Evidence map›Paper›PMID 38293566›Full record

ArticleTherapeutic advances in drug safety2024

Drug-induced interstitial lung disease: a real-world pharmacovigilance study of the FDA Adverse Event Reporting System from 2004 to 2021.

Tingting Jiang, Hui Su, Jing Xu, Chen Li, Ni Zhang, Yanping Li, Yuanlin Wu, Rui Ni, Yue Ming, Ziwei Li and 2 more

Abstract read
In one paragraph

Article in Therapeutic advances in drug safety, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Review
  4. Observational
  5. Article
  6. Article
  7. Article
  8. Drug-induced pulmonary edema: a real-world pharmacovigilance study using the FDA Adverse Event Reporting System (FAERS).Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica · 2025
    Article
  9. Article
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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

12 authors.

Tingting JiangDepartment of Pharmacy, Daping Hospital, Army Medical University, Chongqing, China.
Hui SuDepartment of Pharmacy, Daping Hospital, Army Medical University, Chongqing, China.
Jing XuDepartment of Pharmacy, Daping Hospital, Army Medical University, Chongqing, China.
Chen LiDepartment of Pharmacy, Daping Hospital, Army Medical University, Chongqing, China.
Ni ZhangDepartment of Pharmacy, Daping Hospital, Army Medical University, Chongqing, China.ORCID https://orcid.org/0009-0005-3474-2269
Yanping LiDepartment of Pharmacy, Daping Hospital, Army Medical University, Chongqing, China.
Yuanlin WuDepartment of Pharmacy, Daping Hospital, Army Medical University, Chongqing, China.
Rui NiDepartment of Pharmacy, Daping Hospital, Army Medical University, Chongqing, China.
Yue MingDepartment of Pharmacy, Daping Hospital, Army Medical University, Chongqing, China.
Ziwei LiDepartment of Pharmacy, Daping Hospital, Army Medical University, Chongqing, China.
Li LiDepartment of Pharmacy, Daping Hospital, Army Medical University, Chongqing, China.
Yao LiuDepartment of Pharmacy, Daping Hospital, Army Medical University, No. 10 Changjiang Branch Road, Yuzhong District, Chongqing 400042, China.ORCID https://orcid.org/0000-0001-7507-2410

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Drug-induced interstitial lung disease (DILD) is an increasingly common cause of morbidity and mortality. However, due to the lack of specificity, DILD detection remains an unsolved public health challenge. Objectives: For the first time, we aimed to examine DILD reports submitted to the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) to identify demographic characteristics and top drugs associated with DILD at a group level (including age, sex, drug class, and country stratification) and individual drug level. Design: A retrospective analysis of the FAERS database was examined by disproportionality analysis. Methods: We reviewed the FAERS database from 2004 to 2021, using search terms 'interstitial lung disease' and sorting cases by generic drug name. The reporting odds ratio, proportional reporting ratio, and Bayesian confidence propagation neural network were calculated as the measure of strength of association. Results: There were 32,821 DILD reports in the FAERS. After excluding reports without age, sex, or country data according to the specific measurement, the median age of patients was 68 (interquartile range: 59), 54.77% were male, and 46.00% of reports came from Japan. The top drug classes related to DILD in the FAERS were antineoplastic, followed by cardiovascular and antirheumatic agents, in varying order in different sexes. Fam-trastuzumab deruxtecan-nxki, ramucirumab, and eribulin were the top three drugs with the highest strength of association. We also found some drugs without DILD in the labels, such as amiodarone, temsirolimus, and ursodiol. There are significant differences in DILD reports in various countries. For example, the United States and France reported more cardiovascular agents, whereas Canada reported more antirheumatic agents. Conclusion: We found the top drugs and drug classes that were associated with DILD in the FAERS, which provides a real-world window for different ages, sexes, and countries to formulate precise pharmacovigilance policies.

Indexed as

adverse eventdata miningdisproportionality analysisdrug-induced interstitial lung diseaseFAERS databasepharmacovigilance

Identifiers

PMID38293566
PMCPMC10823853

What OpenQuestion holds

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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.