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Record W1975745084 · doi:10.1586/erp.12.64

Pegfilgrastim: a review of the pharmacoeconomics for chemotherapy-induced neutropenia

2012· review· en· W1975745084 on OpenAlexaff
Pierre Rofail, Mariam M. Tadros, Riham Ywakim, Mina Tadrous, Allison Krug, Leon E. Cosler

Bibliographic record

VenueExpert Review of Pharmacoeconomics & Outcomes Research · 2012
Typereview
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPegfilgrastimFilgrastimMedicinePharmacoeconomicsNeutropeniaChemotherapyIntensive care medicineFebrile neutropeniaOncologyInternal medicine

Abstract

fetched live from OpenAlex

For oncology patients, febrile neutropenia (FN) can be a serious and costly toxicity of chemotherapy, often forcing a reduction in chemotherapy dose intensity and/or duration. Several therapeutic agents are used to reduce the occurrence of neutropenic episodes: granulocyte colony-stimulating factors (G-CSFs) and granulocyte-macrophage colony-stimulating factors. Appropriate administration of colony-stimulating factors reduces the risk of FN episodes and the costs associated with FN treatment. In the USA, the two most commonly used G-CSFs are filgrastim and the longer-acting pegfilgrastim. This pharmacoeconomic review of pegfilgrastim briefly considers some of the early research of G-CSFs, then focuses on the most recent comparative studies of pegfilgrastim against the backdrop of forthcoming US patent expiration for both products. The authors conclude with commentary on the market for pegfilgrastim in light of the growing debate surrounding the optimal selection of patients, treatment costs and future alternatives for the use of these agents in chemotherapy.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.733
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.005
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.132
GPT teacher head0.581
Teacher spread0.449 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations12
Published2012
Admission routes1
Has abstractyes

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