Four cycles of docetaxel and cyclophosphamide as adjuvant chemotherapy in node negative breast cancer: A real-world study
Bibliographic record
Abstract
INTRODUCTION: The optimal number of cycles of adjuvant docetaxel and cyclophosphamide (DC) in patients with node negative breast cancer is not known. We aimed to analyse the survival outcomes of patients with node negative and human epidermal growth factor receptor (HER2)-negative breast cancer treated with four cycles of DC. METHODS: Patients with node negative and HER2-negative breast cancer treated with four cycles of DC after surgery in a large Canadian province from 2008 to 2012 were identified. We analysed the 4-year and 9-year invasive disease free survival (iDFS) and overall survival (OS). Cox regression models were constructed to examine the associations of clinical characteristics with survival outcomes. RESULTS: A total of 657 patients were eligible for the current analysis. The median age was 53 years and 71.2% of patients had hormone receptor-positive breast cancer. Approximately three-fourths of patients had grade III tumours. At a median follow-up of nine years, the 4-year iDFS and OS were 91.0% and 95.5% and the corresponding 9-year rates were 80.5% and 88.0%, respectively. On multivariable Cox regression analysis, grade III tumour predicted worse iDFS (hazard ratio [HR], 2.15; 95% confidence interval [CI], 1.09-4.21; P = 0.026) and OS (HR, 3.15; 95% CI, 1.18-8.45; P = 0.022). CONCLUSIONS: Adjuvant chemotherapy with four cycles of DC in a select population of node negative breast cancer was associated with encouraging long-term survival. In the absence of a randomized comparison between four and six cycles of DC, this study presents real-world evidence to consider four cycles of DC as a reasonable option.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".