Evidence map›Paper›PMID 38947042›Full record

ArticlemedRxiv : the preprint server for health sciences2024

State-level disparities in cervical cancer prevention and outcomes in the U.S.: 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 readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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, and Stanford Health Policy, Freeman-Spogli Institute for International Studies, Stanford University, Stanford, CA, USA.ORCID 0000-0001-5076-1172
Valeria GraciaDepartment of Health Policy, School of Medicine, Stanford University, Stanford, CA, USA.ORCID 0000-0003-4853-2922
Marina WolfUniversity of Minnesota Medical School, Minneapolis, MN, USA.ORCID 0000-0001-9129-3432
Ran ZhaoDivision of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA.
Caleb W EasterlyMD/PhD Program, University of North Carolina at Chapel Hill, Chapel Hill, NC.ORCID 0000-0001-7853-377X
Jane J KimCenter for Health Decision Science, Department of Health Policy and Management, Harvard TH Chan School of Public Health, Boston, MA, USA.
Karen CanfellThe Daffodil Centre, University of Sydney, a joint venture with Cancer Council NSW, Sydney, NSW.ORCID 0000-0002-6443-6618
Inge M C M de KokDepartment of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands.ORCID 0000-0002-9419-0452
Ruanne V BarnabasDivision of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.ORCID 0000-0002-1793-6003
Shalini KulasingamDivision of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA.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
NCI NIH HHS U01 CA253912
6 · The paper itself

Abstract

Background: Despite HPV vaccines' availability for over a decade, coverage across the US varies. While 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. Methods: We developed a new mathematical model of HPV transmission and cervical cancer, creating US 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 <4 per 100k women. Results: Increasing vaccination coverage to 80% in Texas over ten 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 (Crl:0.66-1.53) per 100,000 women, and California a 24.4% (CrI:20.0-30.0%) reduction, from 1.01 (Crl:0.66-1.44) to 0.76 (Crl:0.50-1.09) per 100,000 women. Achieving 80% coverage in five years will provide slightly larger and sooner reductions. If the vaccination coverage levels in 2019 continue, cervical cancer elimination could occur nationally by 2051 (Crl:2034-2064), but state timelines may vary by decades. Conclusion: Targeting 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.

Identifiers

PMID38947042
PMCPMC11213118

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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.