Randomised feasibility trial to compare three standard of care chemotherapy regimens for early stage triple-negative breast cancer (REaCT-TNBC trial)
Bibliographic record
Abstract
INTRODUCTION: Despite the importance of chemotherapy in the treatment of early stage triple negative breast cancer (TNBC), no one optimal regimen has been identified. We conducted a pilot trial comparing outcomes for the three most commonly used chemotherapy regimens to assess the feasibility of conducting a larger definitive trial. METHODS: Using integrated consent, newly diagnosed TNBC patients were randomised to one of three standard regimens: dose-dense doxorubicin-cyclophosphamide then paclitaxel, doxorubicin-cyclophosphamide then weekly paclitaxel or 5-FU-epirubicin-cyclophosphamide then docetaxel. Feasibility endpoints included; physician engagement, accrual rates, physician compliance and patient satisfaction with the integrated consent model. Our anticipated pilot trial sample size was 35 randomised patients in one year. RESULTS: Between August 30th, 2016 and January 31st 2017, 2 patients met eligibility and were randomised. A survey of 10 participating oncologists was performed to identify potential strategies to enhance accrual. Most investigators (9/10) believed that the best regimen for TNBC was unknown, and 4/10 felt this was a pressing clinical question. Physicians' responses suggested that poor accrual was due to: a lack of interest in some study arms as oncologists already had a preferred regimen (4/10) and concerns about trial demands in busy clinics (3/10). The pilot feasibility endpoints were not met and the study was closed. CONCLUSIONS: Despite initial interest in the trial question and multiple investigators agreeing to approach patients, this trial failed to meet feasibility endpoints. The reasons for poor accrual were multiple and require further evaluation if this important patient-centred question is to be answered. TRIAL REGISTRATION: ClinicalTrials.gov NCT02688803.
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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 | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".