Prognostic factors for male breast cancer: similarity to female counterparts.
Bibliographic record
Abstract
AIM: To assess whether prognostic factors in male (MBC) and female (FBC) breast cancer have similar impact on survival. PATIENTS AND METHODS: Charts for men and women diagnosed with breast cancer referred to the London Regional Cancer Program (LRCP) were reviewed. Patients with distant metastatic diseases were excluded. Data on prognostic factors including age, nodal status, resection margin, use of hormonal therapy, chemotherapy with/without hormone and radiation therapy (RT), overall survival (OS), cancer-specific survival (CSS), and disease-free survival (DFS) were analyzed. Survival estimates were obtained using the Kaplan-Meier methodology. The Cox regression interaction was used to compare male and female differences in prognostic factors. RESULTS: From 1963-2006 there were 75 cases of MBC and 1,313 of FBC totaling in 1,388 breast cancer cases. The median age of the cohort was 53 (range=23-90) years. The median follow-up was 90 (range=0.4-339) months. Of the prognostic factors considered, nodal status had a significant Cox regression interaction. For OS, p=0.001 with hazard ratios of 0.83 (95% confidence interval CI=0.42-1.64) and 2.88 (95% CI=2.36-3.52) for males and females, respectively. For CSS p=0.041 with hazard ratios of 1.22 (95% CI=0.45-3.27) and 3.52 (95% CI=2.76-4.48) for males and females, respectively. For node-positive cases, distant disease recurrence-free survival was worse for MBC (log rank, p<0.001). CONCLUSION: This large series showed that the nodal status influences survival differently in MBC and FBC. The findings of this study need confirmation from a more complete prospective database and further investigations on improving high-risk node-positive MBC management are warranted.
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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".