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Record W2110770087 · doi:10.1002/ijc.21577

Diet and body mass, and oral and oropharyngeal squamous cell carcinomas: Analysis from the IARC multinational case–control study

2005· article· en· W2110770087 on OpenAlexfundno aff
Aimée R. Kreimer, G. Randi, Rolando Herrero, Xavier Castellsagué, Carlo La Vecchia, Silvia Franceschi

Bibliographic record

VenueInternational Journal of Cancer · 2005
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsnot available
FundersNational Cancer InstitutePan American Health OrganizationMcGill University
KeywordsMedicineOdds ratioConfidence intervalConfoundingBody mass indexCancerEnvironmental healthCase-control studyTobacco smokeBasal cellPhysiologyInternal medicine

Abstract

fetched live from OpenAlex

Tobacco and alcohol use are the main risk factors for oral and oropharyngeal cancers, yet, dietary habits may also be of importance. Data from a series of case-control studies conducted in 9 countries worldwide (1,670 cases and 1,732 controls) were used to investigate the role of several food groups and body mass index (BMI). Low BMI significantly increased the odds ratio (OR) of cancer more than 2-fold among ever- and never-tobacco users and ever- and never-alcohol drinkers. After adjustment for potential confounders, high intake of fruits and vegetables significantly reduced the OR of cancer compared to low intake among ever-tobacco users (OR 0.4, 95% confidence interval [CI] 0.3-0.6), although not among never-tobacco users (OR 1.1, 95% CI 0.6-2.0). Similarly, the protective effect of high fruit and vegetable consumption was present among ever-drinkers (OR 0.4, 95% CI 0.3-0.6), but not among never-drinkers (OR 1.0, 95% CI 0.6-1.6). In conclusion, low BMI increases the risk of oral cancer, and vegetables and fruits may modulate the carcinogenic effects of tobacco and alcohol.

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)0.000
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 score0.020
Threshold uncertainty score0.327

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 head0.014
GPT teacher head0.319
Teacher spread0.305 · 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 designObservational
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

Citations97
Published2005
Admission routes1
Has abstractyes

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