Higher-risk breast cancer in women aged 80 and older: Exploring the effect of treatment on survival
Bibliographic record
Abstract
BACKGROUND: To understand the association between various treatments and survival for older women with higher-risk breast cancer when controlling for patient and tumor factors. MATERIALS AND METHODS: We conducted a retrospective, population-based study. Women aged 80 years or older and diagnosed between 2004 and 2017 with non-metastatic, higher-risk breast cancer were identified form the provincial cancer registry in Alberta, Canada. Higher-risk was defined as any of following: T3/4, node positive, human epidermal factor receptor-2 (Her2) positive or triple negative disease. Treatments were surgery, radiotherapy and systemic therapy (hormonal therapy, and/or chemotherapy and/or trastuzumab) or a combination of the previous. Cox regression models were used to examine the association between treatments and breast cancer specific survival (BCSS) and overall survival (OS). RESULTS: 1369 patients were included. The median age was 84 years. 332 (24%) of women had T3-T4 tumors, 792 (58%) had nodal involvement, 130 (10%) had Her2 positive tumors, 124 (9%) had triple negative tumors. After a median follow-up of 35 months, 29.5% of patients died of breast cancer whereas 34.2% died from other causes. Patients had a lower adjusted hazard for BCSS if they had surgery (hazard ratio [HR] = 0.37 95% confidence interval [CI]: 0.27, 0.51), or systemic therapy (HR = 0.75, 95%CI: 0.58, 0.98). Patients had an increased probability of breast cancer death in the first 5 years after diagnosis compared to death from other causes. CONCLUSIONS: Surgery and systemic therapy were associated with longer BCSS and OS. This suggests that maximizing treatments might benefit higher-risk patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".