Evidence map›Paper›PMID 39471191›Full record

ArticlePloS one2024

Using a Bayesian analytic approach to identify county-level ecological factors associated with survival among individuals with early-onset colorectal cancer.

Sunny Siddique, Laura V M Baum, Nicole C Deziel, Jill R Kelly, Joshua L Warren, Xiaomei Ma

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Sunny SiddiqueDepartment of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, Connecticut, United States of America.ORCID 0000-0002-5746-1161
Laura V M BaumDivision of Medical Oncology, Department of Medicine, Yale School of Medicine, New Haven, CT, United States of America.ORCID 0000-0002-4853-6213
Nicole C DezielDepartment of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut, United States of America.ORCID 0000-0002-5751-9191
Jill R KellyDepartment of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut, United States of America.
Joshua L WarrenDepartment of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America.ORCID 0000-0002-6274-6970
Xiaomei MaDepartment of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, Connecticut, United States of America.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

backgroundIn the United States (US), incidence of early age of onset colorectal cancer (EOCRC, diagnosed <50 years of age) has been increasing. Using a Bayesian analytic approach, we evaluated the association between county-level ecological factors and survival among individuals with EOCRC and identified hotspot and coldspot counties with unexplained low and high survival, respectively.

methodsPrincipal component (PC) analysis was used to reduce dimensionality of 36 county-level social, behavioral, and preventive factors from the Centers for Disease Control and Prevention data. Survival information was derived from the Surveillance, Epidemiology, and End Results Program data from January 1, 2000 to December 31, 2019. The association between the identified PCs and survival was evaluated using multivariable spatial generalized linear mixed models. Counties with residual low and high survival (i.e., unexplained by the PCs) were classified as hotspots and coldspots, respectively.

resultsFour PCs were used to explain the spatial variability in 5-year survival among 75,215 individuals with EOCRC: PC1) poverty, chronic disease, health risk behaviors (β = -0.03, 95% credible interval (CrI): -0.04, -0.03); PC2) younger age, chronic disease-free, minority status (β = -0.01, 95% CrI: -0.02, 0.00); PC3) urban environment, preventive services (β = 0.02, 95% CrI: 0.00, 0.03); and PC4) older age (-0.04, 95% CrI: -0.06, -0.02). Among individuals with distant malignancies, the residual spatial variability remained high for two US counties: 1) Salt Lake County, UT residents experiencing 26.5% (95% CrI: 1.5%, 47.8%) lower odds of survival [hotspot], and 2) Riverside County, CA residents experiencing 37% (95% CrI: 7.97%, 78.8%) higher odds survival [coldspot] after adjustment for county-level factors.

conclusionsCounty-level ecological factors are strongly associated with survival among individuals with EOCRC. Yet there is some evidence of survival disparities among individuals with distant malignancies that remain unexplained by the included factors.

Indexed as

Bayes TheoremColorectal NeoplasmsAdultAge of OnsetFemaleHumansMaleMiddle AgedPrincipal Component AnalysisRisk FactorsSEER ProgramUnited States

Identifiers

PMID39471191
PMCPMC11521299

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