Evidence map›Paper›PMID 39570647›Full record

ArticleJournal of the National Cancer Institute2025

State-level disparities in cervical cancer prevention and outcomes in the United States: a modeling study.

Fernando Alarid-Escudero, Valeria Gracia, Marina Wolf, Ran Zhao, Caleb W Easterly, Jane J Kim, Karen Canfell, Inge M C M de Kok, Ruanne V Barnabas, Shalini Kulasingam

Abstract read
In one paragraph

Article in Journal of the National Cancer Institute, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Calculating epidemiological outcomes from simulated longitudinal data.medRxiv : the preprint server for health sciences · 2025
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Fernando Alarid-EscuderoDepartment of Health Policy, School of Medicine, Stanford University, Stanford, CA 94305, United States.ORCID 0000-0001-5076-1172
Valeria GraciaDepartment of Health Policy, School of Medicine, Stanford University, Stanford, CA 94305, United States.ORCID 0000-0003-4853-2922
Marina WolfUniversity of Minnesota Medical School, Minneapolis, MN 55455, United States.ORCID 0009-0004-1204-3152
Ran ZhaoDivision of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN 55415, United States.ORCID 0000-0001-9539-8274
Caleb W EasterlyDepartment of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, United States.ORCID 0000-0001-7853-377X
Jane J KimCenter for Health Decision Science, Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States.
Karen CanfellSchool of Public Health, The University of Sydney, Sydney, NSW 2050, Australia.ORCID 0000-0002-6443-6618
Inge M C M de KokDepartment of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam 3015 GD, Netherlands.ORCID 0000-0002-9419-0452
Ruanne V BarnabasDivision of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, United States.ORCID 0000-0002-1793-6003
Shalini KulasingamDivision of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN 55415, United States.ORCID 0000-0002-0932-9166

Funding

Comparative Modeling to Inform Cervical Cancer Control Policies: USPSTF SupplementU01CA253912 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI BARNABAS, RUANNE VANESSA, CANFELL, KAREN · 2020 to 2024
$7.9M
Cancer Intervention and Surveillance Modeling Network U01CA253912NCI NIH HHSNCI NIH HHS U01 CA253912NIH HHS
6 · The paper itself

Abstract

backgroundDespite human papillomavirus (HPV) vaccines' availability for over a decade, coverage across the United States varies. Although some states have tried to increase HPV vaccination coverage, most model-based analyses focus on national impacts. We evaluated hypothetical changes in HPV vaccination coverage at the national and state levels for California, New York, and Texas using a mathematical model.

methodsWe developed a new mathematical model of HPV transmission and cervical cancer, creating national- and state-level models, incorporating country- and state-specific vaccination coverage and cervical cancer incidence and mortality. We quantified the national- and state-level impact of increasing HPV vaccination coverage to 80% by 2025 or 2030 on cervical cancer outcomes and the time to elimination defined as less than 4 per 100 000 women.

resultsIncreasing vaccination coverage to 80% in Texas over 10 years could reduce cervical cancer incidence by 50.9% (95% credible interval [CrI] = 46.6%-56.1%) by 2100, from 1.58 (CrI = 1.19-2.09) to 0.78 (CrI = 0.57-1.02) per 100 000 women. Similarly, New York could see a 27.3% (CrI = 23.9%-31.5%) reduction from 1.43 (CrI = 0.93-2.07) to 1.04 (CrI = 0.66-1.53) per 100 000 women, and California a 24.4% (CrI = 20.0%-30.0%) reduction from 1.01 (CrI = 0.66-1.44) to 0.76 (CrI = 0.50-1.09) per 100 000 women. Achieving 80% coverage in 5 years will provide slightly larger and sooner reductions. If the vaccination coverage levels in 2019 continue, cervical cancer elimination could occur nationally by 2051 (CrI = 2034-2064), but state timelines may vary by decades.

conclusionTargeting an HPV vaccination coverage of 80% by 2030 will disproportionately benefit states with low coverage and higher cervical cancer incidence. Geographically focused analyses can better inform priorities.

Indexed as

Healthcare DisparitiesPapillomavirus InfectionsPapillomavirus VaccinesUterine Cervical NeoplasmsVaccination CoverageAdultCaliforniaFemaleHumansIncidenceModels, TheoreticalNew YorkTexasUnited StatesPapillomavirus Vaccines

Identifiers

PMID39570647
PMCPMC11972673

What OpenQuestion holds

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Registered trials

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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.