Real-World Adjuvant TAC or FEC-D for HER2-Negative Node-Positive Breast Cancer in Women Less Than 50 Years of Age
Bibliographic record
Abstract
PURPOSE: We compared the efficacy, toxicity, and use of granulocyte colony-stimulating factor (g-csf) with tac (docetaxel-doxorubicin-cyclophosphamide) and fec-d (5-fluorouracil-epirubicin-cyclophosphamide followed by docetaxel) in women less than 50 years of age. METHODS: The study included all women more than 18 years but less than 50 years of age with her2-negative, node-positive, stage ii or iii breast cancer diagnosed in Alberta between 2008 and 2012 who received tac (n = 198) or fec-d (n = 274). RESULTS: The patient groups were well-balanced, except that radiotherapy use was higher in the tac group (91.9% vs. 79.9%, p < 0.001). At a median follow-up of 49.6 months, disease-free survival was 91.4% for tac and 92.0% for fec-d (p = 0.76). Overall survival (os) was 96% with tac and 95.3% with fec-d (p = 0.86).The incidences of grades 3 and 4 toxicities were similar in the two groups (all p > 0.05). Overall, febrile neutropenia (fn) was reported in 11.6% of tac patients and 15.7% of fec-d patients (p = 0.26). However, use of g-csf was higher in the tac group than in the fec-d group (96.4% vs. 71.5%, p < 0.001). Hospitalization for fn was required in 10.5% of tac patients and 13.0% of fec-d patients (p = 0.41). In g-csf-supported and -unsupported patients receiving tac, fn occurred at rates of 11.1% and 33.3% respectively (p = 0.08); in patients receiving the fec portion of fec-d, those proportions were 2.9% and 8.1% respectively (p = 0.24); and in patients receiving docetaxel after fec, the proportions were 4.1% and 17.6% respectively (p < 0.001). CONCLUSIONS: In women less than 50 years of age receiving adjuvant tac or fec-d, we observed no differences in efficacy or other nonhematologic toxicities. Based on the timing and rates of fn, use of prophylactic g-csf should be routine for the docetaxel-containing portion of treatment; however, prophylactic g-csf could potentially be avoided during the fec portion of fec-d treatment.
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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 | 0.000 | 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) | 0.000 | 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".