Febrile neutropenia with adjuvant docetaxel and cyclophosphamide (TC) chemotherapy for breast cancer.
Bibliographic record
Abstract
e17523 Background: The combination of docetaxel and cyclophosphamide (TC) for adjuvant treatment of early stage breast cancer has been shown to improve overall survival compared with doxorubicin and cyclophosphamide (AC) (Jones et al., 2006). Although cardiotoxicity is avoided with TC, the risk of febrile neutropenia (FN) is higher. For TC, reported rates of FN without prophylactic G-CSF range from 5% in the phase III trial to as high as 50% in retrospective chart reviews. As G-CSF is not covered by our provincial cancer funding agency for primary prophylaxis of FN with TC chemotherapy, we sought to determine the incidence of FN with TC chemotherapy in two comprehensive cancer centres in Ontario, Canada. Methods: Patients who received adjuvant TC chemotherapy between January 1, 2008 and December 31, 2012 were identified through the pharmacy databases. Electronic charts were retrospectively reviewed to abstract patient characteristics, treatment details including G-CSF use, and incidence of FN. Results: Preliminary results from one institution demonstrate that 187 patients were treated with TC over the study period. Of the 74 (40%) patients who did not receive primary G-CSF prophylaxis, 23 (31%) developed FN requiring hospitalization and treatment with intravenous antibiotics. However, none of the 113 patients who received primary G-CSF prophylaxis (funded by the patient or a third party payer) developed FN. Putative risk factors for FN in the absence of G-CSF including age, BSA, BMI, and pre-treatment absolute neutrophil count were examined and will be reported. Conclusions: The FN rate associated with TC chemotherapy exceeds 30%, higher than that reported in the clinical trial. As per ASCO guidelines, primary G-CSF prophylaxis should be given with TC chemotherapy, and in Canada this should be covered by provincial cancer funding agencies.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".