Evidence map›Paper›PMID 39621782›Full record

ArticlePLoS medicine2024

A latent class assessment of healthcare access factors and disparities in breast cancer care timeliness.

Matthew R Dunn, Didong Li, Marc A Emerson, Caroline A Thompson, Hazel B Nichols, Sarah C Van Alsten, Mya L Roberson, Stephanie B Wheeler, Lisa A Carey, Terry Hyslop and 2 more

Abstract read
In one paragraph

Article in PLoS medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Applying a Novel Measure of Community-Level Healthcare Access to Assess Breast Cancer Care Timeliness.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025
    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

12 authors.

Matthew R DunnDepartment of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, United States of America.ORCID https://orcid.org/0000-0001-7618-4983
Didong LiDepartment of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, United States of America.ORCID https://orcid.org/0000-0001-9146-705X
Marc A EmersonDepartment of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, United States of America.
Caroline A ThompsonDepartment of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, United States of America.
Hazel B NicholsDepartment of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, United States of America.ORCID https://orcid.org/0000-0003-0972-1560
Sarah C Van AlstenDepartment of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, United States of America.ORCID https://orcid.org/0000-0003-2131-6939
Mya L RobersonLineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina, United States of America.ORCID https://orcid.org/0000-0002-9908-910X
Stephanie B WheelerLineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina, United States of America.
Lisa A CareyLineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina, United States of America.
Terry HyslopThomas Jefferson University, Sidney Kimmel Cancer Center, Philadelphia, Pennsylvania, United States of America.
Jennifer Elston LafataLineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina, United States of America.ORCID https://orcid.org/0000-0002-8550-6195
Melissa A TroesterDepartment of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, United States of America.

Funding

Virology Research Program (Program 4)P30CA016086 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Deborah F. Tate · 1985 to 2026
$201.5M
Tissue Procurement & PathologyP50CA058223 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BENJAMIN CARLISLE CALHOUN · 1992 to 2026
$59.3M
UNC-CH CENTER FOR ENVIRONMENTAL HEALTH &SUSCEPTIBILITYP30ES010126 · NIEHS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Hazel B Nichols · 2001 to 2026
$36.3M
Cancer Control Education ProgramT32CA057726 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Melissa B Gilkey, Melissa A. Troester · 2017 to 2026
$3.7M
P53, DNA Repair Imbalance, and Immune Response in Breast Cancer Mortality DisparitiesR01CA253450 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KATHERINE A. HOADLEY, Melissa A. Troester · 2021 to 2026
$3.6M
Cancer Care Quality Training ProgramT32CA116339 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ETHAN M. BASCH, Stephanie Brooke Wheeler · 2018 to 2026
$3.0M
NCI NIH HHS P30 CA016086NCI NIH HHS P50 CA058223NCI NIH HHS R01 CA253450NCI NIH HHS T32 CA057726NCI NIH HHS T32 CA116339NIEHS NIH HHS P30 ES010126
6 · The paper itself

Abstract

backgroundDelays in breast cancer diagnosis and treatment lead to worse survival and quality of life. Racial disparities in care timeliness have been reported, but few studies have examined access at multiple points along the care continuum (diagnosis, treatment initiation, treatment duration, and genomic testing). METHODS AND

findingsThe Carolina Breast Cancer Study (CBCS) Phase 3 is a population-based, case-only cohort (n = 2,998, 50% black) of patients with invasive breast cancer diagnoses (2008 to 2013). We used latent class analysis (LCA) to group participants based on patterns of factors within 3 separate domains: socioeconomic status ("SES"), "care barriers," and "care use." These classes were evaluated in association with delayed diagnosis (approximated with stages III-IV at diagnosis), delayed treatment initiation (more than 30 days between diagnosis and first treatment), prolonged treatment duration (time between first and last treatment-by treatment modality), and receipt of OncotypeDx genomic testing (evaluated among patients with early stage, ER+ (estrogen receptor-positive), HER2- (human epidermal growth factor receptor 2-negative) disease). Associations were evaluated using adjusted linear-risk regression to estimate relative frequency differences (RFDs) with 95% confidence intervals (CIs). Delayed diagnosis models were adjusted for age; delayed and prolonged treatment models were adjusted for age and tumor size, stage, and grade at diagnosis; and OncotypeDx models were adjusted for age and tumor size and grade. Overall, 18% of CBCS participants had late stage/delayed diagnosis, 35% had delayed treatment initiation, 48% had prolonged treatment duration, and 62% were not OncotypeDx tested. Black women had higher prevalence for each outcome. We identified 3 latent classes for SES ("high SES," "moderate SES," and "low SES"), 2 classes for care barriers ("few barriers," "more barriers"), and 5 classes for care use ("short travel/high preventive care," "short travel/low preventive care," "medium travel," "variable travel," and "long travel") in which travel is defined by estimated road driving time. Low SES and more barriers to care were associated with greater frequency of delayed diagnosis (RFDadj = 5.5%, 95% CI [2.4, 8.5]; RFDadj = 6.7%, 95% CI [2.8,10.7], respectively) and prolonged treatment (RFDadj = 9.7%, 95% CI [4.8 to 14.6]; RFDadj = 7.3%, 95% CI [2.4 to 12.2], respectively). Variable travel (short travel to diagnosis but long travel to surgery) was associated with delayed treatment in the entire study population (RFDadj = 10.7%, 95% CI [2.7 to 18.8]) compared to the short travel, high use referent group. Long travel to both diagnosis and surgery was associated with delayed treatment only among black women. The main limitations of this work were inability to make inferences about causal effects of individual variables that formed the latent classes, reliance on self-reported socioeconomic and healthcare history information, and generalizability outside of North Carolina, United States of America.

conclusionsBlack patients face more frequent delays throughout the care continuum, likely stemming from different types of access barriers at key junctures. Improving breast cancer care access will require intervention on multiple aspects of SES and healthcare access.

Indexed as

Breast NeoplasmsHealthcare DisparitiesHealth Services AccessibilityAdultAgedBlack or African AmericanDelayed DiagnosisFemaleHumansLatent Class AnalysisMiddle AgedTime FactorsTime-to-TreatmentWhite

Identifiers

PMID39621782
PMCPMC11649116

What OpenQuestion holds

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LicenceCC BY
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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.