Evidence map›Paper›PMID 42379756›Full record

ArticleIn vivo (Athens, Greece)

Temporal Trends in Antineoplastic Agent-associated Interstitial Lung Disease Involving Immune Checkpoint Inhibitors in the JADER Database.

Yuki Ibayashi, Hiroaki Watanabe, Yusuke Shimura, Yukiko Nishiyama, Yoshimichi Sai, Yukio Suga

Abstract read
In one paragraph

Article in In vivo (Athens, Greece). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

6 authors.

Yuki IbayashiDivision of Pharmacy, Graduate School of Medical Sciences, Kanazawa University, Ishikawa, Japan.
Hiroaki WatanabeDepartment of Clinical Pharmacy and Healthcare Sciences, Faculty of Pharmacy, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Ishikawa, Japan.
Yusuke ShimuraDepartment of Hospital Pharmacy, University Hospital, Kanazawa University, Ishikawa, Japan.
Yukiko NishiyamaDepartment of Pharmacy, National Hospital Organization Kanazawa Medical Center, Ishikawa, Japan.
Yoshimichi SaiDepartment of Hospital Pharmacy, University Hospital, Kanazawa University, Ishikawa, Japan.
Yukio SugaDepartment of Clinical Pharmacy and Healthcare Sciences, Faculty of Pharmacy, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Ishikawa, Japan; suga@staff.kanazawa-u.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

aimCancer pharmacotherapy has advanced substantially with the introduction of novel agents such as immune checkpoint inhibitors (ICIs). However, managing drug-induced interstitial lung disease (DIILD) associated with these agents remains a major clinical challenge in maintaining treatment. Detailed investigations into recent changes in DIILD reporting and specific drug categories contributing to these changes remain limited. Therefore, we aimed to identify factors contributing to recent changes in DIILD reports by analyzing temporal trends in antineoplastic agent-associated DIILD using the Japanese Adverse Drug Event Report database. MATERIALS AND

methodsWe analyzed the database reports from 2004 to 2024. The reporting odds ratio (ROR) and Weibull model were used to evaluate safety signals and the time to onset of ICI-associated DIILD, respectively.

resultsThe mean rate of antineoplastic agent-associated DIILD among total adverse event reports was significantly higher in the most recent period (2016-2024) than in the earlier period (2004-2015) (25.9%

conclusionThe recent increase in antineoplastic agent-associated DIILD may primarily be driven by the expanding use of ICIs, particularly ICI in combination with chemotherapy. Because DIILD tends to occur in the early phase of treatment, strict monitoring is warranted during the initial therapy period.

Indexed as

Antineoplastic AgentsImmune Checkpoint InhibitorsLung Diseases, InterstitialAdverse Drug Reaction Reporting SystemsDatabases, FactualDrug-Related Side Effects and Adverse ReactionsHumansJapanAntineoplastic AgentsImmune Checkpoint InhibitorsDrug-induced interstitial lung diseaseimmune checkpoint inhibitorJapanese Adverse Drug Event Report databasepharmacovigilance

Identifiers

PMID42379756
PMCPMC13322017

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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.