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Record W2110867120 · doi:10.1093/annhyg/meh023

The Interaction of Asbestos and Smoking in Lung Cancer: A Modified Measure of Effect

2004· article· en· W2110867120 on OpenAlexaff
George Packer Berry, F. D. K. Liddell

Bibliographic record

VenueThe Annals of Occupational Hygiene · 2004
Typearticle
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsMcGill University
Fundersnot available
KeywordsAsbestosRelative riskMedicineLung cancerConfidence intervalAttributable riskAbsolute risk reductionPopulationEpidemiologyCohort studyCohortStandardized mortality ratioDemographyEnvironmental healthOncologyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: The ratio of the relative risk of lung cancer due to asbestos exposure in non-smokers to that in smokers has been termed the relative asbestos effect (RAE). In a review, Liddell [Liddell FDK (2001) Ann Occup Hyg; 45: 341-56] estimated that the RAE was approximately 2. This measure is satisfactory when there is an appreciable relative risk due to asbestos but does not generalize to lower levels of exposure. A modified measure is proposed to overcome this difficulty. The modified measure, RAEm, is defined as the ratio of the excess relative risk (RR - 1) in non-smokers to that in smokers. METHODS: The cohort studies combined in Liddell's 2001 analysis have been used to give a combined estimate of the modified measure. RESULTS: The combined value of RAEm is 3.19 with 95% confidence interval 1.67-6.13. CONCLUSION: The excess relative risk of lung cancer from asbestos exposure is about three times higher in non-smokers than in smokers. The modified measure has been placed within a more versatile model of interaction. If interaction is present the relative risk from asbestos exposure changes only slightly between light and heavy smokers, but is higher in very light smokers and non-smokers. The relative risk estimated from epidemiological studies of a mixed population of non-smokers and smokers applies to smokers.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.170

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.054
GPT teacher head0.367
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations50
Published2004
Admission routes1
Has abstractyes

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