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Early clearance of plasma EGFR mutations as a predictor of response to osimertinib in the AURA3 trial.

2018· article· en· W2890739427 on OpenAlexaff
Frances A. Shepherd, Vassiliki A. Papadimitrakopoulou, Tony Mok, Yi‐Long Wu, Ji‐Youn Han, Myung‐Ju Ahn, Suresh S. Ramalingam, Martin Sebastian, Willemijn S.M.E. Theelen, Gianluca Laus, Barbara Collins, Aleksandra Markovets, Kenneth S. Thress, Geoffrey R. Oxnard

Bibliographic record

VenueJournal of Clinical Oncology · 2018
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsOsimertinibT790MMedicineInternal medicineOncologyLung cancerClinical trialAcquired resistanceGastroenterologyCancerEpidermal growth factor receptorGefitinibErlotinib

Abstract

fetched live from OpenAlex

9027 Background: In the Phase III AURA3 trial (NCT02151981), osimertinib, a third-generation EGFR-TKI, had significantly greater efficacy than platinum-pemetrexed in patients (pts) with advanced NSCLC and T790M-mediated acquired resistance to first-line EGFR-TKI. We investigate whether the presence of plasma EGFR mutations at 3 and 6 wks post-osimertinib treatment (80 mg, once daily) is associated with clinical outcomes, and identify pre-existing genomic aberrations that may impact outcomes. Methods: EGFR mutation analysis (Ex19del/L858R/T790M) was conducted at baseline, wks 3 and 6, by droplet digital (dd)PCR (Biodesix). Next generation sequencing (NGS, Guardant Health; 73 genes) was conducted on baseline plasma samples to explore mechanisms of innate resistance. Clinical outcomes (median progression-free survival [mPFS], objective response rate [ORR]) were investigator assessed, per RECIST 1.1. Results: Of 207 pts with a valid plasma ddPCR result at baseline (all T790M+), 150 had detectable EGFR-TKI sensitizing mutations (EGFRm; Ex19del/L858R) and 57 did not. mPFS was 14.0 mo (95% CI 12.4, not calculable) in pts without detectable baseline EGFRm vs 8.3 mo (95% CI 6.9, 10.9) in pts with detectable baseline EGFRm; EGFRm allelic fraction in baseline plasma was not related to ORR or mPFS. Of the 129 pts with baseline EGFRm and evaluable plasma samples at wk 3, 48 had detectable EGFRm (EGFRm+) and 81 had undetectable EGFRm (EGFRm-). mPFS was 5.7 mo (95% CI 4.1, 9.7) in pts EGFRm+ vs 10.9 mo (95% CI 8.3, 12.7) in pts EGFRm-; hazard ratio (HR) 2.0 (95% CI 1.3, 3.2), p = 0.001; HR > 1 favors pts EGFRm-. ORR was 50% vs 82%, respectively. A similar trend was observed at wk 6 (n = 132): PFS, HR 2.8 (95% CI 1.8, 4.3), p < 0.0001. NGS of baseline plasma showed no association between pre-existing genomic aberrations (TP53, BRAF, KRAS, MET/HER2 amp) and clinical outcome; additional analyses are ongoing. Conclusions: In pts with tissue T790M+ NSCLC and detectable baseline plasma EGFRm, continued presence of EGFRm at wks 3 and 6 was associated with less favorable outcomes with osimertinib. Early dynamic changes of plasma EGFR mutations may predict clinical outcome in pts receiving osimertinib for T790M+ NSCLC. Clinical trial information: NCT02151981.

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)0.001
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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.099
GPT teacher head0.525
Teacher spread0.426 · 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".

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Citations32
Published2018
Admission routes1
Has abstractyes

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