Canadian Supportive Care Recommendations for the Management of Neutropenia in Patients with Cancer
Bibliographic record
Abstract
Hematologic toxicities of cancer chemotherapy are common and often limit the ability to provide treatment in a timely and dose-intensive manner. These limitations may be of utmost importance in the adjuvant and curative intent settings. Hematologic toxicities may result in febrile neutropenia, infections, fatigue, and bleeding, all of which may lead to additional complications and prolonged hospitalization. The older cancer patient and patients with significant comorbidities may be at highest risk of neutropenic complications. Colony-stimulating factors (csfs) such as filgrastim and pegfilgrastim can effectively attenuate most of the neutropenic consequences of chemotherapy, improve the ability to continue chemotherapy on the planned schedule, and minimize the risk of febrile neutropenia and infectious morbidity and mortality. The present consensus statement reviews the use of csfs in the management of neutropenia in patients with cancer and sets out specific recommendations based on published international guidelines tailored to the specifics of the Canadian practice landscape. We review existing international guidelines, the indications for primary and secondary prophylaxis, the importance of maintaining dose intensity, and the use of csfs in leukemia, stem-cell transplantation, and radiotherapy. Specific disease-related recommendations are provided related to breast cancer, non-Hodgkin lymphoma, lung cancer, and gastrointestinal cancer. Finally, csf dosing and schedules, duration of therapy, and associated acute and potential chronic toxicities are examined.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".