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Record W4413458009 · doi:10.1016/j.vaccine.2025.127632

Impact of HPV vaccination on the incidence and clearance of HPV infections in sexually active young women

2025· article· en· W4413458009 on OpenAlexafffundabout
Pareesa Kassam, Cassandra Laurie, Mariam El‐Zein, Joseph E. Tota, Pierre‐Paul Tellier, François Coutlée, Ann N. Burchell, Eduardo L. Franco

Bibliographic record

VenueVaccine · 2025
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsMcGill University Health CentreSt. Michael's HospitalCentre Hospitalier de l’Université de MontréalMcGill University
FundersDepartment of Family and Community Medicine, University of TorontoCanadian Institutes of Health ResearchMerck CanadaCanada Research ChairsMerck
KeywordsSexually activeIncidence (geometry)MedicineVaccinationImmunologyGynecologyVirologyHuman immunodeficiency virus (HIV)

Abstract

fetched live from OpenAlex

BACKGROUND: Human papillomavirus (HPV) vaccination protects against new HPV infections, but seemingly no impact on the clearance of existing infections. We assessed the association between HPV vaccination and incidence and clearance of HPV infections among sexually active women in the Carrageenan-gel Against Transmission of Cervical HPV trial, conducted in Montreal, Canada (2013-2020). METHODS: Participants attended seven visits over 12 months, where they provided self-collected vaginal samples and completed questionnaires on risk factors. Participants self-reported their HPV vaccination status at screening, enrollment, and follow-up visits. Samples were genotyped for HPV using the Linear Array assay. We used Cox regression to estimate hazard ratios (HR) and 95 % confidence intervals (CI) for incidence and clearance of HPV infections, with the unit of analysis being the HPV type. Analyses considered stringent (reported in ≥2 sources) and non-stringent (reported in ≥1 source) definitions of vaccination status. HPV types were classified as vaccine-targeted (HPVs 6/11/16/18) and non-vaccine-targeted (within-species: HPVs 31/33/35/39/44/45/52/58/59/67/68/70; cross-species: HPVs 26/34/40/42/51/53/54/56/61/62/66/69/71/72/73/81/82/83/84/89). To control for confounding, we applied inverse probability of treatment weights, based on study and participant characteristics. RESULTS: Of 461 participants, 45.8 % and 55.5 % were vaccinated according to the stringent and non-stringent definitions, respectively. Vaccination was associated with a lower risk of new HPVs 6/11/16/18 detection in the most stringent (HR = 0.41, CI:0.23-0.72) and least stringent (HR = 0.41, CI:0.23-0.72) definitions. Vaccination was not associated with incident within-species (most stringent: HR = 1.21, CI:0.90-1.64; least stringent: HR = 1.10, CI:0.82-1.48) or cross-species (most stringent: HR = 1.21, CI:0.94-1.55; least stringent: HR = 1.11, CI:0.87-1.41) HPV types. Vaccination did not impact clearance of baseline HPVs 6/11/16/18 (most stringent: HR = 1.23, CI:0.47-3.24; least stringent: HR = 1.40, CI:0.57-3.47), within-species (most stringent: HR = 1.50, CI:0.88-2.56; least stringent: HR = 1.58, CI:0.98-2.55) or cross-species HPV infections (most stringent: HR = 0.71, CI:0.49-1.03; least stringent: HR = 0.80, CI:0.56-1.16). CONCLUSION: We found that HPV vaccination is effective as a prophylactic measure but has no therapeutic effects on existing infections.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.362
Teacher spread0.346 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations3
Published2025
Admission routes3
Has abstractyes

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