilance index as the reporting odds ratio (ROR), logistic regression models, propensity score-matching techniques, and Weibull shape parameters.

RESULTS

The adjusted RORs using multivariate logistic regression models for Scutellariae radix (daily intake), Pinelliae tuber (daily intake), sex (male), age (≥ 60 years), Scutellariae radix (daily intake)age (≥ 60 years), and Scutellariae radix (daily intake) Pinelliae tuber (daily intake) were 1.47 (1.36 - 1.59), 1.05 (1.01 - 1.10), 1.45 (1.34 - 1.57), 1.92 (1.74 - 2.11), 3.35 (3.12 - 3.60), and 1.49 (1.46 - 1.53), respectively. DIILD onset profiles were evaluated using the Weibull shape parameter. A logistic plot of daily intake and onset of DIILD was drawn. ROR signals were detected in 32 of 54 herbal medicines, including Scutellariae radix, Bupleuri radix, and Pinelliae tuber. The median duration (days) (interquartile range) to DIILD onset was 36.0 (27.0-63.0) for Saikokaryukotsuboreito, 35.0 (21.0-55.0) for Saireito, and 31.0 (13.5-67.5) for Shosaikoto. The Weibull shape parameter beta (95% confidence interval) values for Saikokaryukotsuboreito, Saireito, and Shosaikoto were 1.36 (1.08-1.67), 1.36 (1.20-1.52), and 1.31 (0.98-1.68), respectively.

CONCLUSIONS

DIILD demonstrated a dose-dependent to crude drugs. Clinicians should strive for the early detection of DIILD and avoid the inadvertent administration of herbal medicines.

摘要

背景

药物性间质性肺病(DIILD)是一种导致发病率和死亡率的严重不良事件。本研究使用日本不良药物事件报告数据库评估了草药(黄芩根[日文“ogon”]、柴胡根[日文“saiko”]和半夏块茎[日文“hange”])每日摄入后 DIILD 的不良事件指标和发病时间分布。DIILD 是根据监管活动医学词典定义的。

方法

日本不良药物事件报告数据库包含了 2004 年 4 月至 2023 年 4 月期间发表的 830,079 份报告。使用药物警戒指数作为报告比值比(ROR)、逻辑回归模型、倾向评分匹配技术和威布尔形状参数来评估草药与 DILLD 之间的关联。

结果

使用多变量逻辑回归模型对黄芩根(每日摄入)、半夏块茎(每日摄入)、性别(男)、年龄(≥60 岁)、黄芩根(每日摄入)*年龄(≥60 岁)和黄芩根(每日摄入)*半夏块茎(每日摄入)进行调整后的 ROR 分别为 1.47(1.36-1.59)、1.05(1.01-1.10)、1.45(1.34-1.57)、1.92(1.74-2.11)、3.35(3.12-3.60)和 1.49(1.46-1.53)。使用威布尔形状参数评估了 DIILD 发病时间分布。绘制了每日摄入和 DIILD 发病的逻辑图。在 54 种草药中,包括黄芩根、柴胡根和半夏块茎,检测到 32 种草药存在 ROR 信号。Saikokaryukotsuboreito、Saireito 和 Shosaikoto 发病的中位时间(天)(四分位距)分别为 36.0(27.0-63.0)、35.0(21.0-55.0)和 31.0(13.5-67.5)。Saikokaryukotsuboreito、Saireito 和 Shosaikoto 的威布尔形状参数β(95%置信区间)值分别为 1.36(1.08-1.67)、1.36(1.20-1.52)和 1.31(0.98-1.68)。

结论

DIILD 表现出与粗药的剂量依赖性。临床医生应努力早期发现 DIILD,并避免无意中使用草药。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eca9/10938654/e9963956b92a/12906_2024_4428_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eca9/10938654/fc5de7738809/12906_2024_4428_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eca9/10938654/174189145006/12906_2024_4428_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eca9/10938654/e9963956b92a/12906_2024_4428_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eca9/10938654/fc5de7738809/12906_2024_4428_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eca9/10938654/da8569e87946/12906_2024_4428_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eca9/10938654/0daba02fe5d9/12906_2024_4428_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eca9/10938654/fe59aa8c5a08/12906_2024_4428_Fig4_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eca9/10938654/e9963956b92a/12906_2024_4428_Fig6_HTML.jpg

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