Evidence map›Paper›PMID 39605908›Full record

ArticleFrontiers in pharmacology2024

Risks of malignancies related to disease-modifying antirheumatic drugs in rheumatoid arthritis: a pharmacovigilance analysis using the FAERS database.

Wan Xiong, Yilin Li, Lin Hu, Gefei He, Juanjuan Huang

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Wan XiongDepartment of Pharmacy, The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University, Changsha, China.
Yilin LiDepartment of Information and Digital Technology, PowerChina Zhongnan Engineering Corporation Limited, Changsha, China.
Lin HuDepartment of Pharmacy, The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University, Changsha, China.
Gefei HeDepartment of Pharmacy, The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University, Changsha, China.
Juanjuan HuangDepartment of Pharmacy, The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Over the years when disease-modifying antirheumatic drugs (DMARDs) have been used in rheumatoid arthritis patients, reports of malignancies have emerged. This study aims to investigate the association between malignancies and DMARDs by using data extracted from the Food and Drug Administration Adverse Event Reporting System (FAERS). Methods: FAERS data (January 2019 to December 2023) were reviewed. For each drug-event pair, the disproportionality analysis was conducted to evaluate the risk of malignancy. Multivariate logistic regression was implemented to mitigate potential biases. Moreover, the time to onset of malignancy was also evaluated. Results: We conducted a detailed search for rheumatoid arthritis indications and identified a total of 17,412 adverse event reports associated with malignancies, with selective DMARDs designated as the role code "primary suspect". At the preferred term level, there were 198 positive signals, among which the lower limit of the 95% confidence interval for the information component is 3.55 for squamous cell carcinoma of the skin, 2.39 for breast cancer, and 2.27 for lymphoproliferative disorder. In comparison to other DMARDs, targeted synthetic DMARDs were associated with a broader range of malignancies at both preferred term and Standardized MedDRA Queries levels. The number of adverse events reported in female patients is approximately 2-3 times higher than men, and the median age across the population was approximately 62 years. In terms of onset time, the conventional synthetic DMRADs exhibited a relatively longer median time, ranging from 3.58 to 7.08 years, while the targeted synthetic DMARDs demonstrated a shorter median time of 0.83-1.67 years. Conclusion: Our study uncovers varying degrees of malignancy risks related to DMARDs, with a significantly higher risk observed in targeted synthetic DMARDs. Additionally, novel malignancy signals, not documented in product labels, have been detected. In the future, further research will be necessary to validate our findings.

Indexed as

DMARDsFAERSmalignancypharmacovigilancerheumatoid arthritis

Identifiers

PMID39605908
PMCPMC11598350

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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.