Cost-effectiveness of pegfilgrastim versus filgrastim for prevention of chemotherapy-induced febrile neutropenia in patients with lymphoma: A systematic review
Bibliographic record
Abstract
Abstract Background: Febrile neutropenia (FN) is a prevalent and potentially life-threatening complication in patients with lymphoma receiving myelosuppressive chemotherapy. Pegfilgrastim is more effective than filgrastim as prophylaxis for FN. However, its usage has been limited because of its higher cost. Pegfilgrastim's value for money remains unclear. Objective: To systematically review the cost-effectiveness of pegfilgrastim compared to filgrastim for prevention of chemotherapy-induced FN among patients with lymphoma. Methods: A systematic literature search was conducted in PubMed, EMBASE, Cochrane Library databases, and Google Scholar. Only full-economic evaluations were included in the review. Data extraction was guided by the Consolidated Health Economic Evaluation Reporting Standards checklist, and the quality of reviewed articles was assessed using the Joanna Briggs Institute (JBI) checklist. Cost-effectiveness data were rigorously summarized and synthesized narratively. Costs were adjusted to 2020 US$. Results: We identified eight full economic evaluation studies (two cost-utility analyses, three cost-effectiveness analyses, and three studies reporting cost-effectiveness and cost-utility analyses). Half of these studies were from Europe (n=4), the other half were from Iran, USA, Canada and Singapore. Six studies met >80% of the JBI quality assessment criteria. Cost-effectiveness estimates in the majority (n=6) of these studies were for Non-Hodgkin Lymphoma patients receiving myelosuppressive chemotherapy with high-risk of FN ( > 20%). The studies considered a wide range of baseline FN risk (17-97.4%) and mortality rates (5.8-8.9%). Reported incremental cost-effectiveness ratios ranged from 2,199US$ to 8,871,600US$ per quality-adjusted life-year (QALY) gained, dominant to 44,358 US$ per FN averted, and 4,261US$-7,251US$ per life-year gained. The most influential parameters were medication and hospitalization costs, relative risk of FN, and assumptions of mortality benefit. Conclusions: Pegfilgrastim appears to be cost-effective primary prophylactic for preventing chemotherapy-induced FN in lymphoma patients. he findings could assist clinicians and healthcare decision-makers to make informed decisions regarding resource allocation for the management of chemotherapy-induced FN in settings similar to those studied.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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".