Cost-Utility Analysis of Primary Prophylaxis Versus Secondary Prophylaxis With Granulocyte Colony-Stimulating Factor in Elderly Patients With Diffuse Aggressive Lymphoma Receiving Curative-Intent Chemotherapy
Bibliographic record
Abstract
PURPOSE: The 2006 American Society of Clinical Oncology (ASCO) guideline recommended primary prophylaxis (PP) with granulocyte colony-stimulating factor (G-CSF) instead of secondary prophylaxis (SP) for elderly patients with diffuse aggressive lymphoma receiving chemotherapy. We examined the cost-effectiveness of PP when compared with SP. METHODS: We conducted a cost-utility analysis to compare PP to SP for diffuse aggressive lymphoma. We used a Markov model with an eight-cycle chemotherapy time horizon with a government-payer perspective and Ontario health, economic, and cost data. Data for efficacies of G-CSF, probabilities, and utilities were obtained from published literature. Probabilistic sensitivity analysis (PSA) was conducted. RESULTS: The incremental cost-effectiveness ratio of PP to SP was $700,500 per quality-adjusted life-year (QALY). One-way sensitivity analyses (willingness-to-pay threshold = $100,000/QALY) showed that if PP were to be cost-effective, the cost of hospitalization for febrile neutropenia (FN) had to be more than $31,138 (2.5 × > base case), the cost of G-CSF per cycle less than $960 (base case = $1,960), the risk of first-cycle FN more than 47% (base case = 24%), or the relative risk reduction of FN with G-CSF more than 91% (base case = 41%). Our result was robust to all variables. PSA revealed a 10% probability of PP being cost-effective over SP at a willingness-to-pay threshold of $100,000/QALY. CONCLUSION: PP is not cost-effective when compared with SP in this population. PP becomes attractive only if the cost of hospitalization for FN is significantly higher or the cost of G-CSF is significantly lower.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 |
| 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".