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Record W2130440200 · doi:10.5271/sjweh.1145

Incidence trends and gender differences in malignant mesothelioma in New South Wales, Australia

2007· article· en· W2130440200 on OpenAlexaff
Rebecca Hyland, Sandra Ware, Anthony Johnson, Deborah Yates

Bibliographic record

VenueScandinavian Journal of Work Environment & Health · 2007
Typearticle
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsWorkers Compensation Board of British Columbia
Fundersnot available
KeywordsMesotheliomaMedicineCancer registryAsbestosIncidence (geometry)Latency stageEpidemiologyCancerDemographyInternal medicinePathology

Abstract

fetched live from OpenAlex

OBJECTIVES: Features of malignant mesothelioma reportedly differ between men and women, including occupational asbestos exposure, histological subtype, and median survival. In this study, incidence trends and clinical features for malignant mesothelioma were compared between genders in New South Wales (NSW), where notification of malignant mesothelioma to the Central Cancer Registry is a statutory requirement. METHODS: Notifications to the Central Cancer Registry were compared with those to the registry of the NSW Workers' Compensation (Dust Diseases) Board. The latter includes occupational and clinical data. RESULTS: Of the 3090 cases of malignant mesothelioma reported to the Central Cancer Registry between 1972 and 2004, 456 (15%) were female. Altogether 1995 malignant mesotheliomas were compensated between 1969 and 2004, of which 105 (5%) occurred among women. The incidence increased for both genders by approximately 15-fold. Median survival was similar for the men and women for all of the cases (7 versus 6 months), but was better among the women who received compensation (8.5 versus 10.4 months, P<0.0001). The mean disease latency (42.8 years) increased over the study period (P<0.001). CONCLUSIONS: In New South Wales over the last 30 years, the total number of malignant mesotheliomas and the number of compensated cases of malignant mesothelioma have risen for both genders. The mean latency is increasing, and increasing numbers of "nonoccupational" cases are being reported. Survival remains poor.

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)0.001
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 score0.017
Threshold uncertainty score0.562

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.050
GPT teacher head0.310
Teacher spread0.259 · 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

Citations60
Published2007
Admission routes1
Has abstractyes

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