Evidence map›Paper›PMID 42225416›Full record

ArticleOccupational and environmental medicine2026

Lung cancer risk prediction models and asbestos exposure: a validation study on the Western Australia Asbestos Review Program.

Chellan Kumarasamy, Kim Betts, Richard Norman, Kirsten Bennett, Peter Franklin, Martin Tammemägi, Fraser Brims

Abstract readValidation Study
In one paragraph

Article in Occupational and environmental medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Chellan KumarasamyCurtin Medical School, Curtin University, Perth, Western Australia, Australia.ORCID 0000-0001-7775-3578
Kim BettsCurtin School of Population Health, Curtin University, Perth, Western Australia, Australia.
Richard NormanCurtin School of Population Health, Curtin University, Perth, Western Australia, Australia.
Kirsten BennettCurtin Medical School, Curtin University, Perth, Western Australia, Australia.
Peter FranklinSchool of Population and Global Health, The University of Western Australia, Perth, Western Australia, Australia.ORCID 0000-0002-9983-1212
Martin TammemägiBC Cancer Research Centre, Integrative Oncology, The University of British Columbia Faculty of Medicine, Vancouver, British Columbia, Canada.
Fraser BrimsCurtin Medical School, Curtin University, Perth, Western Australia, Australia fraser.brims@curtin.edu.au.ORCID 0000-0002-6725-7535

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesAsbestos exposure raises the lung cancer risk and has supra-additive synergy alongside tobacco exposure. Lung cancer screening (LCS) is effective when high-risk populations are targeted. This study examined the utility of various LCS eligibility and risk prediction models in an asbestos-exposed population.

methodsThe Western Australia Asbestos Review Program (ARP) consists of individuals with known exposure to asbestos. All participants underwent annual review with low-dose CT screening. The performance of the Prostate, Lung, Colorectal and Ovarian (PLCO)

resultsThe cohort consisted of 2126 participants of which 85.4% were male with a median (IQR) age of 70 (63-75) years old. Former smokers comprised 55.1% (n=1172) and never smokers 36.2% (n=769) of the cohort. Median smoking and cessation duration were 24 years (IQR: 13-72) and 32 years (IQR: 22-41), respectively. Lung cancer was diagnosed in 51 (2.4%) participants.When applying the risk models to the ARP cohort, the area under the curve for all models was modest, ranging from 0.602 to 0.675. All models underestimated risk in this cohort during calibration assessment, with the exception of the LLP V.2, which overestimated risk.

conclusionsIn an asbestos exposed population, current LCS eligibility criteria and risk models mostly underestimate the risk of lung cancer, reflecting the need for improved risk prediction models that adequately account for asbestos exposure.

Indexed as

AsbestosLung NeoplasmsOccupational ExposureAgedEarly Detection of CancerFemaleHumansMaleMiddle AgedPrediction AlgorithmsRisk AssessmentRisk FactorsTomography, X-Ray ComputedWestern AustraliaAsbestosAsbestosCancerLung Diseases, InterstitialOccupational HealthPublic Health Surveillance

Identifiers

PMID42225416
PMCPMC13311979

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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.