ORIGINAL ARTICLE Real world experience with dose dense ac-paclitaxel: Two canadian cancer centers ’ experience
Bibliographic record
Abstract
Early breast cancer treatment with dose dense Adriamycin-Cyclophosphamide and Paclitaxel (AC-P) has been shown to increase survival. However, it is commonly associated with neutropenia, anemia or both. This retrospective chart review study was done to evaluate the real world experience with this regimen and included a series of 83 adult women from the London Regional Cancer Program and 50 patients from the Windsor Regional Cancer Center who were treated with dose dense adjuvant AC-P for early breast cancer from January 2009 to August 2012. Toxicities like febrile neutropenia (FN) and anemia based on NCIC-CTC v2 criteria and grades were recorded along with the use of erythropoietin stimulating agents (ESA), Neupogen or Neulasta, and blood transfusion. The majority of our patients (88.72%) were able to complete all 8 cycles of AC-Taxol, although 32 of these patients (24.06%) experienced delay during their treatment. Grade 3 anemia was seen in one patient after cycle #4 and increased to two patients after both cycles 5 and 7. Only one patient developed grade 4 anemia, observed in the 5th cycle. Blood transfusion was given to sixteen patients and three patients received ESA. The incidence of febrile neutropenia was only
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".