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Record W4403356879 · doi:10.1038/s41598-024-75305-4

Sex hormones and risk of lung and colorectal cancers in women: a Mendelian randomization study

2024· article· en· W4403356879 on OpenAlexfundno aff
Marion Denos, Yi‐Qian Sun, Ben Brumpton, Yafang Li, Demetrius Albanes, Andrea N. Burnett‐Hartman, Peter T. Campbell, Sébastien Küry, Christopher I. Li, Emily White, Mark A. Jenkins, Xiao‐Mei Mai

Bibliographic record

VenueScientific Reports · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsnot available
FundersFaculty of Medicine and Health, University of SydneyNIHR Imperial Biomedical Research CentreInstituto de Salud Carlos IIICancer Council VictoriaNational Health and Medical Research CouncilNorwegian Institute of Public HealthWorld Cancer Research FundMedical Research CouncilFakultet for medisin og helsevitenskap, Norges Teknisk-Naturvitenskapelige UniversitetChonnam National University Hwasun HospitalCenters for Disease Control and PreventionBiobanco VascoDamon Runyon Cancer Research FoundationKarl-Franzens-Universität GrazSchool of Public Health, Imperial College LondonDeutsche KrebshilfeAssociazione Italiana per la Ricerca sul CancroXunta de GaliciaUniversity of South FloridaHelse Midt-NorgeVetenskapsrådetMutuelle Générale de l'Education NationaleBundesministerium für Bildung und ForschungMinisterio de Economía y CompetitividadChonnam National UniversityCentres de Recerca de CatalunyaUmeå UniversitetMinisterstvo Zdravotnictví Ceské RepublikyImperial College LondonGeneralitat de CatalunyaCanadian Institutes of Health ResearchCancerfondenNational Cancer InstituteFundación Científica Asociación Española Contra el CáncerInstitut Gustave-RoussyMedizinische Universität GrazGrantová Agentura České RepublikyHarvard T.H. Chan School of Public HealthAgència de Gestió d'Ajuts Universitaris i de RecercaNational Institute for Health and Care ResearchInstitut National de la Santé et de la Recherche MédicaleMarshfield Clinic Research FoundationMoffitt Cancer CenterNorges Teknisk-Naturvitenskapelige UniversitetLigue Contre le CancerUniverzita Karlova v PrazeDeutsches KrebsforschungszentrumMike and Josie Harper Cancer Research InstituteNational Institutes of HealthFlorida Department of HealthUniversity of PittsburghMemorial Sloan-Kettering Cancer CenterJohns Hopkins UniversityBrigham and Women's HospitalWorld Health OrganizationWageningen University and ResearchCancer Research UKAmerican Cancer SocietyU.S. Department of Health and Human Services
KeywordsMendelian randomizationSex hormone-binding globulinTestosterone (patch)OncologyColorectal cancerHormoneMedicineHazard ratioInternal medicineGenome-wide association studyPhysiologyConfidence intervalCancerBioinformaticsAndrogenBiologySingle-nucleotide polymorphismGeneticsGenotypeGene

Abstract

fetched live from OpenAlex

The roles of sex hormones such as estradiol, testosterone, and sex hormone-binding globulin (SHBG) in the etiology of lung and colorectal cancers in women, among the most common cancers after breast cancer, are unclear. This Mendelian randomization (MR) study evaluated such potential causal associations in women of European ancestry. We used summary statistics data from genome-wide association studies on sex hormones and from the Trøndelag Health Study (HUNT) and large consortia on cancers. There was suggestive evidence of 1-standard deviation increase in total testosterone levels being associated with a lower risk of lung non-adenocarcinoma (hazard ratio 0.60, 95% confidence interval 0.37-0.98) in the HUNT Study. However, this was not confirmed by using data from a larger consortium. In general, we did not find convincing evidence to support a causal role of sex hormones on risk of lung and colorectal cancers in women of European ancestry.

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)0.011
metaresearch head score (Gemma)0.027
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 score0.011
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.027
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.252
Teacher spread0.247 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

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