Cost-effectiveness of Outpatient Management for Febrile Neutropenia in Children With Cancer
Bibliographic record
Abstract
OBJECTIVE: Inpatient management remains the standard of care for treatment of febrile neutropenia (FN) in children with cancer. Clinical data suggest, however, that outpatient management might be a safe and efficacious alternative for patients with low-risk FN episodes. METHODS: A cost-utility model was created to compare 4 treatment strategies for low-risk FN. The base case considered pediatric cancer patients with low-risk FN. The model used a health care payer's perspective and a time horizon of 1 FN episode. Four treatment strategies were evaluated: (1) entire treatment in hospital with intravenous antibiotics (HospIV); (2) early discharge consisting of 48 hours of inpatient observation with intravenous antibiotics followed by oral outpatient treatment (EarlyDC); (3) entirely outpatient management with intravenous antibiotics (HomeIV); and (4) entirely outpatient management with oral antibiotics (HomePO). Outcome measures were quality-adjusted FN episodes (QAFNEs), costs (Canadian dollars), and incremental cost-effectiveness ratios. Parameter uncertainty was assessed with probabilistic sensitivity analyses. RESULTS: The most cost-effective strategy was HomeIV. It was cost-saving ($2732 vs $2757) and more effective (0.66 vs 0.55 QAFNE) as compared with HomePO. EarlyDC was slightly more effective (0.68 QAFNE) but significantly more expensive ($5579) than HomeIV, which resulted in an unacceptably high incremental cost-effectiveness ratio of more than $130 000 per QAFNE. HospIV was the least cost-effective strategy because it was more expensive ($14 493) and less effective (0.65 QAFNE) than EarlyDC. CONCLUSION: The findings of this decision-analytic model indicate that the substantially higher costs of inpatient management cannot be justified on the basis of safety and efficacy considerations or patient/parent preferences.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".