Management of chemotherapy‐induced febrile neutropenia in pediatric oncology patients: A North American survey of pediatric hematology/oncology and pediatric infectious disease physicians
Bibliographic record
Abstract
BACKGROUND: Chemotherapy-induced febrile neutropenia (FN) is traditionally managed with hospital admission for parenteral antibiotics until neutropenia resolves. Recent studies have explored risk stratification and the safety of managing "low-risk" patients as outpatients. Few studies have directly assessed pediatric provider preferences for managing FN. PROCEDURE: We conducted a survey of practicing US and Canadian pediatric hematology/oncology (PHO) and pediatric infectious disease (PID) physicians to assess their FN management preferences using case scenarios with varying risk profiles. RESULTS: Twenty-one percent (n = 186) of PHO and 32% (n = 123) of PID physicians completed the survey. Overall, both groups of providers agreed regarding which patients with FN could be managed outpatient. For a child with acute lymphoblastic leukemia receiving maintenance chemotherapy with an absolute neutrophil count (ANC) of 400 cells/μl, 35% (n = 66) of PHO and 49% (n = 60) of PID physicians would consider outpatient management (P = 0.02). Of those physicians selecting inpatient management, 41% (n = 49) of PHO and 52% (n = 33) of PID physicians would be willing to discharge the patient without an increase in ANC, if afebrile with a negative blood culture (P = 0.16). For a similar patient with an ANC of 100 cells/μl, only 23% (n = 35) of PHO and 42% (n = 39) of PID physicians would consider discharge without an increase in ANC (P = 0.002). CONCLUSIONS: Despite the lack of established guidelines for low-risk pediatric FN, a significant proportion of North American physicians report willingness to modify traditional management. This reinforces the need for evidence-based low-risk criteria and outpatient management guidelines to optimize consistency of care for these patients.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".