Evidence map›Paper›PMID 23637921›Full record

ArticlePloS one2013

Trends in breast cancer stage and mortality in Michigan (1992-2009) by race, socioeconomic status, and area healthcare resources.

Tomi F Akinyemiju, Amr S Soliman, Glenn Copeland, Mousumi Banerjee, Kendra Schwartz, Sofia D Merajver

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.4field-weighted citation impact, top 11% of its field
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

14 citing papers in PubMed, 50 citations in OpenAlex.

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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

6 authors at 6 institutions in 1 country.

Tomi F AkinyemijuDepartment of Epidemiology, Columbia University Mailman School of Public Health, New York, New York, United States of America. ofa2107@columbia.edu
Amr S Soliman
Glenn Copeland
Mousumi Banerjee
Kendra Schwartz
Sofia D Merajver
Center for Global Health · USColumbia University · USMichigan Department of Health and Human Services · USUniversity of Michigan–Ann Arbor · USUniversity of Nebraska at Omaha · USWayne State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The long-term effect of socioeconomic status (SES) and healthcare resources availability (HCA) on breast cancer stage of presentation and mortality rates among patients in Michigan is unclear. Using data from the Michigan Department of Community Health (MDCH) between 1992 and 2009, we calculated annual proportions of late-stage diagnosis and age-adjusted breast cancer mortality rates by race and zip code in Michigan. SES and HCA were defined at the zip-code level. Joinpoint regression was used to compare the Average Annual Percent Change (AAPC) in the median zip-code level percent late stage diagnosis and mortality rate for blacks and whites and for each level of SES and HCA. Between 1992 and 2009, the proportion of late stage diagnosis increased among white women [AAPC = 1.0 (0.4, 1.6)], but was statistically unchanged among black women [AAPC = -0.5 (-1.9, 0.8)]. The breast cancer mortality rate declined among whites [AAPC = -1.3% (-1.8,-0.8)], but remained statistically unchanged among blacks [AAPC = -0.3% (-0.3, 1.0)]. In all SES and HCA area types, disparities in percent late stage between blacks and whites appeared to narrow over time, while the differences in breast cancer mortality rates between blacks and whites appeared to increase over time.

Indexed as

Social ClassAdultAge DistributionBreast NeoplasmsFemaleHealth ResourcesHumansMichiganNeoplasm StagingRacial Groups

Identifiers

PMID23637921
PMCPMC3639257
OpenAlexW2067877337

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.