Evidence map›Paper›PMID 41455016›Full record

ArticleCancer causes & control : CCC2025

Beyond screening: neighborhood-level factors associated with colorectal cancer stage at diagnosis.

Trisha Lal, Natalie N Chakraborty, Siran Koroukian, Johnie Rose, Weichuan Dong, Richard S Hoehn

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Article in Cancer causes & control : CCC, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Trisha LalDivision of Surgical Oncology, University Hospitals, Cleveland Medical Center, Cleveland, Ohio, 44106, USA.
Natalie N ChakrabortyDivision of Surgical Oncology, University Hospitals, Cleveland Medical Center, Cleveland, Ohio, 44106, USA.
Siran KoroukianSchool of Medicine, Case Western Reserve University, Cleveland, Ohio, 44106, USA.
Johnie RoseSchool of Medicine, Case Western Reserve University, Cleveland, Ohio, 44106, USA.
Weichuan DongDepartment of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, Ohio, 44106, USA. wdong2@houstonmethodist.org.
Richard S HoehnDivision of Surgical Oncology, University Hospitals, Cleveland Medical Center, Cleveland, Ohio, 44106, USA. Richard.hoehn@uhhospitals.org.

Funding

TUMOR METABOLISM PROGRAMP30CA043703 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI Amar Desai · 1987 to 2026
$142.3M
NCI NIH HHS P30 CA043703
6 · The paper itself

Abstract

purposeWhile increasing colorectal cancer (CRC) screening uptake is a major public health goal, it remains unclear whether screening rates consistently translate to high earlier-stage diagnosis at the community level. This study examined the relationship between screening and early stage CRC diagnosis, identifying barriers that may disrupt this pathway.

methodsWe used census-tract-level data on CRC patients diagnosed between 2010 and 2019 in the Ohio Cancer Incidence Surveillance System, linked to community-level screening estimates from CDC PLACES (2018). Census tracts were grouped into sociodemographically similar communities using the Max-p regionalization method. We applied geographic weighted regression (GWR) to assess spatial variation in the screening-early diagnosis relationship and used the Variable Selection Using Random Forest (VSURF) algorithm to identify key predictors of early stage diagnosis. Linear regression models evaluated associations between predictors, screening, and early stage diagnosis.

results2,952 census tracts were aggregated into 869 communities for analysis. Higher screening rates were not consistently associated with early stage diagnosis, as revealed by GWR, which showed significant regional variation. VSURF identified structural factors, rather than screening uptake, as top predictors of early stage diagnosis. In multivariable models, uninsurance (β - 0.29) and public transportation dependence (β - 0.31) were associated with lower early stage diagnosis, while the screening rate was not independently associated.

conclusionsStructural barriers may disrupt the screening-to-diagnosis pathway at the community level. Our findings underscore the importance of investing in follow-up infrastructure, including navigation and transportation, to ensure that screening achieves its goal of early detection.

Indexed as

Colorectal NeoplasmsEarly Detection of CancerNeighborhood CharacteristicsAgedFemaleHumansIncidenceMaleMass ScreeningMiddle AgedNeoplasm StagingOhioColorectal cancerEarly diagnosisHealth disparitiesScreening uptake

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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.