Evidence map›Paper›PMID 40841132›Full record

ArticleJournal for immunotherapy of cancer2025

Immune-related adverse events of neoadjuvant immunotherapy in patients with perioperative cancer: a machine-learning-driven, decade-long informatics investigation.

Song-Bin Guo, Deng-Yao Liu, Rong Hu, Zhen-Zhong Zhou, Yuan Meng, Hai-Long Li, Wei-Juan Huang, Xiao-Peng Tian

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal for immunotherapy of cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 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

13 citing papers in PubMed, 2 syntheses or guidelines 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

8 authors.

Song-Bin Guo *Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China tianxp@sysucc.org.cn wjhuang@jnu.edu.cn guosb.sysucc@yeah.net.ORCID http://orcid.org/0000-0001-5768-0922
Deng-Yao Liu *Department of Interventional Radiology, Xinjiang Key Laboratory of Translational Biomedical Engineering Research, Tumor Hospital Affiliated to Xinjiang Medical University, The Third Clinical Medical College of Xinjiang Medical University, Urumqi, China.
Rong Hu *Department of Hematology/Oncology, Fujian Children's Hospital (Fujian Branch of Shanghai Children's Medical Center), College of Clinical Medicine for Obstetrics and Gynecology and Pediatrics, Fujian Medical University, Fuzhou, China.
Zhen-Zhong Zhou *Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China.
Yuan MengState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China.
Hai-Long LiDepartment of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China.
Wei-Juan HuangDepartment of Pharmacology, College of Pharmacy, Jinan University, Guangzhou, China tianxp@sysucc.org.cn wjhuang@jnu.edu.cn guosb.sysucc@yeah.net.
Xiao-Peng TianDepartment of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China tianxp@sysucc.org.cn wjhuang@jnu.edu.cn guosb.sysucc@yeah.net.ORCID http://orcid.org/0000-0003-4601-3475

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Research on neoadjuvant immunotherapy (NAI) is increasingly focusing on immunotherapy-related adverse events (AEs). However, many unknowns remain in this field. Hence, through the machine learning (ML)-driven informatics analysis, this study aimed to profile the global decade-long scientific landscape of AEs of NAI and further reveal its critical issues and directions that deserve deeper exploration. During the past decade, the amount of research in the field of NAI safety has displayed a positive trend (annual growth rate: 30.2%), and it has achieved good global collaboration (international coauthorship: 17.43%). Using an unsupervised clustering algorithm, we identified six dominant research clusters, among which Cluster 1 (standardizing response assessment criteria for NAI to minimize its adverse reactions; average citation=34.86±95.48) had the highest impact and Cluster 6 (efficacy and safety of multiple therapy patterns combination) was an emerging research cluster (temporal central tendency=2022.43, research effort dispersion=0.52), with "irAEs" (s=0.4242 (95% CI: 0.01142 to 0.8371), R

Indexed as

ImmunotherapyMachine LearningNeoadjuvant TherapyNeoplasmsHumansImmune Checkpoint Inhibitor

Identifiers

PMID40841132
PMCPMC12374627

What OpenQuestion holds

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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.