Evidence map›Paper›PMID 40530674›Full record

ArticleCancer2025

An examination of factors associated with disparities in clinical trial eligibility guided by the Socioecological Model.

Yayi Zhao, Rossybelle P Amorrortu, J Kevin Hicks, Melany A Garcia, Eric B Haura, Jun Yin, Susan T Vadaparampil, Dana E Rollison

Abstract read
In one paragraph

Article in Cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

8 authors.

Yayi ZhaoCancer Epidemiology Program, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, USA.
Rossybelle P AmorrortuCancer Epidemiology Program, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, USA.
J Kevin HicksDepartment of Pathology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, USA.
Melany A GarciaCancer Epidemiology Program, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, USA.
Eric B HauraDepartment of Thoracic Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, USA.
Jun YinDepartment of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, USA.
Susan T VadaparampilHealth Outcomes and Behavior Program, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, USA.
Dana E RollisonCancer Epidemiology Program, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, USA.ORCID https://orcid.org/0000-0002-3171-8045

Funding

TRANSLATIONAL RESEARCHP30CA076292 · NCI · UNIVERSITY OF SOUTH FLORIDA · PI John L. Cleveland · 1998 to 2026
$93.5M
Advancing Clinical Trials: Working through Outreach, Navigation and Digital Enabled Referral and Recruitment Strategies (ACT WONDERS)U01CA274971 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI SUSAN T VADAPARAMPIL · 2022 to 2026
$3.9M
Moffitt Cancer Center Support Grant, Grant/Award Number P30-CA076292National Cancer Institute of the National Institutes of Health, Grant/Award Number U01CA274971NCI NIH HHS P30 CA076292NCI NIH HHS U01 CA274971
6 · The paper itself

Abstract

backgroundPatients from diverse demographic groups remain underrepresented in cancer clinical trials (CCTs) because of various factors, including disparities in eligibility. In the current study, the authors investigated associations between demographic characteristics and factors associated with CCT eligibility and enrollment using real-world data.

methodsA cross-sectional analysis was conducted among 113,030 adult patients with cancer who were treated at Moffitt Cancer Center between 2011 and 2021. Eligibility criteria from 100 CCTs were manually abstracted and conceptually mapped to variables in the Moffitt Cancer Analytics Platform. Other factors potentially affecting patient eligibility or enrollment in CCTs were identified following the Socioecological Model and were compared across patient groups by age, sex, race, and ethnicity.

resultsThe most frequent eligibility criteria in the abstracted CCTs included laboratory results associated with liver function (89%) and bone marrow function (88%). Thirty-nine percent of the protocols required genetic testing. Black/African American patients experienced a higher prevalence of diabetes (Δ = 3.2%), human immunodeficiency virus infection (Δ = 1.4%), and abnormal laboratory results compared with White patients. Hispanic patients experienced a higher prevalence of human immunodeficiency virus infection (Δ = 0.2%) and a history of organ transplantation (Δ = 0.2%) compared with non-Hispanic patients. Compared with younger patients, older adults had a higher prevalence of nononcologic conditions. Female, Black, and/or Hispanic patients were more likely to experience barriers to care, including childcare and transportation, and to live in more socially deprived areas compared with male, White, or non-Hispanic patients.

conclusionsRestrictive CCT eligibility criteria and social determinants of health may pose structural barriers that disproportionately affect patient diversity. Investigators should leverage real-world data to design appropriate trial eligibility criteria.

Indexed as

Clinical Trials as TopicEligibility DeterminationHealthcare DisparitiesNeoplasmsPatient SelectionAdultAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedSocioeconomic Factorscancer treatment trialsclinical trialsdisparitieseligibility criteriaoncologysocial determinants of health (SDOH)socioecological model

Identifiers

PMID40530674
PMCPMC12263167

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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.