Evidence map›Paper›PMID 39833723›Full record

ArticleBMC cancer2025

Enhanced spatial analysis assessing the association between PFAS-contaminated water and cancer incidence: rationale, study design, and methods.

Resa M Jones, Erin R Kulick, Ryan Snead, Robin Taylor Wilson, John Hughes, Ted Lillys

Abstract read
In one paragraph

Article in BMC cancer, 2025. 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.

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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.

Resa M JonesDepartment of Epidemiology and Biostatistics, College of Public Health, Temple University, 1301 Cecil B. Moore Ave. Ritter Annex, 9th Floor, Rm 917, Philadelphia, PA, 19122, United States. resa.jones@temple.edu.ORCID http://orcid.org/0000-0002-0080-4047
Erin R KulickDepartment of Epidemiology and Biostatistics, College of Public Health, Temple University, 1301 Cecil B. Moore Ave. Ritter Annex, 9th Floor, Rm 917, Philadelphia, PA, 19122, United States.ORCID http://orcid.org/0000-0001-8650-5357
Ryan SneadDepartment of Epidemiology and Biostatistics, College of Public Health, Temple University, 1301 Cecil B. Moore Ave. Ritter Annex, 9th Floor, Rm 917, Philadelphia, PA, 19122, United States.ORCID http://orcid.org/0000-0003-2876-7003
Robin Taylor WilsonDepartment of Epidemiology and Biostatistics, College of Public Health, Temple University, 1301 Cecil B. Moore Ave. Ritter Annex, 9th Floor, Rm 917, Philadelphia, PA, 19122, United States.ORCID http://orcid.org/0000-0002-5739-558X
John HughesDepartment of Community and Population Health, College of Health, Lehigh University, Bethlehem, Pennsylvania, United States.ORCID http://orcid.org/0000-0003-1538-2569
Ted LillysResearch Triangle Institute, International, Cary, North Carolina, United States.ORCID http://orcid.org/0000-0003-0163-813X

Funding

ATSDR CDC HHS U01 TS000301Centers for Disease Control and Prevention and Agency for Toxic Substances and Disease Registry U01TS000301Commonwealth of Pennsylvania, Department of Health and Human Services 271138
6 · The paper itself

Abstract

backgroundCancer is a complex set of diseases, and many have decades-long lag times between possible exposure and diagnosis. Environmental exposures, such as per- and poly-fluoroalkyl substances (PFAS) and area-level risk factors (e.g., socioeconomic variables), vary for people over time and space. Evidence suggests PFAS exposure is associated with several cancers; however, studies to date have various limitations. Few studies have used rigorous spatiotemporal approaches, and, to our knowledge, none have assessed cumulative exposures given residential histories or incorporated chemical mixture modeling. Thus, spatiotemporal analysis using advanced statistical approaches, accounting for spatially structured and unstructured heterogeneity in risk, can be a highly informative strategy for addressing the potential health effects of PFAS exposure.

methodsUsing population-based incident cancer cases and cancer-free controls in a 12-county area of southeastern Pennsylvania, we will apply Bayesian spatiotemporal analysis methods using historically reconstructed PFAS-contaminated water exposure given residential histories, and other potential cancer determinants over time. Bayesian group index models enable assessment of various mixtures of highly correlated PFAS chemical exposures incorporating mobility/residential history, and contextual factors to determine the association of PFAS-related exposures and cancer incidence. DISCUSSION: The purpose of this paper is to describe the Enhanced PFAS Spatial Analysis study rationale, study design, and methods.

Indexed as

Environmental ExposureFluorocarbonsNeoplasmsWater Pollutants, ChemicalBayes TheoremCase-Control StudiesFemaleHumansIncidenceMalePennsylvaniaResearch DesignRisk FactorsSpatial AnalysisSpatio-Temporal AnalysisFluorocarbonsWater Pollutants, ChemicalBayesianCancer incidenceDrinking waterIndex modelPFASResidential historySpatiotemporal

Identifiers

PMID39833723
PMCPMC11744822

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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.