Evidence map›Paper›PMID 23028869›Full record

ArticlePloS one2012

Local breast cancer spatial patterning: a tool for community health resource allocation to address local disparities in breast cancer mortality.

Dana M Brantley-Sieders, Kang-Hsien Fan, Sandra L Deming-Halverson, Yu Shyr, Rebecca S Cook

Abstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 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.

Dana M Brantley-SiedersDepartment of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
Kang-Hsien Fan
Sandra L Deming-Halverson
Yu Shyr
Rebecca S Cook

Funding

Tumor Immunology and Microenvironment Research ProgramP30CA068485 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI MATTHEW J TYSKA · 1995 to 2026
$172.8M
VANDERBILT UNIVERSITY CTSA FOR PEDIATRIC RESEARCHUL1RR024975 · NCRR · VANDERBILT UNIVERSITY · PI BERNARD, GORDON RAPHAEL · 2007 to 2011
$45.7M
The Vanderbilt Institute for Clinical and Translational Research (VICTR) KL2KL2RR024977 · NCRR · VANDERBILT UNIVERSITY · PI BERNARD, GORDON RAPHAEL · 2007 to 2011
$3.0M
EphA2 Receptor in Endothelial Cell-Mediated Tumor ProgressionR01CA148934 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BRANTLEY-SIEDERS, DANA M · 2011 to 2015
$1.6M
HER3 Signaling in Development and Cancer of the BreastR01CA143126 · NCI · VANDERBILT UNIVERSITY · PI COOK, REBECCA SARA · 2010 to 2014
$1.5M
The Vanderbilt Institute for Clinical and Translational Research (VICTR) TL1TL1RR024978 · NCRR · VANDERBILT UNIVERSITY · PI BERNARD, GORDON RAPHAEL · 2007 to 2011
$1.3M
NCI NIH HHS K01CA1179151NCI NIH HHS P30 CA068485NCI NIH HHS P30 CA68485NCI NIH HHS R01 CA143126NCI NIH HHS R01CA143126NCI NIH HHS R01 CA148934NCI NIH HHS R01CA148934NCRR NIH HHS KL2 RR024977NCRR NIH HHS TL1 RR024978NCRR NIH HHS UL1 RR024975
6 · The paper itself

Abstract

Despite available demographic data on the factors that contribute to breast cancer mortality in large population datasets, local patterns are often overlooked. Such local information could provide a valuable metric by which regional community health resources can be allocated to reduce breast cancer mortality. We used national and statewide datasets to assess geographical distribution of breast cancer mortality rates and known risk factors influencing breast cancer mortality in middle Tennessee. Each county in middle Tennessee, and each ZIP code within metropolitan Davidson County, was scored for risk factor prevalence and assigned quartile scores that were used as a metric to identify geographic areas of need. While breast cancer mortality often correlated with age and incidence, geographic areas were identified in which breast cancer mortality rates did not correlate with age and incidence, but correlated with additional risk factors, such as mammography screening and socioeconomic status. Geographical variability in specific risk factors was evident, demonstrating the utility of this approach to identify local areas of risk. This method revealed local patterns in breast cancer mortality that might otherwise be overlooked in a more broadly based analysis. Our data suggest that understanding the geographic distribution of breast cancer mortality, and the distribution of risk factors that contribute to breast cancer mortality, will not only identify communities with the greatest need of support, but will identify the types of resources that would provide the most benefit to reduce breast cancer mortality in the community.

Indexed as

Black PeopleHealthcare DisparitiesWhite PeopleBlack or African AmericanBreast NeoplasmsFemaleGeography, MedicalHumansIncidenceMammographyMass ScreeningResearch DesignResource AllocationRisk FactorsSocial ClassSocioeconomic Factors

Identifiers

PMID23028869
PMCPMC3460936

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.