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Abstract P2-08-01: Alcohol and tobacco use in relation to mammographic density in 23,456 women

2020· article· en· W3013804677 on OpenAlexaff
Russell B. McBride, Kezhen Fei, Joseph H. Rothstein, Stacey Alexeeff, Xiaoyu Song, Lori C. Sakoda, Valerie McGuire, Ninah Achacoso, Luana Acton, Rhea Liang, Jafi A. Lipson, Martin J. Yaffe, Daniel L. Rubin, Alice S. Whittemore, Laurel A. Habel, Weiva Sieh

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineBreast cancerTamoxifenMenarcheMammographyBody mass indexPopulationCohortMenopauseGynecologyFamily historyHormone replacement therapy (female-to-male)CancerDigital mammographyBreast cancer screeningInternal medicineOncologyObstetricsDemographyEnvironmental health

Abstract

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Abstract Background: High percent density (PD) is common and is among the strongest risk factors for breast cancer. The prevalence of heterogeneously dense or extremely dense breasts is between 40% to 60% of screening age women, and is estimated to account for up to one third of all breast cancer (BC) diagnoses. PD decreases with age, body mass index (BMI), number of children, and menopause; and increases with age at menarche, age at first birth, and family history of breast cancer. Of particular interest are modifiable exposures believed to alter PD, such as the use of menopausal hormone therapy (MHT), tamoxifen and alcohol that could provide opportunities for women to reduce their BC risk. The dense area (DA) of the breast appears radiopaque on a mammogram and contains greater proportions of collagen, epithelial and stromal cells compared to the nondense area (NDA), which largely consists of fatty tissue. Recent studies have shown that NDA is inversely associated with BC risk, independently of DA, suggesting that normal breast fat may play a protective role. The underlying mechanisms through which mammographic density (MD) phenotypes are associated with BC risk are poorly understood. Methods: We examined associations of alcohol and tobacco use with PD, DA and NDA in a population-based cohort of 23,456 women screened using full-field digital mammography machines manufactured by Hologic or General Electric (GE). MD measurements were obtained using Cumulus an average of 2.9 years after the survey date. Machine-specific effects were estimated using linear regression, adjusted for known biologically plausible correlates of MD, and combined using random effects meta-analysis methods. Results: Alcohol use was positively associated with PD (ptrend=0.01), unassociated with DA (ptrend=0.23), and inversely associated with NDA (ptrend=0.02) in models adjusted for age, BMI, reproductive factors, physical activity, and family history of breast cancer. In contrast, tobacco use was inversely associated with PD (ptrend=0.0008), unassociated with DA (ptrend=0.93), and positively associated with NDA (ptrend<0.0001). These trends were stronger in normal and overweight women than in obese women. Conclusions: This study provides the strongest evidence to date that association of alcohol and tobacco use with PD result from their associations with NDA rather than DA. Impact: Alcohol consumption, and less consistently tobacco use, have been shown to increase risk of breast cancer. These findings indicate that PD and NDA may mediate the association of alcohol drinking, but not tobacco smoking, with increased breast cancer risk. Further studies are needed to elucidate the modifiable lifestyle factors that influence breast tissue composition, and the important role of the fatty tissues on breast health. Citation Format: Russell B McBride, Kezhen Fei, Joseph H Rothstein, Stacey E Alexeeff, Xiaoyu Song, Lori C Sakoda, Valerie McGuire, Ninah Achacoso, Luana Acton, Rhea Y Liang, Jafi A Lipson, Martin J Yaffe, Daniel L Rubin, Alice S Whittemore, Laurel A Habel, Weiva Sieh. Alcohol and tobacco use in relation to mammographic density in 23,456 women [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-08-01.

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)0.000
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 score0.019
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.155
GPT teacher head0.414
Teacher spread0.259 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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