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Record W1520216531 · doi:10.1155/2015/203284

Serum IGFBP-2 and Risk of Atypical Hyperplasia of the Breast

2015· article· en· W1520216531 on OpenAlexaff
Chelsea Catsburg, Marc J. Gunter, Lesley F. Tinker, Rowan T. Chlebowski, Michaël Pollak, Howard D. Strickler, Michele L. Coté, David L. Page, Thomas E. Rohan

Bibliographic record

VenueJournal of Cancer Epidemiology · 2015
Typearticle
Languageen
FieldMedicine
TopicBreast Lesions and Carcinomas
Canadian institutionsMcGill University
FundersNational Center for Advancing Translational SciencesNational Cancer InstituteBreast Cancer Research Foundation
KeywordsHyperplasiaChemistryMedicineInternal medicine

Abstract

fetched live from OpenAlex

Atypical hyperplasia of the breast (AH) is associated with increased risk of subsequent invasive breast cancer, yet little is known about the etiology of AH. Insulin-like growth factor binding protein 2 (IGFBP-2) may contribute to the development of AH due to its proliferative effects on mammary tissue. We conducted a nested case-control study of postmenopausal women enrolled in Women's Health Initiative-Clinical Trial. Cases were 275 women who developed incident AH during follow-up, individually (1 : 1) matched to controls. Levels of IGFBP-2 were determined from fasting serum collected at baseline. Multivariable conditional logistic regression models were used to estimate odds ratios for the association of IGFBP-2 with risk of AH. Serum IGFBP-2 was associated with a nonsignificant decrease in risk for AH, when comparing the highest quartile to lowest quartile (OR = 0.65; 95% CI = 0.32-1.31). This decrease in risk was most evident when analyses were restricted to nondiabetic, nonusers of hormone therapy (OR = 0.33, 95% CI = 0.13-0.86, p trend = 0.06) and nondiabetic women who were overweight or obese (OR = 0.43, 95% CI = 0.18-1.03, p trend = 0.05). Results from this study provide some support for an inverse association between serum IGFBP2 levels and risk of AH, particularly in nondiabetic women who are overweight or obese. Further studies are required to confirm these results.

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)0.001
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 score0.017
Threshold uncertainty score0.167

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.054
GPT teacher head0.349
Teacher spread0.295 · 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

Citations5
Published2015
Admission routes1
Has abstractyes

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