Evidence map›Paper›PMID 41123893›Full record

ArticleJAMA network open2025

National Outcomes of Increasing Cervical Cancer Screening in Federally Qualified Health Centers.

Trisha L Amboree, Prajakta Adsul, Haluk Damgacioglu, Kathleen M Schmeler, Elizabeth Y Chiao, Roxana Cruz, Kalyani Sonawane, Ashish A Deshmukh, Jane R Montealegre

Abstract read
In one paragraph

Article in JAMA network open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Rural-Urban Differences in Cervical Cancer Screening Patterns: A Cross-Sectional Analysis of the 2021 National Health Interview Survey (NHIS).The Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care Association · 2026
    Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Trisha L AmboreeDepartment of Public Health Science, Medical University of South Carolina, Charleston.
Prajakta AdsulDepartment of Internal Medicine, School of Medicine, University of New Mexico, Albuquerque.
Haluk DamgaciogluDepartment of Public Health Science, Medical University of South Carolina, Charleston.
Kathleen M SchmelerDepartment of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston.
Elizabeth Y ChiaoDepartments of Epidemiology and Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston.
Roxana CruzTexas Association of Community Health Centers, Austin.
Kalyani SonawaneDepartment of Public Health Science, Medical University of South Carolina, Charleston.
Ashish A DeshmukhDepartment of Public Health Science, Medical University of South Carolina, Charleston.
Jane R MontealegreDepartment of Behavioral Science, The University of Texas MD Anderson Cancer Center, Houston.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Federally qualified health centers (FQHCs) deliver health care to more than 30 million people across the US and often face structural constraints that affect their ability to provide cervical cancer screening (CCS). Objectives: To estimate the number of underscreened individuals served by FQHCs and the outcomes of improving CCS in FQHCs to meet the Healthy People 2030 goal of 79.2%. Design, Setting, and Participants: This cross-sectional analysis used data from the Uniform Data System reported in 2023 by 1352 FQHCs across the US, self-reported survey-weighted CCS prevalence from the National Health Interview Survey, and population size estimates from the US Census Bureau American Community Survey 2023. Participants were US adults served by FQHCs who were CCS eligible nested within the estimated 85 364 685 CCS-eligible individuals in the US population. Analyses were conducted between September 2024 and July 2025. Exposures: Receipt of CCS at an FQHC. Main Outcomes and Measures: Percentage of CCS-eligible individuals who were up to date on CCS. Results: In 2023, a total of 7 757 211 CCS-eligible individuals were served by FQHCs, representing 9.1% (95% uncertainty interval [UI], 9.0%-9.2%) of the estimated 85 364 685 individuals in the CCS-eligible population. FQHCs served 35.9% (95% UI, 32.9%-39.6%) of the underscreened publicly insured population, 26.3% (95% UI, 23.1%-30.1%) of the underscreened rural population, 22.4% (95% UI, 20.9%-24.0%) of the underscreened population living at or below 200% of the poverty level, 19.5% (95% UI, 17.9%-21.4%) of the underscreened uninsured population, and 17.7% (95% UI, 16.7%-18.9%) of the underscreened racial or ethnic minority population. By region, FQHCs served 16.5% (95% UI, 14.6%-18.7%) of the underscreened population in the Northeast, 14.1% (95% UI, 12.7%-15.9%) in the Midwest, 13.5% (95% UI, 12.5%-14.7%) in the South, and 19.1% (95% UI, 17.3%-21.1%) in the West. Increasing CCS in FQHCs from the current estimate of 55.1% to the Healthy People 2030 goal of 79.2% would screen an additional 1 872 367 people and increase CCS among the aforementioned subgroups and regions by 2 to 6 percentage points. Conclusions and Relevance: This cross-sectional study found that FQHCs served a large number of underscreened individuals from traditionally underscreened subgroups. These results suggest that improving CCS in FQHCs would result in a substantial increase in national CCS rates.

Indexed as

Early Detection of CancerSafety-net ProvidersUterine Cervical NeoplasmsAdultAgedCross-Sectional StudiesFemaleHealth Services AccessibilityHumansMiddle AgedUnited States

Identifiers

PMID41123893
PMCPMC12547585

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.