Evidence map›Paper›PMID 25856581›Full record

ArticlePloS one2015

Local bladder cancer clusters in southeastern Michigan accounting for risk factors, covariates and residential mobility.

Geoffrey M Jacquez, Chen Shi, Jaymie R Meliker

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 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

3 authors.

Geoffrey M JacquezDepartment of Geography, University at Buffalo, The State University of New York, Buffalo, New York, United States of America; BioMedware Inc., Ann Arbor, Michigan, United States of America.
Chen ShiDepartment of Geography, University at Buffalo, The State University of New York, Buffalo, New York, United States of America.
Jaymie R MelikerDepartment of Preventive Medicine and Graduate Program in Public Health, Stony Brook University, Stony Brook, New York, United States of America.

Funding

Case-only Cancer Clustering for Mobile PopulationsR44CA135818 · NCI · BIOMEDWARE · PI JACQUEZ, GEOFFREY M. · 2009 to 2010
$878k
Cancer Clustering for Residential HistoriesR44CA117171 · NCI · BIOMEDWARE · PI JACQUEZ, GEOFFREY M. · 2007 to 2008
$750k
NCI NIH HHS R44 CA117171NCI NIH HHS R44CA117171NCI NIH HHS R44 CA135818NCI NIH HHS R44CA135818
6 · The paper itself

Abstract

backgroundIn case control studies disease risk not explained by the significant risk factors is the unexplained risk. Considering unexplained risk for specific populations, places and times can reveal the signature of unidentified risk factors and risk factors not fully accounted for in the case-control study. This potentially can lead to new hypotheses regarding disease causation.

methodsGlobal, local and focused Q-statistics are applied to data from a population-based case-control study of 11 southeast Michigan counties. Analyses were conducted using both year- and age-based measures of time. The analyses were adjusted for arsenic exposure, education, smoking, family history of bladder cancer, occupational exposure to bladder cancer carcinogens, age, gender, and race.

resultsSignificant global clustering of cases was not found. Such a finding would indicate large-scale clustering of cases relative to controls through time. However, highly significant local clusters were found in Ingham County near Lansing, in Oakland County, and in the City of Jackson, Michigan. The Jackson City cluster was observed in working-ages and is thus consistent with occupational causes. The Ingham County cluster persists over time, suggesting a broad-based geographically defined exposure. Focused clusters were found for 20 industrial sites engaged in manufacturing activities associated with known or suspected bladder cancer carcinogens. Set-based tests that adjusted for multiple testing were not significant, although local clusters persisted through time and temporal trends in probability of local tests were observed.

conclusionQ analyses provide a powerful tool for unpacking unexplained disease risk from case-control studies. This is particularly useful when the effect of risk factors varies spatially, through time, or through both space and time. For bladder cancer in Michigan, the next step is to investigate causal hypotheses that may explain the excess bladder cancer risk localized to areas of Oakland and Ingham counties, and to the City of Jackson.

Indexed as

Age FactorsArsenicCluster AnalysisEducational StatusGeographyHumansMichiganOccupational ExposureRacial GroupsRisk FactorsSex FactorsSmokingUrinary Bladder NeoplasmsArsenic

Identifiers

PMID25856581
PMCPMC4391784

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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.