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Record W2336946997 · doi:10.1097/mpa.0000000000000635

Menstrual and Reproductive Factors, Hormone Use, and Risk of Pancreatic Cancer

2016· article· en· W2336946997 on OpenAlexaff
Wei Zhang, Sara H. Olson, Yu‐Tang Gao, Herbert Yu, Peter Baghurst, Paige M. Bracci, H. Bas Bueno-de-Mesquita, Lenka Foretová, Steven Gallinger, Ivana Holcátová, Vladimí­r Janout, Bu‐Tian Ji, Robert C. Kurtz, Carlo La Vecchia, Παγώνα Λάγιου, Donghui Li, Anthony B. Miller, Diego Serraino, Witold Zatoński, Harvey A. Risch, Eric J. Duell

Bibliographic record

VenuePancreas · 2016
Typearticle
Languageen
FieldMedicine
TopicUterine Myomas and Treatments
Canadian institutionsPublic Health OntarioUniversity of TorontoUniversity Health Network
FundersUniversity of Texas MD Anderson Cancer CenterNational Center for Advancing Translational SciencesFondazione Italiana per la Ricerca sul CancroAssociazione Italiana per la Ricerca sul CancroCalifornia Department of Public HealthMinisterstvo Zdravotnictví Ceské RepublikyNational Cancer InstituteNational Institutes of HealthGeneralitat de CatalunyaUniversity of California, San FranciscoMemorial Sloan-Kettering Cancer Center
KeywordsMedicineHysterectomyOdds ratioHormone replacement therapy (female-to-male)GynecologyLogistic regressionCase-control studyConfoundingConfidence intervalObstetricsHormone therapyCancerInternal medicineSurgeryBreast cancer

Abstract

fetched live from OpenAlex

OBJECTIVES: We aimed to evaluate the relation between menstrual and reproductive factors, exogenous hormones, and risk of pancreatic cancer (PC). METHODS: Eleven case-control studies within the International Pancreatic Cancer Case-control Consortium took part in the present study, including in total 2838 case and 4748 control women. Pooled estimates of odds ratios (ORs) and their 95% confidence intervals (CIs) were calculated using a 2-step logistic regression model and adjusting for relevant covariates. RESULTS: An inverse OR was observed in women who reported having had hysterectomy (ORyesvs.no, 0.78; 95% CI, 0.67-0.91), remaining significant in postmenopausal women and never-smoking women, adjusted for potential PC confounders. A mutually adjusted model with the joint effect for hormone replacement therapy (HRT) and hysterectomy showed significant inverse associations with PC in women who reported having had hysterectomy with HRT use (OR, 0.64; 95% CI, 0.48-0.84). CONCLUSIONS: Our large pooled analysis suggests that women who have had a hysterectomy may have reduced risk of PC. However, we cannot rule out that the reduced risk could be due to factors or indications for having had a hysterectomy. Further investigation of risk according to HRT use and reason for hysterectomy may be necessary.

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 score0.013
Threshold uncertainty score0.527

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 head0.022
GPT teacher head0.262
Teacher spread0.240 · 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

Citations14
Published2016
Admission routes1
Has abstractyes

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