Abstract 2286: Short term reduction in mammographic density predicts survival in breast cancer.
Bibliographic record
Abstract
Abstract Back ground: Identification of the factors that predict response to treatment in breast cancer patients early after diagnosis is important in guiding the treatment strategy. High mammographic density (MD) is a risk factor for breast cancer. However no study has examined the association between change in MD and death in breast cancer survivors. We hypothesized that a short-term change in breast density may be a surrogate biomarker predicting risk of death from breast cancer and all causes. Methods: We evaluated the relationship between reduction in MD and risk of death from all causes within the Health, Eating, Activity, and Lifestyle (HEAL) Study. In a prospective observational study, we studied 403 women diagnosed with primary invasive breast carcinoma between 1995 and 1998 and followed until death or September 2009. We collected mammograms and prognostic, demographic, and lifestyle factors as well as treatments at the time of diagnosis and two years after the diagnosis was made. Mammograms were digitized and MD was measured on cranio-caudal (CC) images of the unaffected breast using a computer assisted program developed at the University of Toronto. MD reduction (MDR) was evaluated based on two mammograms; the first was taken 12 months before diagnosis, and the second approximately 24 months after diagnosis. MDR was defined as the difference between the MD of these two images (% MDR = % preMD -% postMD). Reduction in MD was categorized into a binary variable as women who had a MDR ≥5% compared to those with less than 5% reduction in MD. Cox proportional hazards models were used to estimate the Hazard ratios and 95% confidence intervals. Results: Breast cancer patients with 5% or more reduction in MD were younger (mean age was 55.7 compared to 58.9), more likely to be premenopausal at diagnosis (36.7% compared to 24.0%), and more likely to have a history of oral contraception (73.9% compared to 63.3%). Women with MDR ≥5% were 49% less likely to die from any cause after adjustment for age, BMI, estrogen receptor status, progesterone receptor status, menopausal status at baseline, smoking, stage, tamoxifen use, chemotherapy, radiation therapy, and study center (HR=0.51 CI: 0.3-0.86). The results were stronger when we restricted the analysis to women who were premenopausal at diagnosis. When we restricted the analysis to women who had taken tamoxifen a similar direction was observed but the results were not statistically significant. Conclusion: Result from our data suggests that reduction in mammographic density few years after breast cancer diagnosis may be used as a predictor of overall survival. Citation Format: Ali Ozhand, Roberta Mckean-Cowdin, Leslie Bernstein, Rachel Ballard-Babash, Anne McTiernan, Kathy B. Baumgartner. Short term reduction in mammographic density predicts survival in breast cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2286. doi:10.1158/1538-7445.AM2013-2286
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".