Evidence map›Paper›PMID 40206559›Full record

ArticleGynecologic oncology reports2025

Experience of healthcare discrimination reported by individuals with a history of gynecologic cancer in the

Allison C Dona, Patricia I Jewett, Sarah Davidson, Deanna Teoh, Rachel I Vogel

Abstract read
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In one paragraph

Article in Gynecologic oncology reports, 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. Article
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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

5 authors.

Allison C DonaSchool of Medicine, University of Minnesota, Minneapolis, MN, USA.
Patricia I JewettDepartment of Obstetrics, Gynecology and Women's Health, Division of Gynecologic Oncology, University of Minnesota, Minneapolis, MN, USA.
Sarah DavidsonDepartment of Obstetrics, Gynecology and Women's Health, Division of Gynecologic Oncology, University of Minnesota, Minneapolis, MN, USA.
Deanna TeohDepartment of Obstetrics, Gynecology and Women's Health, Division of Gynecologic Oncology, University of Minnesota, Minneapolis, MN, USA.
Rachel I VogelDepartment of Obstetrics, Gynecology and Women's Health, Division of Gynecologic Oncology, University of Minnesota, Minneapolis, MN, USA.

Funding

Stigmatizing Language in Cancer Care Electronic Health RecordsF30MD019959 · NIMHD · UNIVERSITY OF MINNESOTA · PI Allison C Dona · 2024 to 2026
$152k
NIMHD NIH HHS F30 MD019959
6 · The paper itself

Abstract

Objective: We aimed to describe prevalence of healthcare discrimination in Methods: We analyzed survey data of participants with a history of gynecologic cancer in the Results: Of 2,195 participants, 1,001 had cervical, 579 uterine, 419 ovarian, 30 vaginal/vulvar, and 166 more than one gynecologic cancer. Most (76.5%) reported experiencing any healthcare discrimination, and 45.0% reported frequent healthcare discrimination. Those with a history of cervical cancer (52%, OR: 1.80, 95% CI: 1.42, 2.28) and multiple cancers (47.8%, OR: 1.53, 95% CI: 1.05, 2.21) had higher odds of frequently reporting discrimination than those with a history of ovarian cancer (37.5%) in the unadjusted model. The relationship observed remained but was attenuated in the adjusted model (Cervical OR: 1.35, 95% CI: 1.04, 1.75; Multiple OR: 1.35 95% CI: 0.91, 2.00). Conclusions: Healthcare discrimination was reported across cancer types. Individuals with a history of cervical or multiple gynecologic malignancies reported frequent healthcare discrimination more often than those with other gynecologic cancers.

Indexed as

Cervical cancerDiscriminationEndometrial cancerHealthcare discriminationOvarian cancerVaginal cancerVulvar cancer

Identifiers

PMID40206559
PMCPMC11981777

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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.