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Record W2808553117 · doi:10.3747/co.25.3761

Circulating Tumour DNA in EGFR-Mutant Non-Small-Cell Lung Cancer

2018· review· en· W2808553117 on OpenAlexaffvenue
Michael Cabanero, Ming‐Sound Tsao

Bibliographic record

VenueCurrent Oncology · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
FundersPeking UniversityPeking University People's HospitalNational Natural Science Foundation of China
KeywordsT790MMedicineLung cancerDigital polymerase chain reactionLiquid biopsyMutationCancer researchTumour heterogeneityCirculating tumor DNACancerTargeted therapyCell-free fetal DNACOLD-PCRComputational biologyBioinformaticsOncologyEpidermal growth factor receptorGeneInternal medicineBiologyPolymerase chain reactionPoint mutationGenetics

Abstract

fetched live from OpenAlex

The advent of targeted therapy in non-small-cell lung cancer (NSCLC) has made the routine molecular diagnosis of EGFR mutations crucial for optimal patient management. Obtaining tumour tissue for biomarker testing, especially in the setting of re-biopsy, can present many challenges. A potential alternative source of tumour dna is circulating cell-free tumour-derived DNA (CTDNA). Although CTDNA is present in low quantities in plasma, the convenience of sample acquisition and the increasing reliability of detection methods make this approach a promising one. The various performance characteristics of both digital and nondigital platforms are still variable, and a standardized approach is needed that will make those platforms reliable clinical tools for the detection of EGFR sensitizing mutations and resistance mutations, including the T790M resistance mutation. Information derived from ctdna can be used to assess tumour burden, to identify genomic-based resistance mechanisms, and to track dynamic changes during therapy.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.078
GPT teacher head0.402
Teacher spread0.324 · 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

Citations39
Published2018
Admission routes2
Has abstractyes

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