MétaCan
Menu
Back to cohort
Record W3046818137 · doi:10.1177/1078155220945374

Off-label infusion of biosimilar bevacizumab: A provincial experience

2020· article· en· W3046818137 on OpenAlexaff
Marc Geirnaert, Jacy Howarth, Curtis Kellett, Kristen Martin, Scott Streilein, Chad Ricard, Danica Wasney, Saroj Niraula

Bibliographic record

VenueJournal of Oncology Pharmacy Practice · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBiosimilars and Bioanalytical Methods
Canadian institutionsUniversity of ManitobaCancerCare Manitoba
Fundersnot available
KeywordsBevacizumabBiosimilarMedicinePharmacologySurgeryInternal medicineChemotherapy

Abstract

fetched live from OpenAlex

The product monograph for reference bevacizumab (Avastin) and biosimilar bevacizumab (Mvasi) recommend to infuse the first dose of bevacizumab over 90 min, second dose over 60 min and third and subsequent doses over 30 min. Despite the product monograph recommendations, many institutions adopted an accelerated bevacizumab (Avastin) 0.5 mg/kg/min infusion time. Our province adopted the accelerated infusion time at time of biosimilar bevacizumab (Mvasi) adoption. Our experience with the accelerated infusion time was well tolerated in the first five months of biosimilar bevacizumab adoption across different tumor types.

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)0.002
metaresearch head score (Gemma)0.008
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 score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.092
GPT teacher head0.424
Teacher spread0.332 · 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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Oncology Pharmacy PracticeSame topicBiosimilars and Bioanalytical MethodsFrench-language works237,207