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Record W2803492840 · doi:10.1038/s41416-018-0108-8

Mendelian randomisation study of age at menarche and age at menopause and the risk of colorectal cancer

2018· article· en· W2803492840 on OpenAlexafffund
Sonja Neumeyer, Barbara L. Banbury, Volker Arndt, Sonja I. Berndt, Stéphane Bezieau, Stephanie A. Bien, Daniel D. Buchanan, Katja Butterbach, Bette J. Caan, Peter T. Campbell, Graham Casey, Andrew T. Chan, Stephen J. Chanock, James Y. Dai, Steven Gallinger, Edward L. Giovannucci, Graham G. Giles, William M. Grady, Jochen Hampe, Michael Hoffmeister, John L. Hopper, Li Hsu, Mark A. Jenkins, Amit D. Joshi, Susanna C. Larsson, Loı̈c Le Marchand, Annika Lindblom, Vı́ctor Moreno, Mathieu Lemire, Li Li, Yi Lin, Kenneth Offit, Polly A. Newcomb, Paul D Pharaoh, John D. Potter, Lihong Qi, Gad Rennert, Clemens Schafmayer, Robert E. Schoen, Martha L. Slattery, Mingyang Song, Cornelia M. Ulrich, Aung Ko Win, Emily White, Alicja Wolk, Michael O. Woods, Anna H. Wu, Stephen B. Gruber, Hermann Brenner, Ulrike Peters, Jenny Chang‐Claude

Bibliographic record

VenueBritish Journal of Cancer · 2018
Typearticle
Languageen
FieldMedicine
TopicHypothalamic control of reproductive hormones
Canadian institutionsMemorial University of NewfoundlandOntario Institute for Cancer ResearchLunenfeld-Tanenbaum Research InstituteMount Sinai Hospital
FundersNational Cancer InstituteNational Human Genome Research InstituteNational Heart, Lung, and Blood InstituteOntario Ministry of Research and InnovationCanadian Institutes of Health ResearchGroupement des Entreprises Françaises dans la lutte contre le CancerNational Institutes of HealthFlorida Department of HealthCentre Hospitalier Universitaire de NantesCancer Council VictoriaDeutsche KrebshilfeMinisterio de Economía y CompetitividadDeutsche ForschungsgemeinschaftBroad InstituteUniversity of South FloridaMemorial Sloan-Kettering Cancer CenterJohns Hopkins UniversityBundesministerium für Bildung und ForschungAssociation Anne de Bretagne GenetiqueNational Institute on AgingDivision of Cancer Prevention, National Cancer InstituteNational Institute of Diabetes and Digestive and Kidney DiseasesMoffitt Cancer CenterNational Health and Medical Research CouncilAmerican Cancer SocietyCenters for Disease Control and PreventionGénome QuébecConseil Régional des Pays de la LoireOntario Institute for Cancer ResearchU.S. Department of Health and Human Services
KeywordsMenarcheOdds ratioMedicineMenopauseConfidence intervalConfoundingInternal medicineBody mass indexOncologyColorectal cancerGynecologyDemographyCancer

Abstract

fetched live from OpenAlex

BACKGROUND: Substantial evidence supports an association between use of menopausal hormone therapy and decreased colorectal cancer (CRC) risk, indicating a role of exogenous sex hormones in CRC development. However, findings on endogenous oestrogen exposure and CRC are inconsistent. METHODS: We used a Mendelian randomisation approach to test for a causal effect of age at menarche and age at menopause as surrogates for endogenous oestrogen exposure on CRC risk. Weighted genetic risk scores based on 358 single-nucleotide polymorphisms associated with age at menarche and 51 single-nucleotide polymorphisms associated with age at menopause were used to estimate the association with CRC risk using logistic regression in 12,944 women diagnosed with CRC and 10,741 women without CRC from three consortia. Sensitivity analyses were conducted to address pleiotropy and possible confounding by body mass index. RESULTS: Genetic risk scores for age at menarche (odds ratio per year 0.98, 95% confidence interval: 0.95-1.02) and age at menopause (odds ratio 0.98, 95% confidence interval: 0.94-1.01) were not significantly associated with CRC risk. The sensitivity analyses yielded similar results. CONCLUSIONS: Our study does not support a causal relationship between genetic risk scores for age at menarche and age at menopause and CRC risk.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.578
Threshold uncertainty score0.862

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.285
Teacher spread0.271 · 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

Citations20
Published2018
Admission routes2
Has abstractyes

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