Adjuvant Docetaxel for Node-Positive Breast Cancer
Bibliographic record
Abstract
BACKGROUND: We compared docetaxel plus doxorubicin and cyclophosphamide (TAC) with fluorouracil plus doxorubicin and cyclophosphamide (FAC) as adjuvant chemotherapy for operable node-positive breast cancer. METHODS: We randomly assigned 1491 women with axillary node-positive breast cancer to six cycles of treatment with either TAC or FAC as adjuvant chemotherapy after surgery. The primary end point was disease-free survival. RESULTS: At a median follow-up of 55 months, the estimated rates of disease-free survival at five years were 75 percent among the 745 patients randomly assigned to receive TAC and 68 percent among the 746 randomly assigned to receive FAC, representing a 28 percent reduction in the risk of relapse (P=0.001) in the TAC group. The estimated rates of overall survival at five years were 87 percent and 81 percent, respectively. Treatment with TAC resulted in a 30 percent reduction in the risk of death (P=0.008). The incidence of grade 3 or 4 neutropenia was 65.5 percent in the TAC group and 49.3 percent in the FAC group (P<0.001); rates of febrile neutropenia were 24.7 percent and 2.5 percent, respectively (P<0.001). Grade 3 or 4 infections occurred in 3.9 percent of the patients who received TAC and 2.2 percent of those who received FAC (P=0.05); no deaths occurred as a result of infection. Two patients in each group died during treatment. Congestive heart failure and acute myeloid leukemia occurred in less than 2 percent of the patients in each group. Quality-of-life scores decreased during chemotherapy but returned to baseline levels after treatment. CONCLUSIONS: Adjuvant chemotherapy with TAC, as compared with FAC, significantly improves the rates of disease-free and overall survival among women with operable node-positive breast cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".