Evidence map›Paper›PMID 41458952›Full record

ArticleFrontiers in pharmacology2025

Real-world safety of tirofiban: a disproportionality analysis using data from FAERS and WHO-VigiAccess.

Jia Li, Fang Wang, Lingquan Zhong, Lei Zhang, Kaiyun Ji, Yifan Zheng

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Jia Li *Department of Pharmacy, Guangxi Hospital Division of The First Affiliated Hospital, Sun Yat-sen University, Nanning, China.
Fang Wang *Department of Pharmacy, Guizhou Hospital of The First Affiliated Hospital of Sun Yat-sen University (The Affiliated Hospital of Guizhou Medical University), Guiyang, China.
Lingquan Zhong *Department of Pharmacy, Guangxi Hospital Division of The First Affiliated Hospital, Sun Yat-sen University, Nanning, China.
Lei ZhangDepartment of Pharmacy, Shanxi Provincial Integrated TCM And WM Hospital, Taiyuan, China.
Kaiyun JiDepartment of Pharmacy, Jincheng General Hospital, Jincheng, China.
Yifan ZhengDepartment of Pharmacy, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to detect tirofiban-related adverse event (AE) signals using the FAERS and WHO-VigiAccess databases to support safer clinical use. Methods: All tirofiban-related AE reports were retrieved from FAERS (2004Q1 to 2024Q4) and WHO-VigiAccess (Retrieval date 2024.12.15). Disproportionality analyses were performed using ROR (Reporting Odds Ratio), PRR (Proportional Reporting Ratio), BCPNN (Bayesian Confidence Propagation Neural Network), and MGPS (Multi-item Gamma Poisson Shrinker) to detect potential drug-AE associations. Time - to - onset was assessed with Weibull distribution and Kaplan-Meier methods. Sensitivity analyses were performed according to reporter type, age group, and sex to assess the robustness of the findings. Results: A total of 2,421 reports from FAERS and 3,485 from WHO-VigiAccess were identified. Bleeding and thrombocytopenia were the most frequent AEs, consistent with drug labeling. Notably, 21 AE signals suggestive of possible associations not listed in the current drug label were observed, such as vascular stent thrombosis and cardiogenic death, which require further studies to verify their causal relationship with tirofiban. The mean onset time was 12 h, and 96.49% occurred within 1 month of exposure. Subgroup analyses showed that male patients exhibited a stronger signal for thrombocytopenia, whereas female patients had a higher risk of ischemic heart disease. Elderly patients (≥65 years) more frequently experienced hemoglobin decreased, while younger patients (<65years) had a higher risk of thrombosis in device. Conclusion: This study identified both known and potentially novel tirofiban-related AEs. The rapid onset, particularly of bleeding and thrombocytopenia, highlights the importance of early monitoring. Management strategies, such as dose adjustment, temporary discontinuation, or supportive treatment including platelet transfusion, may help mitigate severe complications. These findings provide real-world evidence to guide safer tirofiban use, although further studies are required to confirm causality.

Indexed as

adverse events (AEs)disproportionality analysisFAERS databasetirofibanWHO-VigiAccess database

Identifiers

PMID41458952
PMCPMC12738861

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