Evidence map›Paper›PMID 40166649›Full record

ReviewFrontiers in epidemiology2025

Challenges in defining thresholds for health effects: some considerations for asbestos and silica.

Julie E Goodman, Lorenz R Rhomberg, Samuel M Cohen, Kenneth A Mundt, Bruce Case, Igor Burstyn, Michael J Becich, Graham Gibbs

Abstract readReview
In one paragraph

Review in Frontiers in epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

8 authors.

Julie E GoodmanGradient, Boston, MA, United States.
Lorenz R RhombergGradient, Boston, MA, United States.
Samuel M CohenHavlik-Wall Professor of Oncology, Department of Pathology, Microbiology, and Immunology, and the Buffett Cancer Center, University of Nebraska Medical Center, Omaha, NE, United States.
Kenneth A MundtUniversity of Massachusetts, Amherst, MA, United States.
Bruce CaseMcGill University, Montreal, QC, Canada.
Igor BurstynDrexel University, Philadelphia, PA, United States.
Michael J BecichUniversity of Pittsburgh School of Medicine, Pittsburgh, PA, United States.
Graham GibbsPrivate Consultant in Epidemiology and Occupational Health, Eastbourne, United Kingdom.

Funding

The Institute for Translational MedicineUL1TR002389 · NCATS · UNIVERSITY OF CHICAGO · PI Joshua J Jacobs, DAVID O MELTZER · 2017 to 2026
$71.6M
Northwestern University Clinical and Translational Science Institute (NUCATS)UL1TR001422 · NCATS · NORTHWESTERN UNIVERSITY AT CHICAGO · PI D'AQUILA, RICHARD · 2015 to 2023
$56.8M
NCATS NIH HHS UL1 TR001422NCATS NIH HHS UL1 TR002389NIOSH CDC HHS U24 OH009077
6 · The paper itself

Abstract

This paper summarizes several presentations in the Thresholds in Epidemiology and Risk Assessment session at the Monticello III conference. These presentations described evidence regarding thresholds for particles, including asbestos and silica, and cancer (e.g., mesothelioma) and noncancer (e.g., silicosis) endpoints. In the case of exposure to various types of particles and malignancy, it is clear that even though a linear non-threshold model has often been assumed, experimental and theoretical support for thresholds exist (e.g., through particle clearance, repair mechanisms, and various other aspects of the carcinogenic process). For mesothelioma and exposure to elongate mineral particles (EMPs), there remains controversy concerning the epidemiological demonstration of thresholds. However, using data from the Québec mining cohort studies, it was shown that a "practical" threshold exists for chrysotile exposure and mesothelioma. It was also noted that, in such evaluations, measurement error in diagnosis and exposure assessment needs to be incorporated into risk analyses. Researchers were also encouraged to use biobanks that collect specimens and data on mesothelioma to more precisely define cases of mesothelioma and possible variants for cases of all ages, and trends that may help define background rates and distinguish those mesotheliomas related to EMP exposures from those that are not, as well as other factors that support or define thresholds. New statistical approaches have been developed for identifying and quantifying exposure thresholds, an example of which is described for respirable crystalline silica (RCS) exposure and silicosis risk. Finally, the application of Artificial Intelligence (AI) to considering the multiple factors influencing risk and thresholds may prove useful.

Indexed as

asbestoselongate mineral particlesmesotheliomasilicasilicosisthresholds

Identifiers

PMID40166649
PMCPMC11955591

What OpenQuestion holds

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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.