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Record W3129088330 · doi:10.1515/reveh-2020-0109

Exposure to cadmium and head and neck cancers: a meta-analysis of observational studies

2021· review· en· W3129088330 on OpenAlexaboutno aff
Maysam Rezapour, Habib Allah Rezapour, Maryam Chegeni‬‬, Narges Khanjani

Bibliographic record

VenueReviews on Environmental Health · 2021
Typereview
Languageen
FieldEnvironmental Science
TopicHeavy Metal Exposure and Toxicity
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisCadmiumMedicineLarynxPharynxObservational studyInternal medicineHead and neck cancerNasopharyngeal cancerNasopharyngeal carcinomaCADMIUM EXPOSURECancerGastroenterologyOncologySurgeryToxicityRadiation therapyChemistry

Abstract

fetched live from OpenAlex

Cadmium (Cd) is a widespread environmental pollutant. A number of observational studies have reported that Cd might be a cause of nasopharyngeal (NPC), pharyngeal (PC), or laryngeal cancers (LC). In this study evidence about the relation of Cd and NPC, PC, and LC has been summarized. A literature review was conducted until 20 June 2020 in PubMed, Ovid, Scopus, Web of Science and Google scholar databases to investigate the epidemiologic evidence for the relation between cadmium exposure and cancers of the nasopharynx, pharynx, and larynx. Ten articles were selected after careful screening of retrieved studies. All of these studies obtained a Newcastle-Ottawa Scale (NOS) quality score from 6 to 8. Due to high heterogeneity, in all analyses, random effect was used. The pooled results showed that cadmium levels in NPC (standard mean difference (SMD=0.55; 95% CI=0.20, 0.89; p=0.002) and PC (SMD=9.79; 95% CI=0.62, 18.96; p=0.036) patients/tissues were significantly higher than their controls. But cadmium levels were not significantly different between LC cases/tissues and their controls. (SMD=-0.05; 95% CI=-0.99, 0.89; p=0.921). Exposure to cadmium is likely to cause nasopharyngeal and pharyngeal cancer.

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)0.014
metaresearch head score (Gemma)0.028
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: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.028
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0110.047
Bibliometrics0.0050.007
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0020.002
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 head0.391
GPT teacher head0.450
Teacher spread0.059 · 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
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

Citations14
Published2021
Admission routes1
Has abstractyes

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