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Record W2499651799 · doi:10.3945/ajcn.116.130963

Sweet-beverage consumption and risk of pancreatic cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC)

2016· article· en· W2499651799 on OpenAlexaff
Eva María Navarrete‐Muñoz, Petra A. Wark, Dora Romaguera, Nirmala Bhoo‐Pathy, Dominique S. Michaud, Esther Molina‐Montes, Anne Tjønneland, Anja Olsen, Kim Overvad, Marie‐Christine Boutron‐Ruault, Françoise Clavel‐Chapelon, Guy Fagherazzi, Verena Katzke, Tilman Kühn, Annika Steffen, Antonia Trichopoulou, Eleni Klinaki, Eleni‐Maria Papatesta, Giovanna Masala, Vittorio Krogh, ­Rosario ­Tumino, Alessio Naccarati, Amalia Mattiello, Petra H. Peeters, Charlotta Rylander, Christine L Parr, Guri Skeie, Elisabete Weiderpass, J. Ramón Quirós, Eric J. Duell, Miren Dorronsoro, José María Huerta, Eva Ardanáz, Kay‐Tee Khaw, Ruth C. Travis, Tim Key, Magdalena Stępień, Heinz Freisling, Elio Ríboli, H. Bas Bueno-de-Mesquita

Bibliographic record

VenueAmerican Journal of Clinical Nutrition · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiological Research and Disease Studies
Canadian institutionsInstitute of Cancer Research
FundersMedical Research CouncilNational Institute for Health and Care ResearchCancer Research UKWorld Health Organization
KeywordsEuropean Prospective Investigation into Cancer and NutritionEPICCancerPancreatic cancerMedicineProspective cohort studyConsumption (sociology)Environmental healthInternal medicineOncologyArt

Abstract

fetched live from OpenAlex

BACKGROUND: The consumption of sweet beverages has been associated with greater risk of type 2 diabetes and obesity, which may be involved in the development of pancreatic cancer. Therefore, it has been hypothesized that sweet beverages may increase pancreatic cancer risk as well. OBJECTIVE: We examined the association between sweet-beverage consumption (including total, sugar-sweetened, and artificially sweetened soft drink and juice and nectar consumption) and pancreatic cancer risk. DESIGN: The study was conducted within the European Prospective Investigation into Cancer and Nutrition cohort. A total of 477,199 participants (70.2% women) with a mean age of 51 y at baseline were included, and 865 exocrine pancreatic cancers were diagnosed after a median follow-up of 11.60 y (IQR: 10.10-12.60 y). Sweet-beverage consumption was assessed with the use of validated dietary questionnaires at baseline. HRs and 95% CIs were obtained with the use of multivariable Cox regression models that were stratified by age, sex, and center and adjusted for educational level, physical activity, smoking status, and alcohol consumption. Associations with total soft-drink consumption were adjusted for juice and nectar consumption and vice versa. RESULTS: Total soft-drink consumption (HR per 100 g/d: 1.03; 95% CI: 0.99, 1.07), sugar-sweetened soft-drink consumption (HR per 100 g/d: 1.02; 95% CI: 0.97, 1.08), and artificially sweetened soft-drink consumption (HR per 100 g/d: 1.04; 95% CI: 0.98, 1.10) were not associated with pancreatic cancer risk. Juice and nectar consumption was inversely associated with pancreatic cancer risk (HR per 100 g/d: 0.91; 95% CI: 0.84, 0.99); this association remained statistically significant after adjustment for body size, type 2 diabetes, and energy intake. CONCLUSIONS: Soft-drink consumption does not seem to be associated with pancreatic cancer risk. Juice and nectar consumption might be associated with a modest decreased pancreatic cancer risk. Additional studies with specific information on juice and nectar subtypes are warranted to clarify these results.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.030
GPT teacher head0.368
Teacher spread0.338 · 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

Citations41
Published2016
Admission routes1
Has abstractyes

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