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Record W4393090005 · doi:10.1158/1538-7445.am2024-831

Abstract 831: Occupational-related exposure to benzene and risk of breast cancer: Systematic review and meta-analysis

2024· article· en· W4393090005 on OpenAlexaboutno aff
Vincent DeStefano, Darshi Shah, Veer Shah, Monireh Sadat Seyyedsalehi, Mattia Bonetti, Paolo Boffetta

Bibliographic record

VenueCancer Research · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCarcinogens and Genotoxicity Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisBreast cancerMedicineOncologyCancerOccupational exposureEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

Abstract Purpose: Benzene is a recognized carcinogen as evidenced by its association with leukemia; however, its association with breast cancer is not well established. Hence, a meta-analysis of cohort and case-control studies was performed to determine the association between benzene exposure and the risk of breast cancer. Methods: A systematic literature review was conducted and 7221 publications were identified, from which 21 cohort and case-control studies were retained, and evaluated using meta-analyses (fixed effects model). PECOS criteria and STROBE guidelines were followed, and the study protocol was registered in the PROSPERO database (Registration No. 379720). Study quality was assessed using a modified Newcastle-Ottawa scale (NOS). Results: The summary relative risk (RR) for ever-benzene exposure was 1.08 (95% CI=1.02-1.14, I2=43.6%, n=21); corresponding RR for cancer incidence and mortality were 1.08 (95% CI=1.02-1.14, I2=58.6%, n=15) and 1.09 (95% CI=0.87-1.38, I2<0.001%, n=9), respectively. These main results were confirmed in sub-analyses by geographical region, industry type, publication year, and levels of exposure. No heterogeneity was detected amongst geographical regions (p-het=0.19), industry of employment (p-het=0.05) or and duration of the dose (low, high; p-het=0.64). Studies published before 2003 reported a summary RR of 1.24 (95% CI=1.13-1.37), compared to a summary RR of 1.02 (95% CI=0.95-1.08) for studies published later (p-het=0.001). Heterogeneity was observed when evaluating studies at and above, or below the NOS mean (p-het=0.00), with a summary RR of 1.25 (95% CI=1.13-1.28, I2<0.001%, n=9) for studies below the median NOS score. Sub-group analysis of study design demonstrated heterogeneous results (p-het=0.001) with a summary RR of 1.19 (95% CI=1.10-1.29, I2<0.001%, n=16) for cohort studies while compared to the findings of case-control studies. Publication bias was detected (p=0.04). Conclusions: Our meta-analysis identified an association between occupational benzene exposure and risk of breast cancer. The association was restricted to studies published before 2003, below the median NOS score, and cohort studies. Residual confounding variables cannot be excluded, which, together with potential bias, prevents conclusions of causality. Citation Format: Vincent DeStefano, Darshi Shah, Veer Shah, Monireh Sadat Seyyedsalehi, Mattia Bonetti, Paolo Boffetta. Occupational-related exposure to benzene and risk of breast cancer: Systematic review and meta-analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 831.

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)0.012
metaresearch head score (Gemma)0.032
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: none
Teacher disagreement score0.015
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.032
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0150.028
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.059
GPT teacher head0.411
Teacher spread0.352 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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