Evidence map›Paper›PMID 40794364›Full record

ArticleDiscover oncology2025

Mapping the future: bibliometric analysis of omics research trends in non-small cell lung cancer.

Yanqian Zhu, Jiawei Chen, Yufei Wang, Jinyang Hu, Chen Gao, Linyu Wu

Abstract read
In one paragraph

Article in Discover oncology, 2025. 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.

Yanqian Zhu *Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), 54 Youdian Road, Shangcheng District, Hangzhou, 310006, China.
Jiawei Chen *Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), 54 Youdian Road, Shangcheng District, Hangzhou, 310006, China.
Yufei WangDepartment of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), 54 Youdian Road, Shangcheng District, Hangzhou, 310006, China.
Jinyang HuDepartment of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), 54 Youdian Road, Shangcheng District, Hangzhou, 310006, China.
Chen GaoDepartment of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), 54 Youdian Road, Shangcheng District, Hangzhou, 310006, China. doctor_gaochen@zcmu.edu.cn.
Linyu WuDepartment of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), 54 Youdian Road, Shangcheng District, Hangzhou, 310006, China. wulinyu@zcmu.edu.cn.

Funding

Medical and Health Science and Technology Project of Zhejiang Province 2024KY129Medical and Health Science and Technology Project of Zhejiang Province 2024KY132National Natural Science Foundation of China 82102128Natural Science Foundation of Zhejiang Province LTGY23H180001Natural Science Foundation of Zhejiang Province LTGY24H180006Research Project of Zhejiang Chinese Medical University 2022FSYYZY08Zhejiang Province Traditional Chinese Medicine Science and Technology Plan Project 2025ZL302Zhejiang Province Traditional Chinese Medicine Science and Technology Plan Project 2025ZS012
6 · The paper itself

Abstract

purposeOmics technologies, such as genomics, transcriptomics, proteomics, and radiomics, play an increasingly important role in the diagnosis and treatment of non-small cell lung cancer (NSCLC). It is, therefore, essential to unveil the research landscape and future trends of relevant research. This study aims to explore the research fields based on omics technologies in NSCLC, elucidating the research status, hotspots, and trends from a bibliometric perspective.

methodsThe Web of Science Core Collection was utilized to retrieve relevant publications in omics technologies and their applications in NSCLC. By using the bibliometric methods and tools ("bibliometrix" R package, VOSviewer, and CiteSpace), data and visualized analyses for annual publication outputs, countries, institutions, authors, journals, references, and keywords proceeded.

resultsA total of 5,337 publications were involved in our analysis. These articles, written by 32,286 authors, originated in 5,863 institutions from 82 countries and were published in 797 journals. The Journal of Thoracic Oncology and Clinical Cancer Research were representative journals in omics-based research in NSCLC. "Survival," "adenocarcinoma," "mutation," "epidermal growth factor receptor," "resistance," and "chemotherapy" were the highest-frequency keywords. Liquid biopsy and deep learning were also trending topics in omics-related research, according to keyword clustering, trend topics, and citation burst analysis.

conclusionOmics technologies, including genomics, transcriptomics, and proteomics, were widely used in the diagnosis, prognosis, and treatment of NSCLC. And innovative methods, including liquid biopsy and deep learning, demonstrate a profound impact on advancing the understanding and treatment strategies for NSCLC and warrant further investigation.

Indexed as

Bibliometric analysisNon-small cell lung cancerOmicsVisualized study

Identifiers

PMID40794364
PMCPMC12344032

What OpenQuestion holds

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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.