Evidence map›Paper›PMID 40567936›Full record

ArticleSAGE open medicine2025

Analysis of adverse events with ruxolitinib using real-world datasets and drug-interaction networks.

Hideyuki Tanaka, Mika Maezawa, Mizuki Tanaka, Ryogo Umetsu, Sakiko Hirofuji, Koumi Miyasaka, Satoshi Nakao, Yuka Nokura, Moe Yamashita, Nanaka Ichihara and 6 more

Abstract read
In one paragraph

Article in SAGE open medicine, 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

16 authors.

Hideyuki TanakaLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Japan.
Mika MaezawaLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Japan.ORCID https://orcid.org/0000-0002-9166-1351
Mizuki TanakaLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Japan.
Ryogo UmetsuLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Japan.
Sakiko HirofujiLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Japan.
Koumi MiyasakaLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Japan.
Satoshi NakaoLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Japan.ORCID https://orcid.org/0000-0001-7413-2637
Yuka NokuraLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Japan.
Moe YamashitaLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Japan.
Nanaka IchiharaLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Japan.
Kana SugishitaLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Japan.
Tomofumi YamazakiLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Japan.
Kohei ShiotaLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Japan.
Hirofumi TamakiLaboratory of Community Pharmacy, Gifu Pharmaceutical University, Gifu-shi, Japan.ORCID https://orcid.org/0000-0002-4543-1176
Kazuhiro IguchiLaboratory of Community Pharmacy, Gifu Pharmaceutical University, Gifu-shi, Japan.
Mitsuhiro NakamuraLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Japan.ORCID https://orcid.org/0000-0002-5062-5522

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Ruxolitinib is used to treat myelofibrosis, polycythemia vera, and steroid-refractory graft-versus-host disease following allogeneic stem cell transplantation. This study aimed to determine the association between ruxolitinib and adverse events by evaluating case reports published between January 2014 and March 2024 in the Japanese Adverse Drug Event Report database. Methods: The signals for the ruxolitinib-adverse event association were identified using propensity score-adjusted reporting odds ratio analysis. Data obtained from the drug-gene interaction, drug signature, search tool for chemical interactions, and interaction reference index databases were used to construct a drug-gene interaction network. Functional and pathway enrichment analyses were performed using the Disease Ontology Semantic and Enrichment and ReactomePA R packages. Results: The propensity score-adjusted reporting odds ratio for ruxolitinib-associated adverse events was as follows: anemia, 18.49 (95% confidence interval (CI): 16.15-21.16); myelosuppression, 4.70 (95% CI: 3.54-6.24); pancytopenia, 1.97 (95% CI: 1.23-3.16); cardiac failure, 2.29 (95% CI: 1.60-3.28); hepatic function abnormal, 1.60 (95% CI: 1.15-2.23); herpes zoster, 6.40 (95% CI: 4.35-9.41); pneumonia, 2.96 (95% CI: 2.35-3.73); renal impairment, 1.34 (95% CI: 0.94-1.90); sepsis, 5.14 (95% CI: 3.75-7.05); interstitial lung disease, 0.33 (95% CI: 0.21-0.52); deep vein thrombosis, 0.32 (95% CI: 0.07-1.44); hemorrhage, 1.99 (95% CI: 1.05-3.75). We also assessed 3015 human genes that directly or indirectly interact with ruxolitinib. The molecular complex detection plug-in of Cytoscape was used to detect 24 clusters. Several genes were enriched in the biological processes of "anemia" and "bacterial infections," identified as significant ruxolitinib-related disease terms. Conclusions: This retrospective analysis using the Japanese Adverse Drug Event Report database indicated potential associations between ruxolitinib and adverse events, including anemia and bacterial infections. Future research should explore the underlying pharmacological mechanisms using functional enrichment analysis of ruxolitinib-associated genes related to blood toxicity and bacterial infections.

Indexed as

adverse eventsdrug-interaction networkJapanese Adverse Drug Event Report databaseRuxolitinib

Identifiers

PMID40567936
PMCPMC12188073

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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.