Evidence map›Paper›PMID 41593377›Full record

ArticleNaunyn-Schmiedeberg's archives of pharmacology2026

Drug-associated deep vein thrombosis: a disproportionality analysis of the FDA adverse event reporting system (FAERS) database.

Ying Liu, Jintuo Zhou, Lihuan Song, Peiguang Niu

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Article in Naunyn-Schmiedeberg's archives of pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ying Liu *Department of Pharmacy, Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, #18 Daoshan Road, Fuzhou, China.
Jintuo Zhou *Department of Pharmacy, Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, #18 Daoshan Road, Fuzhou, China.
Lihuan Song, Fuzhou, China.
Peiguang NiuDepartment of Pharmacy, Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, #18 Daoshan Road, Fuzhou, China. npg4031@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug-associated deep vein thrombosis (DVT) poses a growing clinical concern, yet the thrombotic risk profiles of many medications are not fully established. This study aimed to systematically detect and characterize drug safety signals for DVT using real-world pharmacovigilance data. A disproportionality analysis was conducted using reports from the FDA adverse event reporting system (FAERS) spanning the first quarter of 2004 to the second quarter of 2025. After deduplication and filtering, 43,226 DVT cases linked to a primary suspect drug were analyzed. Four disproportionality metrics-the reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS)-were applied to identify safety signals. Drugs were categorized using the anatomical therapeutic chemical (ATC) classification system. Time-to-onset (TTO) profiles were assessed via the Weibull distribution modeling and the Kaplan-Meier analysis. Among the included reports, 60.23% involved female patients, and 97.48% were classified as serious outcomes. Eighty-eight drugs met the predefined signal threshold. The ten highest-ranking agents by case count were drospirenone/ethinyl estradiol (ROR 69.09), ethinyl estradiol/etonogestrel (ROR 43.41), lenalidomide (ROR 4.89), testosterone (ROR 30.13), rofecoxib (ROR 5.41), ethinyl estradiol/norelgestromin (ROR 28.53), bevacizumab (ROR 3.53), thalidomide (ROR 9.26), pomalidomide (ROR 3.18), and celecoxib (ROR 3.90). These agents predominantly belonged to antineoplastic/immunomodulatory or genitourinary/hormonal therapeutic classes. The median TTO was 120 days (IQR 29-441), with 25.87% of events occurring within the first month of treatment. Early failure patterns were most frequent (52.6% of drugs), especially among hormonal contraceptives, immunomodulators, and chemotherapeutic agents. This large-scale pharmacovigilance analysis identifies robust DVT signals across multiple drug classes, notably hormonal therapies, immunomodulators, and targeted anticancer agents. The results highlight the importance of proactive thrombotic risk assessment and monitoring in clinical practice when using these medications.

Indexed as

Adverse Drug Reaction Reporting SystemsDrug-Related Side Effects and Adverse ReactionsVenous ThrombosisAdultAgedBayes TheoremDatabases, FactualFemaleHumansMaleMiddle AgedPharmacovigilanceUnited StatesUnited States Food and Drug AdministrationDeep vein thrombosisDisproportionality analysisFAERS databasePharmacovigilance

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.