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Record W4407878129 · doi:10.3390/curroncol32030122

HPV and Cervical Cancer—Biology, Prevention, and Treatment Updates

2025· review· en· W4407878129 on OpenAlexvenueno aff
Emilia Włoszek, Katherine Krupa, Eliza Skrok, Michał Piotr Budzik, Andrzej Deptała, Anna Badowska-Kozakiewicz

Bibliographic record

VenueCurrent Oncology · 2025
Typereview
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCervical cancerHPV vaccinesVaccinationCancerDiagnostic testHuman papillomavirusIntensive care medicineCancer treatmentHPV infectionImmunologyInternal medicinePediatrics

Abstract

fetched live from OpenAlex

One of the most significant breakthroughs in cancer research has been the identification of persistent infection with certain human papillomaviruses (HPV) genotypes as the cause of cervical cancer. Since then, a range of diagnostic and therapeutic methods has been developed based on this discovery. This article aims to describe the latest updates in the biology, prevention, and treatment of HPV-related cervical cancer. The current state of knowledge regarding vaccinations, diagnostic tests, and cervical cancer therapies is presented. The latest WHO guidelines on vaccinations are presented, as well as announcements of upcoming changes. The final part of the article summarizes promising new diagnostic and treatment methods, as well as perspectives and the latest research findings on self-administered diagnostic tests, the use of therapeutic vaccines, and circulating cell-free DNA in diagnosis. Despite the significant progress made in recent years, the strategy based on vaccination and testing remains the cornerstone in the fight against HPV-related cervical cancer.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.261
GPT teacher head0.574
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations35
Published2025
Admission routes1
Has abstractyes

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