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Record W2893214782 · doi:10.1097/cej.0000000000000463

Occupational and environmental exposure to polychlorinated biphenyls and risk of non-Hodgkin lymphoma: a systematic review and meta-analysis of epidemiology studies

2018· review· en· W2893214782 on OpenAlexfundno aff
Simona Catalani, Francesca Donato, Cesare Tomasi, Enrico Pira, Pietro Apostoli, Paolo Boffetta

Bibliographic record

VenueEuropean Journal of Cancer Prevention · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCarcinogens and Genotoxicity Assessment
Canadian institutionsnot available
FundersBC Cancer Agency
KeywordsMeta-analysisConfoundingRelative riskMedicineConfidence intervalOccupational exposureEpidemiologyEnvironmental healthPublication biasInternal medicine

Abstract

fetched live from OpenAlex

We carryied out a meta-analysis of studies on exposure to polychlorinated biphenyls (PCBs) and risk of non-Hodgkin lymphoma (NHL). Through a systematic search of the literature, we identified relative risks (RRs) for PCB exposure and NHL risk in 30 populations (10 occupational exposure, seven high environmental exposure, 13 without special exposure). We performed random effects meta-analyses for exposure to all PCBs, specific PCB congeners and risk of all NHL and NHL subtypes. The meta-RR for studies of occupational exposure, high environmental exposure, and no special exposure were 0.94 [95% confidence interval (CI): 0.84-1.03], 1.05 (95% CI: 0.94-1.16), and 1.03 (95% CI: 0.72-1.34), respectively, and the cumulative meta-RR was 0.96 (95% CI: 0.85-1.07). No positive associations were found for exposure to specific congeners, nor for NHL subtypes. The meta-RR for an increase of 100 ppb serum or fat PCB level was 1.02 (95% CI: 1.00-1.04). There was weak indication of publication bias. Our meta-analysis found no association between PCB exposure and NHL risk, in particular in studies of occupational exposures. We detected a weak dose-response relation; the possibility of residual confounding and other sources of bias cannot be ruled out. PCBs are not likely to cause NHL in humans.

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)0.003
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: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.430
Threshold uncertainty score0.649

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
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 head0.077
GPT teacher head0.393
Teacher spread0.316 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations13
Published2018
Admission routes1
Has abstractyes

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