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Record W2144553478 · doi:10.1093/jnci/djs411

Myelodysplastic Syndrome and Benzene Exposure Among Petroleum Workers: An International Pooled Analysis

2012· article· en· W2144553478 on OpenAlexaboutno aff
A. Robert Schnatter, Deborah C. Glass, Gong Tang, Robert Irons, Lesley Rushton

Bibliographic record

VenueJNCI Journal of the National Cancer Institute · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCarcinogens and Genotoxicity Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOdds ratioMyeloid leukemiaConfidence intervalLeukemiaInternal medicineMyelodysplastic syndromesCancerBone marrow

Abstract

fetched live from OpenAlex

BACKGROUND: Benzene at high concentrations is known to cause acute myeloid leukemia (AML), but its relationship with other lymphohematopoietic (LH) cancers remains uncertain, particularly at low concentrations. In this pooled analysis, we examined the risk of five LH cancers relative to lower levels of benzene exposure in petroleum workers. METHODS: We updated three nested case-control studies from Australia, Canada, and the United Kingdom with new incident LH cancers among petroleum distribution workers through December 31, 2006, and pooled 370 potential case subjects and 1587 matched LH cancer-free control subjects. Quantitative benzene exposure in parts per million (ppm) was blindly reconstructed using historical monitoring data, and exposure certainty was scored as high, medium, or low. Two hematopathologists assigned diagnoses and scored the certainty of diagnosis as high, medium, or low. Dose-response relationships were examined for five LH cancers, including the three most common leukemia cell-types (AML, chronic myeloid leukemia [CML], and chronic lymphoid leukemia [CLL]) and two myeloid tumors (myelodysplastic syndrome [MDS] and myeloproliferative disease [MPD]). Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using conditional logistic regression, controlling for age, sex, and time period. RESULTS: Cumulative benzene exposure showed a monotonic dose-response relationship with MDS (highest vs lowest tertile, >2.93 vs ≤0.348 ppm-years, OR = 4.33, 95% CI = 1.31 to 14.3). For peak benezene exposures (>3 ppm), the risk of MDS was increased in high and medium certainty diagnoses (peak exposure vs no peak exposure, OR = 6.32, 95% CI = 1.32 to 30.2) and in workers having the highest exposure certainty (peak exposure vs no peak exposure, OR = 5.74, 95% CI = 1.05 to 31.2). There was little evidence of dose-response relationships for AML, CLL, CML, or MPD. CONCLUSIONS: Relatively low-level exposure to benzene experienced by petroleum distribution workers was associated with an increased risk of MDS, but not AML, suggesting that MDS may be the more relevant health risk for lower exposures.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.007
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.301
Teacher spread0.282 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
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

Citations198
Published2012
Admission routes1
Has abstractyes

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