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Record W2156573513 · doi:10.1136/jech.2010.120956.42

042 Lifecourse predictors of adult parenchymal breast tissue density: results from the Newcastle Thousand Families Study

2010· article· en· W2156573513 on OpenAlexaff
Mark S. Pearce, Peter W. G. Tennant, Tessa M. Pollard, Lesley McLean, B Kaye, L. Lynette Parker

Bibliographic record

VenueJournal of Epidemiology & Community Health · 2010
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsCancer Care Nova ScotiaDalhousie University
Fundersnot available
KeywordsMedicineMenarcheFamily historyBody mass indexCohortCohort studyDemographyBreast cancerPregnancyBreast cancer screeningYoung adultLive birthLogistic regressionObstetricsPediatricsGerontologyMammographyCancerInternal medicine

Abstract

fetched live from OpenAlex

<h3>Objective</h3> To investigate the relative influences of factors acting throughout life on breast tissue density at age 49-58 years. <h3>Design</h3> Follow-up of the Newcastle Thousand Families birth cohort study. <h3>Setting</h3> In 1947, all 1142 babies born in May and June to mothers resident in the city of Newcastle-upon- Tyne were recruited into the Newcastle Thousand Families birth cohort. This study details a sample of women from this cohort who returned for follow-up 49+ years later, and is therefore drawn from throughout the UK and beyond. <h3>Participants</h3> At age 50, 574 study members returned a self-completion questionnaire. The 307 surviving women who returned questionnaires at age 50 were sent a questionnaire asking for details of mammographic screening and for details of their reproductive and contraceptive history. 199 women who gave access to their previous mammograms and had completed both questionnaires were included in this analysis. <h3>Main outcome measures</h3> Breast tissue density patterns were coded into Wolfe categories (N1=lowest risk, P1=low risk, P2=high risk, PY=highest risk). This was analysed, by ordinal logistic regression, in relation to a range of variables at different stages of life, including birthweight, gestational age, duration breast fed, age at menarche, gravidity, age at first pregnancy, menopausal status, breast feeding history, hormonal contraceptive history, use of hormone replacement therapy, cigarette smoking history, alcohol consumption, height, body mass index, physical activity levels, age at scan, and socio-economic status both at birth and in adulthood. <h3>Results</h3> Eleven % (n=22) of women were classified in the lowest Wolfe category of risk (N1), 20% (n=39) as low risk (P1), 48% (n=95) as high risk (P2), and 22% (n=43) as being in the highest category of risk (PY). Increased standardised birthweight (adjusted odds ratio, aOR 1.42 (95% CI 1.08 to 1.87), p=0.01) and not having entered the menopause (aOR, compared to perimenopausal women 3.99 (95% CI 1.78 to 8.97), p=0.001) were both significant independent predictors of being in a higher density group. In contrast, increasing body mass index was independently predictive of being in a lower density group (aOR 0.85 (0.80 to 0.91), p&lt;0.001). <h3>Conclusions</h3> After adjustment for factors acting throughout life, this study identified a significant association between increased birthweight, standardised for sex and gestational age, and increased breast tissue density in adulthood. This observation is consistent with previous research suggesting that heavier babies have an increased risk of breast cancer in later life.

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)0.009
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.008
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 integrity0.0000.004
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 head0.072
GPT teacher head0.401
Teacher spread0.329 · 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.

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

Citations0
Published2010
Admission routes1
Has abstractyes

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