Evidence map›Paper›PMID 41383471›Full record

ArticleFrontiers in pharmacology2025

Severe cutaneous adverse reactions to anti-osteoporosis drugs: a real-world pharmacovigilance study using the FDA Adverse Event Reporting System database and a review of published cases.

Jun-Wei Li, Xin-Dong Lei, Bing Dai

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. Not yet cited in PubMed.

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

3 authors.

Jun-Wei LiThe First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China.
Xin-Dong LeiSichuan Academy of Chinese Medicine Sciences, Chengdu, Sichuan, China.
Bing DaiThe First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study analyzed severe cutaneous adverse reactions (SCARs) linked to anti-osteoporosis drugs using FDA Adverse Event Reporting System (FAERS) data and characterized implicated drugs and clinical features through a literature review. Methods: A retrospective disproportionality analysis of SCAR reports from FAERS (2004-2024) utilized signal detection metrics, including reporting odds ratio (ROR), proportional reporting ratio (PRR), and Bayesian confidence propagation neural network (BCPNN). A structured literature search across PubMed, Web of Science, and Scopus gathered case reports of SCARs induced by anti-osteoporosis drugs. Results: Of 77,789 SCAR reports, 399 (0.51%) involved anti-osteoporosis drugs, mainly affecting female patients (76.25%) with a median age of 69 years. Denosumab (24%), alendronate (23.25%), and zoledronic acid (17.13%) were most frequently reported. Significant signals included risedronic acid with erythema multiforme [ROR = 9.06; PRR = 9.03; information component (IC) = 3.17], zoledronic acid with cutaneous vasculitis (ROR = 3.15; PRR = 3.15; IC = 1.65), and alendronic acid with Stevens-Johnson syndrome (SJS) (ROR = 4.03; PRR = 4.02; IC = 2.00). The literature review (33 cases) confirmed a median symptom onset of 22 days, with treatments often involving corticosteroids and supportive care. Conclusion: Anti-osteoporosis drugs, notably bisphosphonates and strontium ranelate, are rarely linked to SCARs but may cause serious consequences. Increased clinical awareness, pre-treatment risk evaluation, and vigilant monitoring are essential for at-risk patients.

Indexed as

adverse event reporting systemanti-osteoporosis drugscase reviewpharmacovigilancesevere cutaneous adverse reactions

Identifiers

PMID41383471
PMCPMC12689889

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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.