Evidence map›Paper›PMID 35406469›Full record

ArticleCancers2022

A Machine-Learning-Based Bibliometric Analysis of the Scientific Literature on Anal Cancer.

Pierfrancesco Franco, Eva Segelov, Anders Johnsson, Rachel Riechelmann, Marianne G Guren, Prajnan Das, Sheela Rao, Dirk Arnold, Karen-Lise Garm Spindler, Eric Deutsch and 4 more

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
3.3field-weighted citation impact, top 8% of its field
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

11 citing papers in PubMed, 15 citations in OpenAlex.

  1. Optimising chemoradiotherapy in anal cancer.ESMO gastrointestinal oncology · 2026
    Review
  2. Review
  3. Innovative radiotherapy approaches.ESMO gastrointestinal oncology · 2026
    Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
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

14 authors at 12 institutions in 10 countries.

Pierfrancesco FrancoDepartment of Translational Medicine (DIMET), University of Eastern Piedmont, 28100 Novara, Italy.ORCID 0000-0003-2276-0687
Eva SegelovSchool of Clinical Sciences, Faculty of Medicine, Monash University, Clayton 3168, Australia.ORCID 0000-0002-4410-6144
Anders JohnssonDepartment of Hematology, Oncology and Radiation Physics, Skåne University Hospital, 22002 Lund, Sweden.
Rachel RiechelmannDepartment of Clinical Oncology, AC Camargo Cancer Center, São Paulo 01000-000, Brazil.
Marianne G GurenDepartment of Oncology, Oslo University Hospital, 0316 Oslo, Norway.
Prajnan DasDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Sheela RaoGI Unit, Royal Marsden Hospital, London SW3 6JJ, UK.
Dirk ArnoldAsklepios Tumorzentrum Hamburg, AK Altona, 22763 Hamburg, Germany.
Karen-Lise Garm SpindlerDepartment of Oncology, Aarhus University Hospital, 8200 Aarhus, Denmark.ORCID 0000-0001-8781-3212
Eric DeutschInstitute Gustave Roussy, 94805 Villejuif, France.
Marco KrengliDepartment of Translational Medicine (DIMET), University of Eastern Piedmont, 28100 Novara, Italy.ORCID 0000-0002-2064-8379
Vincenzo TomboliniRadiation Oncology, Policlinico "Umberto I" and Department of Radiological, Oncological and Pathological Sciences, "Sapienza" University of Rome, 00161 Rome, Italy.ORCID 0000-0001-5359-9991
David Sebag-MontefioreLeeds Institute of Medical Research, University of Leeds, Leeds LS2 9JT, UK.
Francesca De FeliceRadiation Oncology, Policlinico "Umberto I" and Department of Radiological, Oncological and Pathological Sciences, "Sapienza" University of Rome, 00161 Rome, Italy.
Policlinico Umberto I · ITUniversità degli Studi del Piemonte Orientale “Amedeo Avogadro” · ITAarhus University Hospital · DKAC Camargo Hospital · BRAsklepios Klinik Altona · DEInstitut Gustave Roussy · FRMonash Health · AUOslo University Hospital · NORoyal Marsden Hospital · GBSkåne University Hospital · SEThe University of Texas MD Anderson Cancer Center · USUniversity of Leeds · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Squamous-cell carcinoma of the anus (ASCC) is a rare disease. Barriers have been encountered to conduct clinical and translational research in this setting. Despite this, ASCC has been a prime example of collaboration amongst researchers. We performed a bibliometric analysis of ASCC-related literature of the last 20 years, exploring common patterns in research, tracking collaboration and identifying gaps. The electronic Scopus database was searched using the keywords "anal cancer", to include manuscripts published in English, between 2000 and 2020. Data analysis was performed using R-Studio 0.98.1091 software. A machine-learning bibliometric method was applied. The bibliometrix R package was used. A total of 2322 scientific documents was found. The average annual growth rate in publication was around 40% during 2000-2020. The five most productive countries were United States of America (USA), United Kingdom (UK), France, Italy and Australia. The USA and UK had the greatest link strength of international collaboration (22.6% and 19.0%). Two main clusters of keywords for published research were identified: (a) prevention and screening and (b) overall management. Emerging topics included imaging, biomarkers and patient-reported outcomes. Further efforts are required to increase collaboration and funding to sustain future research in the setting of ASCC.

Indexed as

anal cancerbibliometricsHIVHPVmachine learningoncologyradiotherapysquamous-cell carcinoma

Identifiers

PMID35406469
PMCPMC8996998
OpenAlexW4220822358

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.