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Record W2942653600 · doi:10.1002/ijc.32386

Anthropometric and reproductive factors and risk of esophageal and gastric cancer by subtype and subsite: Results from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort

2019· article· en· W2942653600 on OpenAlexfundno aff
Harinakshi Sanikini, David C. Muller, Marisa K. Sophiea, Sabina Rinaldi, Antonio Agudo, Eric J. Duell, Elisabete Weiderpass, Kim Overvad, Anne Tjønneland, Jytte Halkjær, Marie‐Christine Boutron‐Ruault, Franck Carbonnel, Iris Cervenka, Heiner Boeing, Rudolf Kaaks, Tilman Kühn, Antonia Trichopoulou, Georgia Martimianaki, Anna Karakatsani, Valeria Pala, Domenico Palli, Amalia Mattiello, ­Rosario ­Tumino, Carlotta Sacerdote, Guri Skeie, Charlotta Rylander, María‐Dolores Chirlaque López, María‐José Sánchez, Eva Ardanáz, Sara Regnér, Tanja Stocks, Bas Bueno‐de‐Mesquita, Roel Vermeulen, Dagfinn Aune, Tammy Y. N. Tong, Nathalie Kliemann, Neil Murphy, Marc Chadeau‐Hyam, Marc J. Gunter, Amanda J. Cross

Bibliographic record

VenueInternational Journal of Cancer · 2019
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsnot available
FundersWorld Cancer Research FundMedical Research CouncilStand Up To CancerInstitut Gustave-RoussyMedical Research Council CanadaDeutsche KrebshilfeMutuelle Générale de l'Education NationaleAssociazione Italiana per la Ricerca sul CancroHealth Research Fund of Central Denmark RegionVetenskapsrådetCancerfondenWorld Health OrganizationEuropean CommissionCancer Research UKDeutsches KrebsforschungszentrumInstitut National de la Santé et de la Recherche MédicaleHellenic Health FoundationKræftens BekæmpelseLigue Contre le CancerNational Institute for Health and Care ResearchNational Research CouncilBundesministerium für Bildung und ForschungCentre International de Recherche sur le Cancer
KeywordsEuropean Prospective Investigation into Cancer and NutritionProspective cohort studyMedicineCancerAnthropometryEsophageal cancerCohortEPICInternal medicineRisk factorOncologyCohort study

Abstract

fetched live from OpenAlex

Obesity has been associated with upper gastrointestinal cancers; however, there are limited prospective data on associations by subtype/subsite. Obesity can impact hormonal factors, which have been hypothesized to play a role in these cancers. We investigated anthropometric and reproductive factors in relation to esophageal and gastric cancer by subtype and subsite for 476,160 participants from the European Prospective Investigation into Cancer and Nutrition cohort. Multivariable hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox models. During a mean follow‐up of 14 years, 220 esophageal adenocarcinomas (EA), 195 esophageal squamous cell carcinomas, 243 gastric cardia (GC) and 373 gastric noncardia (GNC) cancers were diagnosed. Body mass index (BMI) was associated with EA in men (BMI ≥30 vs. 18.5–25 kg/m2: HR = 1.94, 95% CI: 1.25–3.03) and women (HR = 2.66, 95% CI: 1.15–6.19); however, adjustment for waist‐to‐hip ratio (WHR) attenuated these associations. After mutual adjustment for BMI and HC, respectively, WHR and waist circumference (WC) were associated with EA in men (HR = 3.47, 95% CI: 1.99–6.06 for WHR >0.96 vs. <0.91; HR = 2.67, 95% CI: 1.52–4.72 for WC >98 vs. <90 cm) and women (HR = 4.40, 95% CI: 1.35–14.33 for WHR >0.82 vs. <0.76; HR = 5.67, 95% CI: 1.76–18.26 for WC >84 vs. <74 cm). WHR was also positively associated with GC in women, and WC was positively associated with GC in men. Inverse associations were observed between parity and EA (HR = 0.38, 95% CI: 0.14–0.99; >2 vs. 0) and age at first pregnancy and GNC (HR = 0.54, 95% CI: 0.32–0.91; >26 vs. <22 years); whereas bilateral ovariectomy was positively associated with GNC (HR = 1.87, 95% CI: 1.04–3.36). These findings support a role for hormonal pathways in upper gastrointestinal cancers.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.290
Teacher spread0.279 · 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 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

Citations36
Published2019
Admission routes1
Has abstractyes

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