RANDOMIZED PHASE III TRIAL COMPARING EPIRUBICIN/ DOXORUBICIN PLUS DOCETAXEL AND EPIRUBICIN/ DOXORUBICIN PLUS PACLITAXEL AS FIRST LINE TREATMENT IN WOMEN WITH ADVANCED BREAST CANCER
Bibliographic record
Abstract
Background: The purpose of this study was to compare Epirubicin/ doxorubicin plus docetaxel and Epirubicin/ doxorubicin plus paclitaxel as first line treatment in women with advanced breast cancer. Patients and methods: previously untreated patients with advanced breast cancer randomly assigned to recieve Epirubicin 75mg/m2 and docetaxel 75 mg/m2 (ED) 1-hour intravenous (IV) infusion every 21 days, Epirubicin 75 mg/m2 and paclitaxel 175 mg/m2 (EP) 3-hour IV infusion every 21 days, Intravenous bolus injections of doxorubicin 50 mg/m2 and docetaxel 75 mg/m2 (DD) administered as a 1-hour intravenous infusion every 21 days and doxorubicin 50 mg/m2 and paclitaxel 175 mg/m2 (DP) administered as a 1-hour intravenous infusion every 21 days. Previous anthracycline-based neo-adjuvant chemotherapy was allowed if completed ? 1 year before entering the study. Results: Ten women patients were treated on arm ED &EP and median TTP was 10 versus 11 months, 50 women patients were trated on DD & DP cand median TTP was 8.5 versus 9 months respectively. Severe toxicity include grade 3-4 leukopenia (4% versus 2%), neutropenia (20% versus 22%) , anemia (38% versus 34%), thrombocytopenia (18% versus 24%), neurotoxicity (2% versus 6%) with DD and DP, respectively. Conclusion: The DD and DP regimens have similar efficacy but different toxicity. Either regimen can be used as front- line treatment of ABC. But in case of ED and EP regimen was difficult to compare the result due to very small sample size. Keywords: Epirubicin, doxorubicin, docetaxel, paclitaxel, advanced breast cancer, chemotherapy, neurotoxicity.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".