Cox models survival analysis based on breast cancer treatments.
Bibliographic record
Abstract
BACKGROUND: The aim of this study is to evaluate the association between different treatments and survival time of breast cancer patients using either standard Cox model or stratified Cox model. METHODS: The study was conducted on 15830 women diagnosed with breast cancer in British Columbia, Canada. They were divided into eight groups according to patients' ages and stage of disease Either Cox's PH model or stratified Cox model was fitted to each group according to the PH assumption and tested using Schoenfeld residuals. RESULTS: The data show that in the group of patients under age 50 years old and over age 50 with stage I cancer, the highest hazard was related to radiotherapy (HR= 3.15, CI: 1.85-5.35) and chemotherapy (HR= 3, CI: 2.29- 3.93) respectively. For both groups of patients with stage II cancer, the highest risk was related to radiotherapy (HR=3.02, CI: 2.26-4.03) (HR=2.16, CI:1.85-2.52). For both groups of patients with stage III cancer, the highest risk was for surgery (HR=0.49, CI: 0.33-0.73), (HR=0.45, CI: 0.36-0.57). For patients of age 50 years or less with stage IV cancer, none of the treatments were statistically significant. In group of patients over age 50 years old with stage IV cancer, the highest hazard was related to surgery (HR=0.64, CI: 0.53-0.78). CONCLUSION: The results of this study show that for patients with stage I and II breast cancer, radiotherapy and chemotherapy had the highest hazard; for patients with stage III and IV breast cancer, the highest hazard was associated with treatment surgery.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".