Evidence map›Paper›PMID 40069825›Full record

ArticleBMC pharmacology & toxicology2025

Post-market safety profile of cefiderocol: a real-world pharmacovigilance exploratory analysis based on U.S. FDA adverse event reporting system (FAERS).

Hao Lin, Chen Zhu, Shuang Liu, Yingmin Bi, Jindong Hu, Mohan Ju

Abstract read
In one paragraph

Article in BMC pharmacology & toxicology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

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

  1. Pooled it
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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

6 authors.

Hao Lin *Department of Oncology, Huashan Hospital, Fudan University, Shanghai, China.
Chen Zhu *Department of Hematology, Huashan Hospital, Fudan University, Shanghai, China.
Shuang LiuInstitute of Antibiotics, Huashan Hospital, Fudan University, Shanghai, China.
Yingmin BiInstitute of Antibiotics, Huashan Hospital, Fudan University, Shanghai, China.
Jindong HuDepartment of Integrative Medicine, Huashan Hospital, Fudan University, Shanghai, China. jind.hu@outlook.com.
Mohan JuInstitute of Antibiotics, Huashan Hospital, Fudan University, Shanghai, China. 08301010203@fudan.edu.cn.

Funding

National Natural Science Foundation of China 82002176Shanghai Municipal Health Commission 20214Y0392
6 · The paper itself

Abstract

backgroundCefiderocol is a new drug class, which is approved to treat Gram-negative bacteria infection. Its approval for marketing has provided clinicians with additional options for treating antimicrobial resistant gram-negative infections. The aim of our study was to assess the safety profiles of cefiderocol in real-world through data mining of the United States Food and Drug Administration Adverse Event Reporting System (FAERS).

methodsWe included adverse event (AE) reports regarding cefiderocol submitted to the FAERS from 2019 quarter 4 (2019Q4) to 2024 quarter 3 (2024Q3). Disproportionality analyses, including reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN) and Multi-item Gamma Poisson Shrinker (MGPS) techniques were performed to identify the signals of disproportionate reporting of AEs in patients receiving cefiderocol. A signal of disproportionate reporting was detected if the lower limit of the 95% confidence interval (CI) of ROR > 1, the PRR was ≥ 2(while the Chi-Square of PRR was ≥ 4), the lower limit of 95% CI of the information component (IC025) was > 0, the lower limit of 95% CI of the Empirical Bayes Geometric Mean (EBGM05) was > 2 and at least 3 AEs were reported.

resultsA total of 29 significant preferred terms (PTs) were identified among the 592 cefiderocol-associated adverse events (AEs) reports collected from the FAERS database. Cefiderocol-induced adverse events involved 24 System Organ Class (SOC). 29 positive signals of disproportionate reporting are also presented, such as Pathogen resistance (n = 16, ROR 189.35, PRR 184.26, IC 7.52, EBGM 183.89), Systemic candida (n = 3, ROR 138.79, PRR 138.19, IC7.11, EBGM 137.88), Drug resistance (n = 30, ROR 131.96, PRR 125.33, IC6.97, EBGM 125.16), and Drug effect less than expected (n = 6, ROR 68.42, PRR 67.74, IC6.08, EBGM 67.69). The most frequently observed were Death, Drug resistance and Treatment failure.

conclusionsOur findings offer significant evidence regarding the safety profile of cefiderocol in real-world settings. This information may assist clinicians and pharmacists in enhancing their vigilance and improving the overall safety of cefiderocol in clinical practice.

Indexed as

Adverse Drug Reaction Reporting SystemsAnti-Bacterial AgentsCefiderocolCephalosporinsPharmacovigilanceAdultBayes TheoremFemaleHumansMaleMiddle AgedUnited StatesUnited States Food and Drug AdministrationAnti-Bacterial AgentsCefiderocolCephalosporinsAdverse drug eventsCefiderocolFDA adverse event reporting systemReal-world data analysis

Identifiers

PMID40069825
PMCPMC11899456

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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.