Evidence map›Paper›PMID 41728616›Full record

ArticleFrontiers in medicine2026

Comparative safety of denosumab and romosozumab in osteoporosis: an analysis based on the FDA adverse event reporting system database.

Jian Sun, Ciren Lunzhu, Yao Wu, Jun Li

Abstract read
In one paragraph

Article in Frontiers in medicine, 2026. 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

4 authors.

Jian SunDepartment of Orthopedics, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China.
Ciren LunzhuDepartment of Orthopedics, Shannan City People's Hospital, Shannan, Xizang Autonomous Region, China.
Yao WuDepartment of Plastic and Cosmetic Burns, Anhui No.2 Provincial People's Hospital, Hefei,Anhui Province, China.
Jun LiDepartment of Orthopedics, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Denosumab and romosozumab are two biological agents with potential immunomodulatory effects commonly used to treat osteoporosis. This study aimed to compare the safety of these two drugs using the FDA Adverse Event Reporting System (FAERS) with a focus on immune-related adverse reactions. Methods: Data for the second quarter of 2019 (approval date for romosozumab) and the second quarter of 2025 were extracted from the FAERS database. After standardized data cleaning, disproportionality analysis and the Bayesian approach were applied to detect safety signals for the two biological agents simultaneously. Results: After data extraction and cleaning, 38,784 and 10,007 reports were obtained for denosumab and romosozumab, respectively. Denosumab was associated with long-term cumulative risk and showed strong signals in musculoskeletal and metabolic disorders. In contrast, romosozumab demonstrated an acute and severe cardiovascular risk with strong signals for coronary artery disease and heart failure. Regarding immune-related events, denosumab was associated with osteoimmune complications such as noninfectious gingivitis, whereas the immune-related risk of romosozumab was limited to minor injection-site reactions. Conclusion: Research based on FAERS revealed distinct differences in the safety profiles of denosumab and romosozumab. Clinical decision makers should deepen their understanding of these features to advance personalized therapy and improve medication safety.

Indexed as

denosumabFAERSimmunologyosteoporosispharmacovigilanceromosozumab

Identifiers

PMID41728616
PMCPMC12916682

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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.