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Record W2564582044 · doi:10.1158/1940-6215.prev-14-b46

Abstract B46: The influence of exemestane on breast density in postmenopausal women: A cohort study nested within the NCIC CTG MAP.3 chemoprevention trial

2015· article· en· W2564582044 on OpenAlexaffabout
Harriet Richardson, Paul E. Goss, Melanie Walker, Doris Jabs, Will D. King

Bibliographic record

VenueCancer Prevention Research · 2015
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsHotel Dieu HospitalQueen's University
Fundersnot available
KeywordsExemestaneMedicineBreast cancerInternal medicinePlaceboConfoundingRandomized controlled trialOncologyMenopauseGynecologyCancerAromatase

Abstract

fetched live from OpenAlex

Abstract Background: Endogenous estradiol blood levels and high breast density are both associated with an increased risk for breast cancer (BC), but, there is conflicting evidence about whether or not they influence breast cancer risk through a shared pathway. Exemestane is an aromatase inhibitor that blocks the synthesis of estrogen and has been demonstrated to reduce the incidence of breast cancer in postmenopausal women by 65%. However the effects of exemestane on breast density remain unclear. Objectives: The primary objective of this research was to prospectively examine the relationship between exemestane versus placebo and changes in mammographic breast density (BD) in postmenopausal women during 3 or more years of treatment. Methods: The NCIC Clinical Trials Group conducted a phase III randomized controlled trial (RCT) comparing exemestane (E), with placebo (P) in postmenopausal women at higher than average risk for BC (MAP.3). This study was nested within the MAP.3 RCT using data from 568 participants across Canada and Buffalo, New York. Information on treatment allocation and established risk factors for BC was previously collected and data on the outcome measures was obtained from mammograms. Baseline and follow-up mammograms were collected from participating centres and were measured (percent density) using Cumulus software by our team radiologist (DJ). Multivariable linear regression was used to estimate the effect of exemestane treatment on >=3 year change in percent BD from randomization controlling for potential confounding variables. Results: Percent BD was measured for 386 participants (E=200, P=186) with a baseline and >=3 year follow-up mammogram that was matching in format (i.e. film or digital). The average age of women at study entry was 63 years and the average Gail score was 2.8%. The mean BD was similar in both arms at baseline (P: 12.9% (SD: 14.5) and E: 13.7% (SD: 14.4)). Similarly, the annual mean change in percent BD was not significantly different between the two treatment arms (P: 0.63% (SD: 1.82) vs E: .077% (SD: 1.80); p=0.90). After controlling for potential confounders (age, body mass index, first degree family history of BC and prior use of HRT), exemestane was not predictive of change in percent BD (p-value=0.641). Neither age (<60 vs. >=60 yrs) nor BMI modified the exemestane-breast density relationship significantly. Conclusion: We found no association between >=3 years of exemestane use and change in percent BD among a subset of postmenopausal women participating in MAP.3. These results suggest that estrogen and breast density may have independent pathways in breast cancer etiology. Citation Format: Harriet Richardson, Paul E. Goss, Melanie Walker, Doris Jabs, Will King. The influence of exemestane on breast density in postmenopausal women: A cohort study nested within the NCIC CTG MAP.3 chemoprevention trial. [abstract]. In: Proceedings of the Thirteenth Annual AACR International Conference on Frontiers in Cancer Prevention Research; 2014 Sep 27-Oct 1; New Orleans, LA. Philadelphia (PA): AACR; Can Prev Res 2015;8(10 Suppl): Abstract nr B46.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.089
GPT teacher head0.434
Teacher spread0.344 · 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 source (direct Gemma or distilled Codex), 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
Published2015
Admission routes2
Has abstractyes

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