Evidence map›Paper›PMID 36805898›Full record

ArticleEnvironmental research2023

Modeling historic environmental pollutant exposures and non-Hodgkin lymphoma risk.

Joseph Boyle, Mary H Ward, James R Cerhan, Nathaniel Rothman, David C Wheeler

Open access · greenAbstract read
In one paragraph

Article in Environmental research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.7field-weighted citation impact, top 18% 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

8 citing papers in PubMed, 11 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

5 authors at 3 institutions in 1 country.

Joseph BoyleDepartment of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA.
Mary H WardOccupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
James R CerhanDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Nathaniel RothmanOccupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
David C WheelerDepartment of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA. Electronic address: dcwheeler@vcu.edu.
National Cancer Institute · USVirginia Commonwealth University · USMayo Clinic in Florida · US

Funding

Modeling cancer risk and environmental and socio-spatial exposures using residential historiesU01CA259376 · NCI · VIRGINIA COMMONWEALTH UNIVERSITY · PI SABO, ROY TRAVIS · 2021 to 2024
$1.2M
NCI NIH HHS U01 CA259376
6 · The paper itself

Abstract

Environmental exposures to chemicals are suspected risk factors for non-Hodgkin lymphoma (NHL), but few studies have assessed historic environmental risk factors. In this study, we estimated the associations between NHL and 1) historic environmental pollutant emissions from the Risk Screening Environmental Indicators (RSEI) model, which uses a database from the Environmental Protection Agency of toxic release emissions to air, water, and land, and 2) chemical mixtures measured in house dust (groups of PCBs, PAHs, and two mixtures of pesticides) for study participants enrolled in the NCI-SEER population-based case-control study (1998-2000) at four SEER centers - Detroit, Iowa, Los Angeles County, and Seattle. We assigned 11 years of annual temporally-varying historic environmental exposure scores by intersecting residential locations from participants' residential histories with a fine grid from the RSEI model and by performing inverse distance weighting between facilities releasing specific carcinogenic chemicals and residential locations for spatially-precise exposure assignments. We used Bayesian index low-rank kriging multiple membership models to identify important lag times for RSEI scores, cumulative effects of RSEI scores, and specific carcinogenic chemical releases into the environment. We found a significant positive association between RSEI scores and NHL at the maximum time lag of 11 years (OR = 1.17, 95% CI (1.06, 1.32)) and a significant cumulative RSEI score effect (OR = 1.30, 95% CI (1.02, 1.84)) for long-term residents in Detroit, where benzene and trichloroethylene were the most important chemicals driving this association. Additionally, we identified significant inverse associations for two study centers and time lags that did not persist in cumulative exposure models. Large weights for dichloromethane and pentachlorophenol in models of cumulative exposure also support evidence for their association with NHL risk. These results underscore the importance of considering historic and cumulative environmental exposures and using residential histories for diseases with long latency periods such as NHL.

Indexed as

Environmental ExposureEnvironmental PollutantsLymphoma, Non-HodgkinBayes TheoremCarcinogensCase-Control StudiesDustHumansModels, StatisticalCarcinogensDustEnvironmental Pollutants6): exposomeEnvironmental exposureMixture analysisNon-Hodgkin lymphomaSpatial analysis

Identifiers

PMID36805898
PMCPMC10031495
OpenAlexW4321350780

What OpenQuestion holds

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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.