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Record W4414239951 · doi:10.51731/cjht.2025.1224

Osimertinib (Tagrisso)

2025· article· en· W4414239951 on OpenAlexaboutno aff
CDA-AMC

Bibliographic record

VenueCanadian Journal of Health Technologies · 2025
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsnot available
Fundersnot available
KeywordsLung cancerOsimertinibExonDiseaseCancerDrugT790M

Abstract

fetched live from OpenAlex

Canada’s Drug Agency (CDA-AMC) recommends that Tagrisso be reimbursed by public drug plans for the treatment of patients with locally advanced, unresectable (stage III) non–small cell lung cancer (NSCLC) — a stage at which the cancer has spread to nearby areas but cannot be removed by surgery. This applies only to patients whose tumours have specific changes in the EGFR gene, such as exon 19 deletions (Ex19del) or exon 21 L858R substitutions (either alone or in combination with other EGFR mutations), and whose disease has not progressed during or following platinum-based chemoradiation therapy, provided certain conditions are met. Tagrisso should only be covered to treat adult patients with locally advanced unresectable (stage III) nonsquamous NSCLC (the most common subtype of NSCLS, which begins in gland-like cells in the lungs) with documented Ex19del or exon 21 L858R substitutions and who have not had disease progression during or following platinum-based chemoradiation therapy. Only patients who have a good performance status should be eligible for Tagrisso. Tagrisso should only be reimbursed if it is prescribed by clinicians with expertise in treating NSCLC and the cost of Tagrisso is reduced.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.030
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0300.011

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 head0.018
GPT teacher head0.358
Teacher spread0.339 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Health TechnologiesSame topicLung Cancer Treatments and MutationsFrench-language works237,207