Evidence map›Paper›PMID 40439714›Full record

ArticleCancer control : journal of the Moffitt Cancer Center

Signal Mining and Analysis of Drug-Induced Myelosuppression: A Real-World Study From FAERS.

Kaiyue Xia, Shupeng Chen, Yingjian Zeng, Nana Tang, Meiling Zhang

Abstract read
In one paragraph

Article in Cancer control : journal of the Moffitt Cancer Center. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Kaiyue XiaSchool of Clinical Medicine, Jiangxi University of Chinese Medicine, Nanchang, China.
Shupeng ChenHematology Department, Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Nanchang, China.ORCID 0009-0007-8064-4840
Yingjian ZengHematology Department, Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Nanchang, China.ORCID 0009-0005-0949-2982
Nana TangHematology Department, Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Nanchang, China.
Meiling ZhangQihuang National Medical Academy, Jiangxi University of Chinese Medicine, Nanchang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

IntroductionDrug-induced myelosuppression (DIM) is a serious side effect of several medications, particularly chemotherapy, immunosuppressants, and targeted therapies, which can lead to infections, anemia, and bleeding. While these drugs are effective, their adverse effects can disrupt treatment plans and reduce quality of life. However, early identification of DIM remains challenging, as many associated drugs do not explicitly list this risk, complicating clinical monitoring.MethodsThis study utilized the FDA Adverse Event Reporting System (FAERS) database to perform signal mining and assess the risks of DIM. Reports from the first quarter of 2004 to the third quarter of 2024 were analyzed using signal detection algorithms such as Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Empirical Bayesian Geometric Mean (EBGM). These methods helped identify drug signals related to DIM and explore risk factors and occurrence patterns.ResultsThe study analyzed 21 380 adverse event reports related to DIM, showing a significant increase in the number of reports since 2019, peaking at 3501 in 2021. Among patients, 50.2% were female, 35.5% were male, and the majority (44.42%) were aged between 18 and 65. Breast cancer patients had the highest DIM incidence (10.6%). Geographically, China reported the most cases (57.4%), followed by Japan (12.4%), and the United States (6.76%). The drugs most frequently linked to DIM included trastuzumab, bevacizumab, venetoclax, methotrexate, and pertuzumab. Additionally, 12 new drug signals were identified that were not labeled for DIM risk, including PERTUZUMAB, SODIUM CHLORIDE, and MESNA, which showed particularly strong or unexpected associations.ConclusionThis study identifies new DIM-related drug signals and emphasizes the need for early detection to improve clinical management and optimize treatment regimens. The findings provide valuable evidence for drug safety monitoring and can help reduce DIM-related risks in cancer treatment.

Indexed as

Adverse Drug Reaction Reporting SystemsAntineoplastic AgentsData MiningDrug-Related Side Effects and Adverse ReactionsAdolescentAdultAgedBayes TheoremDatabases, FactualFemaleHumansMaleMiddle AgedRisk FactorsUnited StatesUnited States Food and Drug AdministrationAntineoplastic Agentsadverse event reportingdrug-induced myelosuppression (DIM)drug safetyFAERS databasepersonalized treatment regimensreporting odds ratio (ROR)risk assessmentsignal mining

Identifiers

PMID40439714
PMCPMC12123114

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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.