Evidence map›Paper›PMID 42164501›Full record

ArticleFrontiers in immunology2026

Antibiotic use and immune-related adverse events in patients treated with immune checkpoint inhibitors: analysis of the FAERS database.

Jia Yu, Qinxiao Li, Shangpu Zou, Yiyin Rong, Yuting Zhang, Chengshui Chen

Abstract read
In one paragraph

Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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.

Jia Yu *Zhejiang Province Engineering Research Center for Endoscope Instruments and Technology Development, Department of Pulmonary and Critical Care Medicine, Quzhou People's Hospital, The Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou, China.
Qinxiao Li *Department of Dermatology, Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Shangpu ZouDepartment of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Yiyin RongDepartment of Dermatology, Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Yuting ZhangZhejiang Province Engineering Research Center for Endoscope Instruments and Technology Development, Department of Pulmonary and Critical Care Medicine, Quzhou People's Hospital, The Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou, China.
Chengshui ChenZhejiang Province Engineering Research Center for Endoscope Instruments and Technology Development, Department of Pulmonary and Critical Care Medicine, Quzhou People's Hospital, The Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The use of antibiotics may influence the efficacy and toxicity of immune checkpoint inhibitors (ICIs) by altering the gut microbiota. However, current evidence on the link between antibiotic use and immune-related adverse events (irAEs) is limited. This study aims to evaluate whether antibiotics increase the risk of irAEs in ICI-treated patients and to examine their relationship to the timing of irAEs onset. Methods: We analyzed data from the FAERS database from 2014 to the fourth quarter of 2024. Using multivariable logistic regression and descriptive statistical analyses, we evaluated the association between antibiotic co-reporting and irAE reporting frequency and the timing across different antibiotic categories and ICIs regimens. Results: Our study included 155,157 patients treated with ICIs, of whom 9,518 (6.1%) received antibiotic therapy. Patients who used antibiotics had a significantly higher reported frequency risk of irAEs (OR = 1.17; 95%CI: 1.12-1.23; FDR<0.001) compared to those who did not. The strongest associations were observed in patients receiving fluoroquinolones, sulfonamides, penicillin, macrolides, cephalosporins, and monobactams. Co-reporting was associated with a higher reported frequency of irAEs in patients receiving PD-L1 inhibitors (OR = 1.51; 95% CI: 1.39-1.65; FDR<0.001). In exploratory descriptive analysis restricted to patients who reported irAEs, the median time to first reported irAE was shorter in the antibiotic co-reporting group than in the non-co-reporting group (31 days (IQR: 9-105) vs. 42 days (IQR: 14-122), Wilcoxon rank-sum test P < 0.001). Stratified analysis by ICI type showed that this pattern was most evident in patients receiving PD-1 inhibitors. Conclusions: Analysis of the FAERS database suggests that antibiotic co-reporting during ICIs therapy is associated with a higher reported frequency of irAEs and a shorter median time to first reported irAE among patients who experienced irAEs. These findings are subject to the inherent limitations of the FAERS database, including the inability to determine the temporal sequence of antibiotic and ICI exposure, unmeasured confounding, reporting artifacts, and the unsuitability of spontaneous reporting data for formal time-to-event analysis. Prospective cohort studies with detailed medication timing, clinical phenotyping, and microbiome profiling are needed to validate these signals.

Indexed as

Anti-Bacterial AgentsDrug-Related Side Effects and Adverse ReactionsImmune Checkpoint InhibitorsNeoplasmsAdverse Drug Reaction Reporting SystemsAgedDatabases, FactualFemaleHumansMaleMiddle AgedAnti-Bacterial AgentsImmune Checkpoint Inhibitorsadverse event reporting system (FAERS)antibioticscancerimmune checkpoint inhibitorsimmune-related adverse events

Identifiers

PMID42164501
PMCPMC13183842

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.