A phase I/II trial of epirubicin and docetaxel in locally advanced breast cancer (LABC) on 2-weekly or 3-weekly schedules: NCIC CTG MA.22
Bibliographic record
Abstract
This phase I/II neoadjuvant trial (ClinicalTrials.gov identifier NCT00066443) determined maximally-tolerated doses (MTD), dose-limiting toxicities, response-to-therapy, and explored the role of novel response biomarkers. MA.22 accrued T3N0, any N2 or N3, and T4 breast cancer patients. Treatment was 6 cycles of 3-weekly (Schedule A; N = 47) or 8 cycles of 2-weekly (Schedule B; N = 46) epirubicin/docetaxel chemotherapy in sequential phase I/II studies, with growth factor support. In phase I of each schedule, MTDs were based on DLT. In phase II, clinical responses (CR/PR) and pathologic complete responses (pCR) were assessed. Tumor biopsy cores were obtained pre-, mid-, and post-treatment: 3 for pathologic assessment; 3 for microarray studies. DLT for Schedule A was febrile neutropenia at 105 mg/m(2) epirubicin and 75 mg/m(2) docetaxel; for schedule B, it was fatigue at 75 mg/m(2) for both agents. Phase II doses were 90 mg/m(2) epirubicin/75 mg/m(2) docetaxel for Schedule A and 60 mg/m(2) (both agents) for Schedule B. Schedule A CR/PR and pCR rates were 90 and 10 %, with large reductions in tumor RNA content and integrity following treatment; Schedule B results were 93 and 0 %, with smaller reductions in RNA quality. Pre-treatment expression of several genes was associated with clinical response, including those within a likely amplicon at 17q12 (ERBB2, TCAP, GSDMB, and PNMT). The combination regimens had acceptable toxicity, good clinical response, induction of changes in tumor RNA content and integrity. Pre-treatment expression of particular genes was associated with clinical responses, including several near 17q12, which with ERBB2, may better identify chemoresponsiveness.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.007 | 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".