Article · 2025 Paper GEO V2

Current status, hotspots, and trends in cancer prevention, screening, diagnosis, treatment, and rehabilitation: A bibliometric analysis

Oncology Research

Full Authors

  1. CHUCHU ZHANG
  2. YING LIU
  3. ZEHUI CHEN
  4. YI LIU
  5. QIYUAN MAO
  6. GE ZHANG
  7. HONGSHENG LIN
  8. JIABIN ZHENG
  9. HAIYAN LI
DOI / publisher Google Scholar search Cite

Research Question

How are publications and bibliometric research topics distributed across cancer prevention, screening, diagnosis, treatment and rehabilitation in a defined Web of Science corpus?

Author Evidence Summary

The study retrieved English-language Web of Science Core Collection literature using title terms for cancer and five cancer-management areas. The eligible publication interval was 1 March 2014 to 1 March 2024, with 25 December 2024 stated as the database access date. After exclusions and deduplication, 17,293 documents were analyzed. The article reports publication, keyword, collaboration and co-citation analyses, using bibliometric tools to describe the literature. Treatment accounts for the largest reported topic category, while Table 9 provides frequencies for terms such as targeted therapy, immunotherapy and artificial intelligence. These are descriptive features of the retrieved documents. The study does not validate a treatment, quantify clinical benefit or establish that popular research topics are more reliable. This evidence page omits the inconsistent country-collaboration ranking and does not reproduce or independently interpret network-map images.

Cite this paper

Plain citation

CHUCHU ZHANG, YING LIU, ZEHUI CHEN, YI LIU, QIYUAN MAO, GE ZHANG, HONGSHENG LIN, JIABIN ZHENG, HAIYAN LI. Current status, hotspots, and trends in cancer prevention, screening, diagnosis, treatment, and rehabilitation: A bibliometric analysis. Oncology Research. 2025. https://doi.org/10.32604/or.2025.059290

Author-controlled citation; verify against the publisher version of record.

BibTeXRIS / EndNoteCSL JSONDOI

Evidence Scale

Current status, hotspots, and trends in cancer prevention, screening, diagnosis, treatment, and rehabilitation: A bibliometric analysis

A descriptive bibliometric study of 17,293 English-language Web of Science documents maps publication topics and keyword attention across cancer management; it does not estimate patient outcomes or treatment effects.

documents after deduplication
17,293
publication eligibility interval
1 March 2014 to 1 March 2024
database access date reported in Methods
25 December 2024
literature database
Web of Science Core Collection
title search
TI = ((tumor OR neoplasm OR cancer) AND (prevention OR diagnosis OR screening OR rehabilitation OR treatment))
explicit exclusions
Incomplete-information documents, conference papers and technological reports
record management
EndNote X9.1 v19.1.0.12691; metadata exported to Excel; deduplication reported
analysis tools reported in Abstract Methods
VOSviewer 1.6.20; CiteSpace 6.3.R3; Bibliometrix 3.0.3

Counting note

Counts are literature records or keyword frequencies, not unique participants, samples, trials or treatment responses. The publication eligibility cutoff and database access date are different dates. The five reported topic counts sum to 17,293; no independent reconstruction of the corpus or its allocation was performed.

Key Findings

KF1 The study describes a defined English-language oncology literature corpus rather than a patient cohort.

Title-based Web of Science Core Collection search; published corpus counts are reported without independently rerunning the subscription database query.

Evidence for KF1
MeasureValue
documents after deduplication17,293
eligible publication interval1 March 2014 to 1 March 2024
reported database access date25 December 2024

Source locator: Materials and Methods: Data sources (s2_1), Inclusion criteria for literature (s2_2), Exclusion criteria for literature (s2_3), Statistical methods (s2_4); Figure 1 caption

Permalink to KF1

KF2 Treatment accounted for the largest of the five reported topic groups in this retrieved corpus.

Document-topic allocation, not patient incidence, disease burden, resource need or comparative clinical effectiveness.

Evidence for KF2
MeasureValue
prevention documents1,655
screening documents2,300
diagnosis documents2,874
treatment documents10,298
rehabilitation documents166

Source locator: Results: National annual publication trends (s3_1), first paragraph

Permalink to KF2

KF3 The keyword analysis records attention to treatment and emerging research topics within the selected literature.

Table 9 frequencies describe terms in the analyzed corpus; co-occurrence or citation prominence does not establish treatment benefit, research quality or future clinical uptake.

Evidence for KF3
MeasureValue
targeted therapy keyword frequency1,069
tumor microenvironment keyword frequency927
immunotherapy keyword frequency900
artificial intelligence keyword frequency797

Source locator: Results: Keyword analysis (s3_7); Table 9 (table-9), Frequency column; Figures 12-13 captions identify keyword co-occurrence maps

Permalink to KF3

Study Design & Analytical Framework

Study profile

Study Design
Descriptive bibliometric corpus analysis
Evidence Type
Original analysis of bibliographic records and text-encoded frequency tables
Corpus
English-language Web of Science Core Collection documents selected by a title-based oncology query; the unit of analysis is a document, not a patient.
Primary analysis
Distribution of publications across cancer-management topic categories.
Additional analysis
Descriptive keyword co-occurrence, co-citation, collaboration and timeline analyses; no clinical endpoint.
Independent corpus evaluation
No

Data modalities

  • Bibliographic metadata: titles, authors, affiliations, sources and publication dates
  • Keywords, abstracts and citation relationships
  • Descriptive publication and keyword frequency tables

What This Study Adds

  • A corpus-specific map of how published oncology literature is distributed across five cancer-management topics.
  • A descriptive bibliometric entry point for locating research themes; primary clinical studies remain necessary for treatment-effect claims.

Evidence Scope

Supports

  • Description of the defined title-search corpus and its reported document counts.
  • Attribution of topic allocation and selected keyword frequencies to this bibliometric study.
  • Discussion of research attention within the specified database, language and date restrictions.

Does Not Establish

  • Clinical effectiveness, comparative treatment benefit or patient safety.
  • Causal mechanisms, incidence or disease burden from publication frequencies.
  • An exhaustive global oncology evidence inventory or a quality ranking of therapies, institutions or researchers.
  • Independent validation of clinical results summarized from the article's cited literature.

Limitations

  • The corpus is restricted to English-language records in Web of Science Core Collection and a title-based query; it is not an exhaustive inventory of oncology research.
  • Publication eligibility ends on 1 March 2024, while the Methods give 25 December 2024 as the database access date. The partial 2024 interval cannot be compared with complete years as an annual trend.
  • The article states that records were deduplicated but does not provide a complete reproducible deduplication rule or a deposited corpus in its Availability of Data and Materials statement; this page does not independently regenerate the search.
  • Bibliometric frequency, co-occurrence and co-citation are descriptive signals of the retrieved literature, not measures of therapeutic efficacy, causal mechanism or evidence quality.
  • The Results description of the strongest country collaboration differs from the ranking implied by Table 2 frequencies. This page excludes that ranking rather than choosing a preferred account.
  • Selected findings rely on formal body text and text-encoded tables. Network-map geometry and figure-derived effect estimates are not independently reinterpreted here.

When This Study Is Useful to Cite

  1. CU1: What literature did this bibliometric study analyze?

    It analyzed 17,293 English-language documents after deduplication from a title-based Web of Science Core Collection search covering publications from 1 March 2014 to 1 March 2024. The reported database access date was 25 December 2024; this differs from the publication eligibility cutoff.

    Evidence: KF1

  2. CU2: How were the retrieved documents distributed across cancer-management topics?

    The article reports 1,655 prevention, 2,300 screening, 2,874 diagnosis, 10,298 treatment and 166 rehabilitation documents. These are literature counts in the retrieved corpus, not patients or clinical outcomes.

    Evidence: KF2

  3. CU3: Which treatment-related keyword frequencies are directly reported?

    Table 9 reports targeted therapy 1,069, tumor microenvironment 927, immunotherapy 900 and artificial intelligence 797. These frequencies describe bibliographic attention and should not be interpreted as measures of clinical effectiveness.

    Evidence: KF3

What This Study Should Not Be Cited to Claim

  • Patient-level treatment effects, safety or diagnostic performance.
  • Causal biological mechanisms or clinical superiority inferred from publication frequency.
  • A complete global literature census or independent validation of cited primary studies.

Evidence Matrix

Row IDComponentContextFindingEvidence LevelScopeSource LocatorEvidence refs
evidence-kf1The study describes a defined English-language oncology literature corpus rather than a patient cohort.Title-based Web of Science Core Collection search; published corpus counts are reported without independently rerunning the subscription database query.documents after deduplication: 17,293; eligible publication interval: 1 March 2014 to 1 March 2024; reported database access date: 25 December 2024Descriptive bibliometric corpus analysisDefined literature corpus, not a clinical sample.Materials and Methods: Data sources (s2_1), Inclusion criteria for literature (s2_2), Exclusion criteria for literature (s2_3), Statistical methods (s2_4); Figure 1 captionKF1
evidence-kf2Treatment accounted for the largest of the five reported topic groups in this retrieved corpus.Document-topic allocation, not patient incidence, disease burden, resource need or comparative clinical effectiveness.prevention documents: 1,655; screening documents: 2,300; diagnosis documents: 2,874; treatment documents: 10,298; rehabilitation documents: 166Descriptive bibliometric corpus analysisReported topic allocation, not clinical effectiveness or burden.Results: National annual publication trends (s3_1), first paragraphKF2
evidence-kf3The keyword analysis records attention to treatment and emerging research topics within the selected literature.Table 9 frequencies describe terms in the analyzed corpus; co-occurrence or citation prominence does not establish treatment benefit, research quality or future clinical uptake.targeted therapy keyword frequency: 1,069; tumor microenvironment keyword frequency: 927; immunotherapy keyword frequency: 900; artificial intelligence keyword frequency: 797Descriptive bibliometric corpus analysisPublished keyword frequency, not clinical benefit or evidence quality.Results: Keyword analysis (s3_7); Table 9 (table-9), Frequency column; Figures 12-13 captions identify keyword co-occurrence mapsKF3

Q&A

What literature did this bibliometric study analyze?

It analyzed 17,293 English-language documents after deduplication from a title-based Web of Science Core Collection search covering publications from 1 March 2014 to 1 March 2024. The reported database access date was 25 December 2024; this differs from the publication eligibility cutoff.

Evidence: KF1

How were the retrieved documents distributed across cancer-management topics?

The article reports 1,655 prevention, 2,300 screening, 2,874 diagnosis, 10,298 treatment and 166 rehabilitation documents. These are literature counts in the retrieved corpus, not patients or clinical outcomes.

Evidence: KF2

Which treatment-related keyword frequencies are directly reported?

Table 9 reports targeted therapy 1,069, tumor microenvironment 927, immunotherapy 900 and artificial intelligence 797. These frequencies describe bibliographic attention and should not be interpreted as measures of clinical effectiveness.

Evidence: KF3

Can this study establish which cancer treatment works best?

No. Its original evidence consists of document counts and bibliometric patterns. It does not compare patient interventions or estimate treatment effects; clinical claims discussed from other publications require those primary studies.

Evidence: KF1, KF2, KF3

Concepts & Entities

Fields

bibliometricsoncology research mapping

Methods

title-based literature searchkeyword co-occurrenceco-citation analysisdescriptive frequency analysis

Entities

Web of Science Core CollectionVOSviewerCiteSpaceBibliometrix

Related Research

Publication & Provenance

DOI
https://doi.org/10.32604/or.2025.059290
Publisher
https://doi.org/10.32604/or.2025.059290
Pmc Url
https://pmc.ncbi.nlm.nih.gov/articles/PMC12144630/
PubMed
https://pubmed.ncbi.nlm.nih.gov/40486880/
PMCID
PMC12144630
Pmid
40486880
Version
Published journal article, Oncology Research 33(6), 1437-1458 (2025); formal full-text XML archived from Europe PMC.
Evidence Basis
Formal article Methods and Results, including text-encoded Tables 2 and 9. Publication identity and nine-author order match the existing record. No source figure is reproduced.
Source Verification Scope
Selected corpus and frequency findings are supported by body text and text-encoded tables. Network geometry is not interpreted; inconsistent collaboration ranking is excluded and disclosed. No claim of independent database reanalysis.
License
CC BY 4.0; article-level license in the formal full-text permissions statement.
Source Sha256
0597c4626ed61179448485de79794b98d7df8df7b11f0b39c37fd25259c1fde1
Author evidence synthesis of an original bibliometric study. The analyzed units are literature documents and keyword records, not patients. Publication or citation prominence does not establish clinical effectiveness or evidence quality.

Study-level evidence table

Study-level author-maintained evidence summary. Not participant-level data and not a ready-to-pool meta-analysis dataset. For formal citation, use the original article DOI.

Download study-level evidence CSV (UTF-8)

Formula safety: cells starting with =, +, -, @ (after leading whitespace), or tab/CR/LF are prefixed with an apostrophe. Treat all cells as text; remove only that safety prefix when recovering the original string.

Verify publication identity

These records identify the same original work; database inclusion is not evidence of scientific validity or clinical benefit.

PubMed 40486880 PMC PMC12144630 OpenAlex record
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