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Record W4322500492 · doi:10.1038/s41467-023-35962-x

Analysis of acquired resistance mechanisms to osimertinib in patients with EGFR-mutated advanced non-small cell lung cancer from the AURA3 trial

2023· article· en· W4322500492 on OpenAlexaff
Juliann Chmielecki, Tony Mok, Yi‐Long Wu, Ji‐Youn Han, Myung‐Ju Ahn, Suresh S. Ramalingam, Thomas John, Isamu Okamoto, James Chih‐Hsin Yang, Frances A. Shepherd, Krishna C. Bulusu, Gianluca Laus, Barbara Collins, J. Carl Barrett, Ryan J. Hartmaier, Vassiliki A. Papadimitrakopoulou

Bibliographic record

VenueNature Communications · 2023
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
FundersNational Cancer InstituteAstraZeneca
KeywordsOsimertinibT790MLung cancerDiscontinuationMedicineEpidermal growth factor receptorOncologyResistance mutationInternal medicineTyrosine-kinase inhibitorCancer researchChemotherapyCancerBiologyErlotinibGeneGefitinibGeneticsPolymerase chain reaction

Abstract

fetched live from OpenAlex

Osimertinib, an epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI), potently and selectively inhibits EGFR-TKI-sensitizing and EGFR T790M resistance mutations. This analysis evaluates acquired resistance mechanisms to second-line osimertinib (n = 78) in patients with EGFR T790M advanced non-small cell lung cancer (NSCLC) from AURA3 (NCT02151981), a randomized phase 3 study comparing osimertinib with chemotherapy. Plasma samples collected at baseline and disease progression/treatment discontinuation are analyzed using next-generation sequencing. Half (50%) of patients have undetectable plasma EGFR T790M at disease progression and/or treatment discontinuation. Fifteen patients (19%) have >1 resistance-related genomic alteration; MET amplification (14/78, 18%) and EGFR C797X mutation (14/78, 18%).

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)0.001
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.331
Teacher spread0.319 · 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

Citations173
Published2023
Admission routes1
Has abstractyes

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Same venueNature CommunicationsSame topicLung Cancer Treatments and MutationsFrench-language works237,207