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Record W2157283269 · doi:10.1158/1055-9965.epi-04-0706

Insulin-Like Growth Factor-I, IGF-Binding Protein-3, and Mammographic Breast Density

2005· article· en· W2157283269 on OpenAlexaff
Caroline Diorio, Michaël Pollak, Celia Byrne, Benoı̂t Mâsse, Nicole Hébert‐Croteau, Martin J. Yaffe, Gary Côté, Sylvie Bérubé, Carol Morin, Jacques Brisson

Bibliographic record

VenueCancer Epidemiology Biomarkers & Prevention · 2005
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsUniversité LavalCentre hospitalier universitaire de QuébecHealth Sciences CentreUniversity of TorontoThe Quebec Population Health Research NetworkHôpital Charles-Le MoyneMcGill UniversityJewish General HospitalSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineMAMMOGRAPHIC DENSITYBreast cancerMammographyCorrelationBreast densityInternal medicineInsulin-like growth factorPostmenopausal womenInsulin-like growth factor-binding proteinOncologyEndocrinologyGynecologyGrowth factorCancerReceptorMathematics

Abstract

fetched live from OpenAlex

Some studies have suggested that insulin-like growth factor (IGF) pathway is related to premenopausal breast density, one of the strongest known breast cancer risk factors. This study was designed specifically to test the hypothesis that higher levels of IGF-I and lower levels of IGF-binding protein (IGFBP)-3 are associated with high mammographic breast density among premenopausal but not among postmenopausal women. A total of 783 premenopausal and 791 postmenopausal healthy women were recruited during screening mammography examinations. Blood samples were collected at the time of mammography, and plasma IGF-I and IGFBP-3 levels were measured by ELISA. Mammographic breast density was estimated using a computer-assisted method. Spearman's partial correlation coefficients (r(s)) were used to evaluate the associations. Adjusted mean breast density was assessed by joint levels of IGF-I and IGFBP-3 using generalized linear models. Among premenopausal women, high levels of IGF-I and low levels of IGFBP-3 were independently correlated with high breast density (r(s) = 0.083; P = 0.021 and r(s) = -0.124; P = 0.0005, respectively). Correlation of IGF-I with breast density was stronger among women in the lowest tertile of IGFBP-3 than among those in the highest tertile of IGFBP-3 (r(s) = 0.138; P = 0.027 and r(s) = -0.039; P = 0.530, respectively). In contrast, the correlation of IGFBP-3 with breast density was stronger among women in the highest tertile of IGF-I than among those in the lowest tertile of IGF-I (r(s) = -0.150; P = 0.016 and r(s) = -0.008; P = 0.904, respectively). Women in the combined top tertile of IGF-I and bottom tertile of IGFBP-3 had higher mean breast density than those in the combined bottom tertile of IGF-I and top tertile of IGFBP-3 (53.8% versus 40.9%; P = 0.014). No significant association was observed among postmenopausal women. Our findings confirm that IGF-I and IGFBP-3 are associated with breast density among premenopausal women. They provide additional support for the idea that, among premenopausal women, these growth factors may affect breast cancer risk, at least in part, through their influence on breast tissue morphology as reflected on mammogram.

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)0.000
metaresearch head score (Gemma)0.003
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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.038
GPT teacher head0.333
Teacher spread0.294 · 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

Citations155
Published2005
Admission routes1
Has abstractyes

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