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Record W4318755053 · doi:10.1097/ede.0000000000001580

Self-reported Human Papillomavirus Vaccination and Vaccine Effectiveness Among Men Who Have Sex with Men: A Quantitative Bias Analysis

2023· article· en· W4318755053 on OpenAlexafffundabout
Catharine Chambers, Shelley L. Deeks, Rinku Sutradhar, Joseph Cox, Alexandra de Pokomandy, Troy Grennan, Trevor Hart, Gilles Lambert, David Moore, Daniel Grace, Ramandip Grewal, Jody Jollimore, Nathan J. Lachowsky, Ashley Mah, Rosane Nisenbaum, Gina Ogilvie, Chantal Sauvageau, Darrell H. S. Tan, Anna Yeung, Ann N. Burchell

Bibliographic record

VenueEpidemiology · 2023
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsUniversity of VictoriaInstitut National de Santé Publique du QuébecCommunity Based Research CentreAIDS VancouverGovernment of Nova ScotiaBC Centre for Disease ControlUniversity of British ColumbiaMcGill UniversityInstitute for Clinical Evaluative SciencesToronto Metropolitan UniversityDalhousie UniversityUniversity of Toronto
FundersViiV HealthcareUniversité de MontréalUniversité LavalCanadian Institutes of Health ResearchMerck CanadaMinistère de la SantéMinistère de la Santé et des Services sociauxGilead SciencesBill and Melinda Gates Foundation
KeywordsMen who have sex with menHuman papillomavirusVaccinationHuman papillomavirus vaccineMedicineDemographyVirologyCervical cancerInternal medicineHuman immunodeficiency virus (HIV)CancerGardasil

Abstract

fetched live from OpenAlex

BACKGROUND: Self-report of human papillomavirus (HPV) vaccination has ~80-90% sensitivity and ~75-85% specificity. We measured the effect of nondifferential exposure misclassification associated with self-reported vaccination on vaccine effectiveness (VE) estimates. METHODS: Between 2017-2019, we recruited sexually active gay, bisexual, and other men who have sex with men aged 16-30 years in Canada. VE was derived as 1-prevalence ratio × 100% for prevalent anal HPV infection comparing vaccinated (≥1 dose) to unvaccinated men using a multivariable modified Poisson regression. We conducted a multidimensional and probabilistic quantitative bias analysis to correct VE estimates. RESULTS: Bias-corrected VE estimates were relatively stable across sensitivity values but differed from the uncorrected estimate at lower values of specificity. The median adjusted VE was 27% (2.5-97.5th simulation interval = -5-49%) in the uncorrected analysis, increasing to 39% (2.5-97.5th simulation interval = 2-65%) in the bias-corrected analysis. CONCLUSION: A large proportion of participants erroneously reporting HPV vaccination would be required to meaningfully change VE estimates.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.044
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.102
GPT teacher head0.430
Teacher spread0.328 · 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.

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

Citations9
Published2023
Admission routes3
Has abstractyes

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