Evidence map›Paper›PMID 42079638›Full record

ArticleFrontiers in immunology2026

Dynamic changes in gut microbiota and metabolites in advanced lung cancer patients with immune-related adverse events.

Xu Han, Dan Zang, Meixi Lin, Yuting Yin, Dan Liu, Qiangguo Sun, Jun 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
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0citing papers in PubMed
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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

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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

7 authors.

Xu Han *Department of Oncology, The Second Hospital of Dalian Medical University, Dalian, China.
Dan Zang *Department of Oncology, The Second Hospital of Dalian Medical University, Dalian, China.
Meixi Lin *Department of Oncology, The Second Hospital of Dalian Medical University, Dalian, China.
Yuting Yin *Department of Respiratory, The Second Hospital of Dalian Medical University, Dalian, China.
Dan LiuDepartment of Oncology, The Second Hospital of Dalian Medical University, Dalian, China.
Qiangguo SunDepartment of Oncology, The Second Hospital of Dalian Medical University, Dalian, China.
Jun ChenDepartment of Oncology, The Second Hospital of Dalian Medical University, Dalian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Immune-related adverse events (irAEs) represent an urgent clinical challenge. Although accumulating evidence suggests that irAEs are associated with the gut microbiota and its metabolites, our understanding of the dynamic alterations in the gut microbiota and related metabolic profiles throughout the onset and progression of irAEs remains limited. Methods: A total of 48 fecal samples were collected from 32 lung cancer patients treated with immune checkpoint inhibitors, including 16 patients who developed irAEs and 16 who did not. Fecal samples were collected at baseline and, in patients with irAEs, at the time of irAEs onset. Metagenomic sequencing and untargeted metabolomics analyses were performed to identify baseline differences in gut microbiota and metabolites, characterize longitudinal dynamic changes in gut microbiota and metabolite profiles in patients with irAEs, and construct a machine learning based random forest model to predict the occurrence of irAEs. Results: There were baseline differences in microbial communities and metabolites between the two groups. In the non-irAEs group, Conclusions: The occurrence and development of irAEs are associated with the composition of the gut microbiota and metabolites, as well as their dynamic changes over time. These findings highlight the potential of gut microbiota and metabolites as biomarkers for predicting the occurrence and progression of irAEs.

Indexed as

Drug-Related Side Effects and Adverse ReactionsGastrointestinal MicrobiomeImmune Checkpoint InhibitorsLung NeoplasmsMetabolomeAgedFecesFemaleHumansMaleMetabolomicsMiddle AgedImmune Checkpoint Inhibitorsdynamic changesgut metabolitesgut microbiotaimmune-related adverse eventslung cancer

Identifiers

PMID42079638
PMCPMC13130655

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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.