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Record W2740624314 · doi:10.1136/oemed-2016-104173

The economic burden of lung cancer and mesothelioma due to occupational and para-occupational asbestos exposure

2017· article· en· W2740624314 on OpenAlexafffundabout
Emile Tompa, Christina Kalcevich, Chris McLeod, Martin Lebeau, Chaojie Song, Kim McLeod, Joanne Kim, Paul A. Demers

Bibliographic record

VenueOccupational and Environmental Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsOccupational Cancer Research CentreInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du TravailUniversity of British ColumbiaPublic Health OntarioMcMaster UniversityUniversity of TorontoInstitute for Work & Health
FundersCanadian Cancer Society Research Institute
KeywordsAsbestosMesotheliomaOccupational exposureLung cancerMedicineEnvironmental healthAsbestosisOccupational lung diseasePathologyLungInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: To estimate the economic burden of lung cancer and mesothelioma due to occupational and para-occupational asbestos exposure in Canada. METHODS: We estimate the lifetime cost of newly diagnosed lung cancer and mesothelioma cases associated with occupational and para-occupational asbestos exposure for calendar year 2011 based on the societal perspective. The key cost components considered are healthcare costs, productivity and output costs, and quality of life costs. RESULTS: There were 427 cases of newly diagnosed mesothelioma cases and 1904 lung cancer cases attributable to asbestos exposure in 2011 for a total of 2331 cases. Our estimate of the economic burden is $C831 million in direct and indirect costs for newly identified cases of mesothelioma and lung cancer and $C1.5 billion in quality of life costs based on a value of $C100 000 per quality-adjusted life year. This amounts to $C356 429 and $C652 369 per case, respectively. CONCLUSIONS: The economic burden of lung cancer and mesothelioma associated with occupational and para-occupational asbestos exposure is substantial. The estimate identified is for 2331 newly diagnosed, occupational and para-occupational exposure cases in 2011, so it is only a portion of the burden of existing cases in that year. Our findings provide important information for policy decision makers for priority setting, in particular the merits of banning the mining of asbestos and use of products containing asbestos in countries where they are still allowed and also the merits of asbestos removal in older buildings with asbestos insulation.

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 score0.016
Threshold uncertainty score0.686

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 studies0.0010.001
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 head0.016
GPT teacher head0.295
Teacher spread0.280 · 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

Citations53
Published2017
Admission routes3
Has abstractyes

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