Men With Breast Cancer Have Better Disease-Specific Survival Than Women
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
HYPOTHESIS: Male breast cancer patients have better disease-specific survival than carefully matched female breast cancer patients. DESIGN: Retrospective study. SETTING: University hospital. PATIENTS AND METHODS: Each man in the breast cancer database at Columbia-Presbyterian Medical Center (New York, NY) between the years 1980 and 1998 was matched with a woman. Matching was done based on age and date of diagnosis, stage, and primary histologic findings. MAIN OUTCOME MEASURES: The overall survivals and disease-specific survivals of the male breast cancer group and female breast cancer group were compared. RESULTS: Fifty-three male patients were matched with an equal number of female breast cancer patients. The Kaplan-Meier curves demonstrated that there was no significant difference in overall survival. The 5- and 10-year survivals for women were 0.77 and 0.51, and for men 0.77 and 0.56. When the Kaplan-Meier curves for breast cancer-specific survival were compared, however, there was a significant difference in the 5- and 10-year survivals (P = .05, log-rank test). For women, the 5- and 10-year disease-specific survival was 0.81 and 0.7, respectively, while for men it was 0.9 and 0.9, respectively. In a Cox regression analysis for time to death from breast cancer, stage was the only predictor of death that approached significance (P = .06). CONCLUSIONS: While the overall survivals were equivalent, male breast cancer patients had significantly better disease-specific survivals compared with their female counterparts. Male patients were 4 times more likely to die of other causes than their breast cancer.
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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) | 0.001 | 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 it