Survival of Filipino women with breast cancer in the United States
Bibliographic record
Abstract
BACKGROUND: The survival of women with early-stage breast cancer varies by racial group. Filipino women with breast cancer are an understudied group and are often combined with other Asian groups. We compared clinical presentations and survival rates for Filipino and White women with breast cancer diagnosed in the United States. METHODS: We conducted a retrospective cohort study of women with breast cancer diagnosed between 2004 and 2015 in the SEER18 registries database. We compared crude survival between Filipino and White women. We then calculated adjusted hazard ratios (HR) in a propensity-matched design using the Cox proportional hazards model. RESULTS: There were 10,834 Filipino (2.5%) and 414,618 White women (97.5%) with Stage I-IV breast cancer in the SEER database. The mean age at diagnosis was 57.5 years for Filipino women and 60.8 years for White women (p < 0.0001). Filipino women had more high-grade and larger tumors than White women and were more likely to have node-positive disease. Among women with Stage I-IIIC breast cancer, the crude 10-year breast cancer-specific survival rate was 91.0% for Filipino and 88.9% for White women (HR 0.81, 95% CI 0.74-0.88, p < 0.01). In a propensity-matched analysis, the HR was 0.73 (95% CI 0.66-0.81). The survival advantage for Filipino women was present in subgroups defined by age of diagnosis, nodal status, estrogen receptor status, and HER2 receptor status. CONCLUSION: In the United States, Filipino women often present with more advanced breast cancers than White women, but experience better breast cancer-specific survival.
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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 | 0.000 | 0.002 |
| 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) | 0.001 | 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".