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Record W2789986687 · doi:10.3747/co.25.3867

Standardizing Biomarker Testing for Canadian Patients with Advanced Lung Cancer

2018· article· en· W2789986687 on OpenAlexaffvenueabout
Barbara Melosky, Normand Blais, Parneet Cheema, Christian Couture, Rosalyn A. Juergens, Suzanne Kamel‐Reid, Ming‐Sound Tsao, Paul Wheatley‐Price, Zhaolin Xu, Diana N. Ionescu

Bibliographic record

VenueCurrent Oncology · 2018
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsQueen Elizabeth II Health Sciences CentreDalhousie UniversityUniversity of OttawaJuravinski Cancer CentreInstitut universitaire de cardiologie et de pneumologie de QuébecCentre Hospitalier de l’Université de MontréalUniversité LavalWilliam Osler Health SystemOttawa HospitalUniversity Health NetworkUniversity of TorontoPrincess Margaret Cancer CentreBC Cancer Agency
Fundersnot available
KeywordsMedicineKRASLung cancerOncologyNeuroblastoma RAS viral oncogene homologROS1BiomarkerContext (archaeology)Internal medicineAnaplastic lymphoma kinaseCancerEpidermal growth factor receptorAdenocarcinoma

Abstract

fetched live from OpenAlex

Background: The development and approval of both targeted and immune therapies for patients with advanced non-small cell lung cancer (NSCLS) has significantly improved patient survival rates and quality of life. Biomarker testing for patients newly diagnosed with NSCLS, as well as for patients progressing after treatment with epidermal growth factor receptor (EGFR) inhibitors, is the standard of care in Canada and many parts of the world. Methods: A group of thoracic oncology experts in the field of thoracic oncology met to describe the standard for biomarker testing for lung cancer in the Canadian context, focusing on evidence-based recommendations for standard-of-care testing for EGFR, anaplastic lymphoma kinase (ALK), ROS1, BRAF V600 and programmed death-ligand (PD-L1) at the time of diagnosis of advanced disease and EGFR T790M upon progression. As well, additional exploratory molecules and targets are likely to impact future patient care, including MET exon 14 skipping mutations and whole gene amplification, RET translocations, HER2 (ERBB2) mutations, NTRK, RAS (KRAS and NRAS), as well as TP53. Results: The standard of care must include the incorporation of testing for novel biomarkers as they become available, as it will be difficult for national guidelines to keep pace with technological advances in this area. Conclusions: Canadian patients with NSCLS should be treated equally; the minimum standard of care is defined in this paper.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.586
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

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

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 head0.072
GPT teacher head0.459
Teacher spread0.387 · 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.

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

Citations32
Published2018
Admission routes3
Has abstractyes

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