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Record W4402987309 · doi:10.1186/s13058-024-01890-x

Reproductive factors and mammographic density within the International Consortium of Mammographic Density: A cross-sectional study

2024· article· en· W4402987309 on OpenAlexaff
Jessica O’Driscoll, Anya Burton, Gertraud Maskarinec, Beatriz Pérez‐Gómez, Celine M. Vachon, Hui Miao, Martín Lajous, Ruy López‐Ridaura, A. Heather Eliassen, Ana Pereira, María Luisa Garmendia, Rulla M. Tamimi, Kimberly A. Bertrand, Ava Kwong, Giske Ursin, Eunjung Lee, Samera Azeem Qureshi, Huiyan Ma, Sarah Vinnicombe, Sue Moss, Steve Allen, Rose Ndumia, Sudhir Vinayak, Soo‐Hwang Teo, Shivaani Mariapun, Farhana Fadzli, Beata Pepłońska, Chisato Nagata, Jennifer Stone, John L. Hopper, Graham G. Giles, Vahit Özmen, Joachim Schüz, Carla H. van Gils, Johanna O. P. Wanders, Reza Sirous, Mehri Sirous, John H. Hipwell, Jisun Kim, Jong Won Lee, Mikael Hartman, Jingmei Li, Christopher G. Scott, Anna M. Chiarelli, Linda Linton, Marina Pollán, Anath Flugelman, Dorria Salem, Rasha Kamal, Norman F. Boyd, Isabel dos‐Santos‐Silva, Valerie McCormack, Maeve Mullooly

Bibliographic record

VenueBreast Cancer Research · 2024
Typearticle
Languageen
FieldMedicine
TopicDigital Radiography and Breast Imaging
Canadian institutionsPrincess Margaret Cancer CentreCancer Care Ontario
FundersNational Cancer InstituteNational Medical Research CouncilCancer Council VictoriaMedical Research CouncilNational Institutes of HealthUniversiti MalayaZonMwWorld Health OrganizationEuropean CommissionIsfahan University of Medical SciencesBreast Cancer CampaignEngineering and Physical Sciences Research CouncilIsrael Cancer AssociationHealth Research BoardNational Health and Medical Research CouncilCancer Research UKSusan G. Komen for the CureWorld Cancer Research FundNational Breast Cancer FoundationEllison Medical Foundation
KeywordsMAMMOGRAPHIC DENSITYCross-sectional studySurgical oncologyMedicineBreast cancerObstetricsMammographyGynecologyOncologyCancerInternal medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Elevated mammographic density (MD) for a woman's age and body mass index (BMI) is an established breast cancer risk factor. The relationship of parity, age at first birth, and breastfeeding with MD is less clear. We examined the associations of these factors with MD within the International Consortium of Mammographic Density (ICMD). METHODS: ICMD is a consortium of 27 studies with pooled individual-level epidemiological and MD data from 11,755 women without breast cancer aged 35-85 years from 22 countries, capturing 40 country-& ethnicity-specific population groups. MD was measured using the area-based tool Cumulus. Meta-analyses across population groups and pooled analyses were used to examine linear regression associations of square-root (√) transformed MD measures (percent MD (PMD), dense area (DA), and non-dense area (NDA)) with parity, age at first birth, ever/never breastfed and lifetime breastfeeding duration. Models were adjusted for age at mammogram, age at menarche, BMI, menopausal status, use of hormone replacement therapy, calibration method, mammogram view and reader, and parity and age at first birth when not the association of interest. RESULTS: Among 10,988 women included in these analyses, 90.1% (n = 9,895) were parous, of whom 13% (n = 1,286) had ≥ five births. The mean age at first birth was 24.3 years (Standard deviation = 5.1). Increasing parity (per birth) was inversely associated with √PMD (β: - 0.05, 95% confidence interval (CI): - 0.07, - 0.03) and √DA (β: - 0.08, 95% CI: - 0.12, - 0.05) with this trend evident until at least nine births. Women who were older at first birth (per five-year increase) had higher √PMD (β:0.06, 95% CI:0.03, 0.10) and √DA (β:0.06, 95% CI:0.02, 0.10), and lower √NDA (β: - 0.06, 95% CI: - 0.11, - 0.01). In stratified analyses, this association was only evident in women who were post-menopausal at MD assessment. Among parous women, no associations were found between ever/never breastfed or lifetime breastfeeding duration (per six-month increase) and √MD. CONCLUSIONS: Associations with higher parity and older age at first birth with √MD were consistent with the direction of their respective associations with breast cancer risk. Further research is needed to understand reproductive factor-related differences in the composition of breast tissue and their associations with breast cancer 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)0.002
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 score0.004
Threshold uncertainty score0.545

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.385
Teacher spread0.331 · 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

Citations6
Published2024
Admission routes1
Has abstractyes

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