Abstract 776: Temporal changes in mammographic breast density and breast cancer risk among women with benign breast disease
Bibliographic record
Abstract
Abstract Introduction: Benign breast disease (BBD) is associated with increased breast cancer risk, and the magnitude of this risk is characterized by the severity of the histological classification of the biopsy lesion. High mammographic density (MBD) is an independent risk factor for invasive breast cancer. Given that MBD is altered by endogenous and exogenous factors, its temporal changes may impact future breast cancer risk, but this is poorly studied, particularly among high risk BBD patients. In this study, we examined whether MBD changes following a BBD diagnosis were associated with subsequent breast cancer risk. Methods: We conducted a case-control study within a cohort of 15,395 women aged 18-86 years who were members of the Kaiser Permanente Northwest Region health care system, had a diagnosis of BBD between 1970 and 2012 and were followed through mid-2015. Cases (n=261) were BBD patients who developed invasive breast cancer at least one year after the index BBD diagnosis. Controls were matched (1:1), on age at BBD diagnosis and health plan membership duration and did not develop breast cancer during the follow-up duration. Standardized change in percent MBD per 2 years, categorized as an increase (≥0%), stable/minimal decrease (-5%< to <0) or decrease (≤-5%), was determined from baseline (pre-biopsy) and follow-up (prior to breast cancer diagnosis for cases or matched selection date for controls) mammograms, using computer-assisted software. Associations between MBD change and breast cancer risk overall and stratified by BBD diagnosis age and histology were determined using unconditional logistic regression adjusted for matching factors and other covariates. Results: At BBD diagnosis (median age (range)=54.6 years (32.4, 86.6)), 64.5% (n=329: n=151 cases and n=178 controls) of women had non-proliferative and 35.5% (n=181: n=110 cases and n=71 controls) had proliferative BBD with or without atypia. Compared to women with stable/minimal MBD decrease, those who experienced a decline ≥5% per 2 years were less likely to develop breast cancer (odds ratio [OR]: 0.64; 95% confidence interval [CI]: 0.38, 1.07). However, among women aged ≥50 years at BBD diagnosis, an MBD decrease ≥5% was significantly associated with reduced breast cancer risk (OR: 0.48; 95%CI: 0.25, 0.92), with the protective effect most apparent for those with proliferative (OR: 0.32; 95%CI: 0.11, 0.99) versus non-proliferative (OR: 0.70; 95%CI: 0.30, 1.64) BBD. Discussion: Temporal MBD declines were associated with reduced risk of subsequent breast cancer particularly among BBD patients aged ≥50 years and with proliferative BBD diagnoses. These findings suggest that monitoring MBD may be useful in determining risk and that strategies to actively reduce MBD may be helpful in reducing breast cancer risk among high-risk BBD patients. Funding: Dr. Rohan is supported in part by the Breast Cancer Research Foundation (BCRF-22-140). Citation Format: Maeve Mullooly, Shaoqi Fan, Ruth M. Pfeiffer, Erin Aiello Bowles, Máire A. Duggan, Roni T. Falk, Kathryn Richert-Boe, Terry Kimes, Jonine D. Figueroa, Thomas E. Rohan, Mustapha Abubakar, Gretchen L. Gierach. Temporal changes in mammographic breast density and breast cancer risk among women with benign breast disease [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 776.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".