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Record W2979591734 · doi:10.1182/blood.v124.21.737.737

Granulocyte-Colony Stimulating Factor (G-CSF) in Secondary Prophylaxis for Advanced-Stage Hodgkin Lymphoma Treated with ABVD Chemotherapy: A Cost-Effectiveness Analysis

2014· article· en· W2979591734 on OpenAlexaffabout
Matthew C. Cheung, Anca Prica, J Graczyk, Rena Buckstein, Kelvin Chan

Bibliographic record

VenueBlood · 2014
Typearticle
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreMount Sinai HospitalPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineABVDFebrile neutropeniaGranulocyte colony-stimulating factorChemotherapy regimenNeutropeniaInternal medicineOncologyIntensive care medicineSurgeryChemotherapy

Abstract

fetched live from OpenAlex

Abstract Background: G-CSF is commonly administered to patients with advanced-stage Hodgkin Lymphoma (HL) with severe neutropenia during therapy, although such an approach does not appear to provide a survival benefit. Although the therapy may reduce episodes of febrile neutropenia, any benefit might be offset by increased costs and the potential for increased bleomycin lung toxicity with G-CSF exposure, suggested in prior studies (Martin et al., JCO 2005). As an alternative to secondary prophylaxis, single institution studies have suggested that ABVD chemotherapy can be administered without G-CSF support, treatment delays, or dose reductions. The relative costs and benefits of such an approach compared to routine use of G-CSF is unknown. Methods: We constructed a Markov decision-analytic model to compare the strategy of secondary prophylaxis with G-CSF to a strategy of "no G-CSF" in response to therapy-related severe neutropenia for a cohort of 40 year-old patients with clinical stage IIB to IV HL treated with 8 cycles of ABVD. A 2-year time horizon was simulated. Baseline probability estimates and utilities were derived from a systematic review of relevant published studies. Direct medical costs were obtained from publicly available administrative databases or from the literature and applied to the health states. All costs and benefits were discounted by 3%. A Canadian public health payer's perspective was considered and costs were presented in 2013 Canadian dollars. Key variables were subjected to sensitivity analyses. Results: The quality-adjusted life years (QALYs) attained with the G-CSF and "no G-CSF" strategies were 1.403 and 1.416, respectively, for a net expected benefit of 0.013 QALYs associated with omitting G-CSF. Costs for the strategies with and without G-CSF were $38,971 and $33,982, respectively, with a cost savings of $4,989 when G-CSF is omitted. In the base case analysis, the "no G-CSF" strategy was associated with both cost savings and improved quality-adjusted outcomes compared to secondary prophylaxis; therefore, the "no G-CSF" approach was dominant. This analysis was robust to one-way sensitivity analyses involving all key variables; the "no-GCSF" strategy remained dominant even when the cost of G-CSF was zero (Figure 1). In probabilistic sensitivity analysis (1000 simulations), the "no-G-CSF" strategy remained dominant in all pairwise simulations compared to an approach with G-CSF for secondary prophylaxis (Figure 2). Conclusions: For patients with severe neutropenia during ABVD chemotherapy for advanced-stage HL, a strategy without G-CSF support, treatment delay or dose reduction is associated with improved quality-adjusted outcomes and cost savings and is the preferred approach. Figure 1 Figure 1. Figure 2 Figure 2. Disclosures No relevant conflicts of interest to declare.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.008
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.016
GPT teacher head0.291
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2014
Admission routes2
Has abstractyes

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