Evidence map›Paper›PMID 41103707›Full record

ArticleFrontiers in medicine2025

Mining and analysis of adverse event signals of isotretinoin based on the real-world data of FAERS database.

Liu Yang, Hanzhang Xie, Ying Jia, Bingnan Cui, Zhanshuo Xiao

Abstract read
In one paragraph

Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

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

5 authors.

Liu Yang *Department of Dermatology, Guanganmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Hanzhang Xie *College of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Ying Jia *Department of Dermatology, Guanganmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Bingnan CuiDepartment of Dermatology, Guanganmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Zhanshuo XiaoDepartment of Dermatology, Guanganmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Isotretinoin (ISO) is an oral prescription retinoid that is well-known for its effectiveness in treating acne. This study aims to provide valuable insights into the safety of its clinical use by analyzing adverse events (AEs) associated with ISO reported in the FDA Adverse Event Reporting System (FAERS) database. Methods: FAERS data from Q1 2004 to Q2 2024 were analyzed. Duplicate reports were excluded, and disproportionality analysis using four algorithms (ROR, PRR, BCPNN, EBGM) was performed. AEs were classified using MedDRA terms, with Important Medical Events (IMEs) flagged based on the MedDRA IME list. Results: The FAERS database identified 46,526 ISO-related AE reports covering 27 System Organ Classes (SOCs). Of these, 445 AEs showed significant signals across all four algorithms, including 38 previously unlabeled AEs within the top 50 positive Preferred Term (PT) signals. Key IMEs, such as Dandy-Walker syndrome ( Conclusion: This study identified previously unlabeled AEs and IMEs associated with ISO, including life-threatening events such as Dandy-Walker syndrome, suicidal ideation, and childhood depression, emphasizing the need for updated drug labels and enhanced safety measures. Future research should focus on mechanisms underlying teratogenicity and psychiatric risks to refine ISO's safety profile.

Indexed as

adverse eventsDandy-Walker syndromeFAERS databaseisotretinoinpharmacovigilancepharmacovigilance methodologysignal detectionsuicidal ideation

Identifiers

PMID41103707
PMCPMC12521089

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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 OpenQuestion graph.