A Multi-Centre Randomized Study Comparing Two Standard of Care Chemotherapy Regimens for Lower-Risk HER2-Positive Breast Cancer
Bibliographic record
Abstract
BACKGROUND: Neither paclitaxel plus trastuzumab (P-H) nor docetaxel-cyclophosphamide plus trastuzumab (TC-H) have been prospectively compared in HER2-positive early-stage breast cancer (EBC). A randomized trial was performed to assess the feasibility of a larger study. METHODS: Lower-risk HER2-positive EBC patients were randomized to either P-H or TC-H treatment arms. The co-primary feasibility outcomes were: ≥75% patient acceptability rate, active trial participation of ≥50% of medical oncologists, ≥75% and ≥90% treatment completion, and receipt rate of planned cycles of chemotherapy, respectively. SECONDARY OUTCOMES: Febrile neutropenia (FN) rate, treatment-related hospitalizations, health-related quality of life (HR-QoL) questionnaires. Analyses were performed by per protocol and intention-to-treat. RESULTS: Between May 2019 and March 2021, 49 of 52 patients agreed to study participation (94% acceptability rate). Fifteen (65%) of 23 medical oncologists approached patients. Rates of FN were higher (8.3% vs. 0%) in the TC-H vs. P-H arm. Median (IQR) changes in scores from baseline in FACT-Taxane Trial Outcome Index at 24 weeks were -4 (-10, -1) vs. -6.5 (-15, -2) for TC-H and P-H arms, respectively. CONCLUSIONS: A randomized trial comparing P-H and TC-H was feasible. Expansion to a larger trial would be feasible to explore patient-reported outcomes of these adjuvant HER2 chemotherapy regimens.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".