Evidence map›Paper›PMID 41546737›Full record

ArticleDiscover oncology2026

Bibliometric analysis of research trends and hotspots in immunotherapy biomarkers for non-small cell lung cancer from 2015 to 2024.

Xiangnv Meng, Zhongting Lu, Fu Mi

Abstract read
In one paragraph

Article in Discover oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

3 authors.

Xiangnv Meng *Second Department of Medical Oncology, Cangzhou Central Hospital, Cangzhou, Hebei, China. mengxiangnv1123@163.com.
Zhongting Lu *General Hospital of Ningxia Medical University, Yinchuan, Ningxia, China.
Fu MiSecond Department of Medical Oncology, Cangzhou Central Hospital, Cangzhou, Hebei, China.

Funding

Cangzhou Key Research and Development Program Project No. 222106036
6 · The paper itself

Abstract

backgroundImmunotherapy has revolutionized the treatment of non-small cell lung cancer (NSCLC), offering promising alternatives to traditional therapies. This study aimed to conduct a bibliometric analysis to identify research hotspots and emerging themes in immunotherapy biomarkers for NSCLC from 2015 to 2024.

methodsArticles and reviews from the Web of Science Core Collection (January 1, 2015–December 31, 2024) were retrieved on June 23, 2025. Networks of countries, institutions, authors, journals, co-cited references, and keywords were constructed using CiteSpace and VOSviewer, with visualizations created using Scimago Graphica.

resultsA total of 2134 publications by 14,723 researchers from 73 countries and 3670 institutions, across 427 journals, were included. The number of annual publications increased steadily, peaking at 404 in 2024. China led in publication volume, while the U.S. had the highest citation impact. Tongji University was the most productive institution, and Caicun Zhou was the most prolific author. Among the journals, Cancers had the highest publication volume, while Lung Cancer had the highest citation frequency. The key topics identified included immune checkpoint inhibitors (ICIs), programmed death-ligand 1 (PD-L1), tumor mutational burden (TMB), liquid biopsy, and combination therapy. Emerging fields included the tumor microenvironment (TME), radiomics, proliferative signaling, and the gut microbiota.

conclusionThis bibliometric analysis provides a comprehensive overview of NSCLC immunotherapy biomarker research, highlighting key trends and emerging directions. These insights are crucial for advancing precision immunotherapies and biomarker-driven strategies.

Indexed as

Bibliometric analysisBiomarkersData visualizationImmunotherapyNSCLC

Identifiers

PMID41546737
PMCPMC12894536

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.