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Record W2290864514

Variation in mammographic density during menstrual cycle

2007· article· en· W2290864514 on OpenAlexaff
Lisa Martin, Norman F. Boyd

Bibliographic record

VenueCancer Epidemiology and Prevention Biomarkers · 2007
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsUniversity of TorontoOntario Institute for Cancer Research
Fundersnot available
KeywordsMedicineMenstrual cycleMammographyConfidence intervalBreast cancerGynecologyFollicular phaseBreast densityObstetricsCancerInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

A54 Background: The sensitivity of mammography for cancer detection is less in women aged 40-49 compared to older women, due in part to more extensive mammographic density in younger women. To improve the quality of screening it has been suggested that premenopausal women to be examined in the follicular phase of the menstrual cycle, when density is thought to be less extensive than in the luteal phase. We have examined the extent to which mammographic density and dense area vary according to the menstrual cycle.
 > Methods: Premenopausal women aged 40-49 with regular menstrual cycles, without a history of breast disease, and who had mammograms at Sunnybrook/Women’s College or Mount Sinai Hospitals participated in the study. We measured percent breast density, breast area, and dense area using the Cumulus software. Dates of the first day of the last and next menstrual cycles (NMC) were determined by follow-up phone calls. To determine the time in the cycle when the mammogram was taken, the interval between mammogram date and the date of the start of NMC was calculated, and divided into 4 intervals: interval 1 (>21 days before NMC), interval 2 (15-21 days before NMC), interval 3 (8-14 days before NMC) and Interval-4 (≤7 days before NMC).
 > Results: The total number of subjects included in the analysis was 419: 77 in interval 1, 109 in interval 2, 105 in interval 3 and 128 in interval 4. The least square means of dense area after adjusting for age, BMI, breast thickness and mammography machine characteristics ( KV, MAS and Pressure), were 51.4 cm 2 , 49.6 cm 2 , 50.7 cm 2 and 55.5 cm 2 during intervals 1-4 respectively, however, the results were not statistically significant. The adjusted least square means of percent density were 41.7%, 39.5%, 40.5% and 41.9% during intervals 1-4 respectively; the results were not statistically significant. There were no significant variations between different intervals with regards to mammographic density after adjusting for age, BMI, breast thickness and mammography machine characteristics, such as KV, MAS and Pressure.
 > Conclusion: There was no difference in mammographic density in relation to the time of mammography after adjusting for machine parameters. Data do not support the suggestion that premenopausal women would benefit from having mammographic examination in the follicular phase of menstrual cycle.

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 score0.017
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.032
GPT teacher head0.361
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.

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

Citations0
Published2007
Admission routes1
Has abstractyes

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