Role of Taxanes in Triple-Negative Breast Cancer: A Study From Tertiary Cancer Center in South India
Bibliographic record
Abstract
BACKGROUND: Breast cancer is the most common female cancer seen globally. Triple-negative breast cancer (TNBC) is a special subtype without any obvious target and optimum treatment remains challenging. The aim was to study the clinical, pathological profile and treatment outcome of TNBC patients. METHODS: This was a retrospective observational study of TNBC patients diagnosed from January 2010 to June 2012 at a tertiary cancer center in South India. Patient's clinical and pathological characteristics were studied. The 5-year estimate of survival for non-metastatic TNBC was done using the Kaplan-Meier method. RESULTS: Out of 804 patients of breast cancer, 237 were diagnosed as TNBC. The median age was 45 years and 58% were premenopausal. The 5-year disease-free survival (DFS) and overall survival (OS) for non-metastatic TNBC patients were 59% and 74%, respectively. The addition of a taxane to anthracycline-based regimen did not show a significant difference in DFS (P = 0.885) as well as OS (P = 0.856). CONCLUSION: The role of adding taxanes to anthracycline-based chemotherapy in adjuvant setting for TNBC remains controversial and larger prospective studies are warranted.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".