Evidence map›Paper›PMID 39954042›Full record

ArticleArchives of dermatological research2025

A pharmacovigilance analysis of abrocitinib-related skin adverse events based on the FDA Adverse Event Reporting System (FAERS).

Min Huang, Peng Li

Abstract read
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In one paragraph

Article in Archives of dermatological research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Min HuangDepartment of Dermatology, Chuiyangliu Hospital Affiliated with Tsinghua University, No.2, Chuiyangliu South Street, Chaoyang District, Beijing, China. 17343008375@163.com.ORCID http://orcid.org/0009-0005-2788-1287
Peng LiDepartment of Pharmacy, Medical Supplies Center, Chinese People's Liberation Army General Hospital, Beijing, China.ORCID http://orcid.org/0009-0009-1768-7172

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In January 2022, the U.S. Food and Drug Administration (FDA) approved the marketing of abrocitinib, an oral small molecule selectively inhibiting Janus kinase, for the treatment of patients with recurrent moderate to severe atopic dermatitis. Despite the lack of long-term post-marketing safety studies, this drug was cited with a black box warning by the FDA for potentially increasing the risk of several severe adverse events (AEs). This retrospective pharmacovigilance disproportionality analysis study used data from the FDA Adverse Event Reporting System (FAERS) from the first quarter of 2022 to the first quarter of 2024, aiming to analyze the potential association between abrocitinib and skin AEs. Three disproportionality measurement were performed for data mining, including the reporting odd ratio method, the proportional reporting ratio method and the Medicines and Healthcare products Regulatory Agency method. Out of 3,269,835 AE reports extracted from the database, 699 cases of skin-related AEs were identified, where abrocitinib was implicated as the primary suspect drug. The patient demographic information, outcomes and report sources were analyzed. 34 kinds of positive risk signals were detected, many of which were unexpected safety signals. This study provided a scientific reference to understand the safety of abrocitinib in practical applications.

Indexed as

Adverse Drug Reaction Reporting SystemsDermatitis, AtopicPyrimidinesAdolescentAdultAgedChildChild, PreschoolFemaleHumansMaleMiddle AgedPharmacovigilanceRetrospective StudiesSkinSulfonamidesabrocitinibPyrimidinesSulfonamidesAbrocitinibData miningFAERSPharmacovigilanceSkin AEs

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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 OpenQuestion graph.