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Record W4224230289 · doi:10.1093/jnci/djac061

Body Size at Different Ages and Risk of 6 Cancers: A Mendelian Randomization and Prospective Cohort Study

2022· article· en· W4224230289 on OpenAlexafffund
Daniela Mariosa, Karl Smith-Byrne, Tom G. Richardson, Pietro Ferrari, Marc J. Gunter, Nikos Papadimitriou, Neil Murphy, Sofia Christakoudi, Konstantinos K. Tsilidis, Elio Ríboli, David C. Muller, Mark P. Purdue, Stephen J. Chanock, Christopher I. Amos, Tracy A. O’Mara, Pilar Amiano, Fabrizio Pasanisi, Miguel Rodríguez‐Barranco, Vittorio Krogh, Anne Tjønneland, Jytte Halkjær, Aurora Perez‐Cornago, María‐Dolores Chirlaque, Guri Skeie, Charlotta Rylander, Kristin Benjaminsen Borch, Dagfinn Aune, Alicia K. Heath, Heather Ward, Matthias B. Schulze, Catalina Bonet, Elisabete Weiderpass, George Davey Smith, Paul Brennan, Mattias Johansson

Bibliographic record

VenueJNCI Journal of the National Cancer Institute · 2022
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsSinai Health SystemLunenfeld-Tanenbaum Research InstitutePublic Health OntarioUniversity of Toronto
FundersNational Cancer InstituteRijksinstituut voor Volksgezondheid en MilieuNational Health and Medical Research CouncilWorld Cancer Research FundMedical Research CouncilWereld Kanker Onderzoek FondsInstitut Gustave-RoussyDeutsche KrebshilfeVetenskapsrådetCanadian Institutes of Health ResearchCancerfondenInstitut National de la Santé et de la Recherche MédicaleWellcome TrustCancer Research UKWorld Health OrganizationEuropean CommissionGenome CanadaAssociazione Italiana per la Ricerca sul CancroImperial College LondonNational Institutes of HealthOvarian Cancer Research FundWorld Cancer Research Fund InternationalLigue Contre le CancerDeutsches KrebsforschungszentrumNIHR Imperial Biomedical Research CentreCentre International de Recherche sur le CancerBundesministerium für Bildung und ForschungNational Institute for Health and Care Research
KeywordsMendelian randomizationProspective cohort studyMedicineMendelian inheritanceCohortCohort studyOncologyRandomizationDemographyInternal medicineGeneticsBiologyClinical trialGeneGenetic variantsGenotype

Abstract

fetched live from OpenAlex

It is unclear if body weight in early life affects cancer risk independently of adult body weight. To investigate this question for 6 obesity-related cancers, we performed univariable and multivariable analyses using 1) Mendelian randomization (MR) analysis and 2) longitudinal analyses in prospective cohorts. Both the MR and longitudinal analyses indicated that larger early life body size was associated with higher risk of endometrial (odds ratioMR = 1.61, 95% confidence interval = 1.23 to 2.11) and kidney (odds ratioMR = 1.40, 95% confidence interval = 1.09 to 1.80) cancer. These associations were attenuated after accounting for adult body size in both the MR and cohort analyses. Early life body mass index (BMI) was not consistently associated with the other investigated cancers. The lack of clear independent risk associations suggests that early life BMI influences endometrial and kidney cancer risk mainly through pathways that are common with adult BMI.

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)0.008
metaresearch head score (Gemma)0.011
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 score0.008
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.019
GPT teacher head0.313
Teacher spread0.293 · 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

Citations29
Published2022
Admission routes2
Has abstractyes

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