Cyclophosphamide, Epirubicin, and Fluorouracil Versus Dose-Dense Epirubicin and Cyclophosphamide Followed by Paclitaxel Versus Doxorubicin and Cyclophosphamide Followed by Paclitaxel in Node-Positive or High-Risk Node-Negative Breast Cancer
Bibliographic record
Abstract
PURPOSE Cyclophosphamide, epirubicin, and fluorouracil (CEF) and doxorubicin and cyclophosphamide (AC) followed by paclitaxel (T) are commonly used adjuvant regimens in women with early breast cancer. In a previous trial in women with locally advanced breast cancer, 3 months of high-dose epirubicin and cyclophosphamide (EC) administered every 2 weeks (dose-dense) was equivalent to 6 months of CEF. We hypothesized that 3 months of paclitaxel after dose-dense EC (EC/T) would be superior to CEF or AC/T. METHODS After lumpectomy or mastectomy, women 60 years of age or younger with axillary node-positive or high-risk node-negative breast cancer were randomly assigned to receive CEF, EC/T, or AC/T for 6 months. This article reports the interim analysis for recurrence-free survival (RFS), which was planned after 227 recurrences. Results A total of 2,104 patients were enrolled. The median follow-up is 30.4 months. Hazard ratios for recurrence are as follows: AC/T versus CEF, 1.49 (95% CI, 1.12 to 1.99), P = .005; AC/T versus EC/T, 1.68 (95% CI, 1.25 to 2.27), P = .0006; and EC/T versus CEF, 0.89 (95% CI, 0.64 to 1.22), P = .46. Three-year RFS rates for CEF, EC/T, and AC/T are 90.1%, 89.5%, and 85.0%, respectively. There was more febrile neutropenia with CEF (22.3%) and EC/T (16.4%) compared with AC/T (4.8%), but more neuropathy with the last two regimens. CONCLUSION Three-weekly AC/T is significantly inferior to CEF or EC/T in terms of RFS. It is too early to detect any difference between CEF and dose-dense EC/T.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".