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Record W4405764199 · doi:10.1177/17588359241308466

Analysis of outcomes in resected early-stage NSCLC with rare targetable driver mutations

2024· article· en· W4405764199 on OpenAlexaff
Nadia Ghazali, Jamie Feng, Katrina Hueniken, Khaleeq Khan, Karmugi Balaratnam, Thomas K. Waddell, Kazuhiro Yasufuku, Andrew Pierre, Laura Donahoe, Elliot Wakeam, Marcelo Cypel, Jonathan Yeung, Shaf Keshavjee, Marc de Perrot, Natasha B. Leighl, Geoffrey Liu, Penelope A. Bradbury, Adrian G. Sacher, Lawson Eng, Tracy Stockley, Ming‐Sound Tsao, Frances A. Shepherd

Bibliographic record

VenueTherapeutic Advances in Medical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineAnaplastic lymphoma kinaseOncologyInternal medicineEpidermal growth factor receptorLung cancerCancer researchROS1CrizotinibStage (stratigraphy)Targeted therapyCancerAdenocarcinomaBiology

Abstract

fetched live from OpenAlex

Background: Given advancements in adjuvant treatments for non-small-cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK)-targeted therapies, it is important to consider postoperative targeted therapies for other early-stage oncogene-addicted NSCLC. Exploring baseline outcomes for early-stage NSCLC with these rare mutations is crucial. Objectives: This study aims to assess relapse-free survival (RFS) and overall survival (OS) in patients with resected early-stage NSCLC with rare targetable driver mutations. Methods: This retrospective single-center study identified stage I–III NSCLC patients with rare targetable mutations who underwent curative surgery. Tissue-based molecular profiling identified mutations in KRASG12C, EGFR Exon20, Erb-B2 receptor tyrosine kinase 2 ( ERBB2), ALK, ROS1, B-Raf proto-oncogene ( BRAF) V600E, mesenchymal–epithelial transition factor ( MET) exon14 skipping, and rearranged during transfection ( RET). Baseline patient and tumor characteristics, mutation subtype, and TP53 co-mutation were correlated with RFS and OS using Cox regression. The KRASG12C cohort was used as the reference for survival comparisons. Results: Among 225 patients, mutations included the following: KRASG12C ( n = 101, 45%), MET exon 14 skipping ( n = 26, 12%), EGFR Exon 20 ( n = 25, 11%), ERBB2 ( n = 25, 11%), ALK fusion ( n = 16, 7%), ROS1 fusion ( n = 14, 6%), BRAF V600E mutation ( n = 13, 6%), and RET fusion ( n = 5, 2%). Five-year survival probabilities were 76% for stage I, 60% for stage II, and 58% for stage III. RFS was shorter across most mutation subgroups compared to KRASG12C, with ROS1 mutations showing significantly poorer RFS (HR 2.70, p = 0.019). By contrast, all mutation subgroups were associated with better OS than KRASG12C. The incidence of brain metastasis was highest in ERBB2 (22% at 5 years). TP53 co-mutation was associated with significantly worse OS (HR 2.35, p = 0.008). Conclusion: While RFS was poorer for most mutations compared to KRASG12C, OS generally was better, suggesting a potential role for postoperative targeted therapies. These findings warrant further investigation through prospective studies and clinical trials to optimize adjuvant treatment strategies for patients with early-stage NSCLC harboring rare driver mutations.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.410
Teacher spread0.395 · 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 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

Citations2
Published2024
Admission routes1
Has abstractyes

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