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Record W4324138251 · doi:10.1136/oem-2023-epicoh.23

O-135 Exploring the etiology of rare cancers using a large multi-ore mining cohort

2023· article· en· W4324138251 on OpenAlex
Paul A Demers, Colin Berriault, Nancy Lightfoot, Victoria H Arrandale

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAbstracts · 2023
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsOccupational Cancer Research CentrePublic Health OntarioLaurentian UniversityUniversity of Toronto
Fundersnot available
KeywordsMedicineCohortCancerCancer registryPoisson regressionPopulationInternal medicineRecord linkageIncidence (geometry)Environmental health

Abstract

fetched live from OpenAlex

<h3>Introduction</h3> Cohort studies may be limited in their ability to investigate rare cancers because of their size, length of follow-up, or access to cancer registry data. This study examines exposure patterns for nasal, nasopharyngeal, laryngeal, salivary gland, and bone cancer using a large multi-ore mining cohort. <h3>Materials &amp; Methods</h3> From 1928–1988 underground miners in Ontario, a region where gold, uranium, nickel, and other ores are mined, were required to undergo an annual medical exam, and record their mining work history to receive certification. These data were used to create the Mining Master File (MMF) cohort. Cancers were identified through linkage with the Ontario Cancer Registry (1964–2017). Cancer risk among miners was compared to the general population using Standardized Incidence Ratios (SIR) and between groups of miners in the cohort using Poisson regression. <h3>Results</h3> The cohort consisted of 61,397 male miners. Nasal cancer was somewhat elevated (48 cases, SIR=1.44, 95% confidence Interval (CI)=1.06–1.91) but the observed excess was largely localized to miners who had the majority of employment in nickel mines (SIR=2.09, CI=1.37–3.06). Nasopharyngeal cancer was similarly elevated (44 cases, SIR=1.42, CI=1.03–1.91) but in contrast the excess risk was limited to gold mining (SIR=2.70, CI=1.57–4.33). A small elevation was observed for larynx cancer (307 cases, SIR=1.26, CI=1.12–1.40), but was not limited to one ore type. Bone cancer was clearly elevated (58 cases, SIR=1.91, CI=1.45–2.47), with ore-specific elevations seen among uranium (SIR=2.46, CI=1.22–4.40) followed by nickel mining (SIR=2.04, CI=1.29–3.06). Salivary gland was only slightly elevated (54 cases, SIR=1.09, CI=0.82–1.42), but the risk among uranium miners exposed to radon was high (SIR=2.97, CI=1.81–4.59) and increased monotonically with employment duration. <h3>Conclusion</h3> This analysis demonstrated the power of this cohort to identify associations for rare cancers. Although the association of nickel with nasal cancer was expected, some other associations were surprising and warrant further investigation.

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.

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 score0.081
Threshold uncertainty score0.239

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 head0.113
GPT teacher head0.344
Teacher spread0.231 · 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