MétaCan
Menu
Back to cohort
Record W2808333976 · doi:10.1001/jamaoncol.2018.0775

Association of <i>ERBB</i> Mutations With Clinical Outcomes of Afatinib- or Erlotinib-Treated Patients With Lung Squamous Cell Carcinoma

2018· article· en· W2808333976 on OpenAlexaff
Glenwood Goss, Enriqueta Felip, Manuel Cobo, Shun Lü, Konstantinos Syrigos, Ki Hyeong Lee, Erdem Göker, Vassilis Georgoulias, Wěi Li, Salih Zeki Güçlü, Dolores Isla, Young Joo Min, Alessandro Morabito, Andrea Ardizzoni, Shirish M. Gadgeel, Andrea Fülöp, Claudia Bühnemann, Neil Gibson, Nicole Krämer, Flavio Solca, A. Cseh, E. Ehrnrooth, Jean‐Charles Soria

Bibliographic record

VenueJAMA Oncology · 2018
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsAfatinibMedicineErlotinibOncologyInternal medicineLung cancerGefitinibBasal cellCarcinomaErbBEpidermal growth factor receptorCancer

Abstract

fetched live from OpenAlex

Importance: Treatment choice for lung squamous cell carcinoma could be aided by identifying predictive biomarkers. Objective: To assess whether patient outcomes in the LUX-Lung 8 trial were associated with ERBB gene family member aberrations in tumor specimens. Design, Setting, and Participants: Ad hoc secondary analysis of the LUX-Lung 8 trial conducted at 183 centers in 23 countries from March 30, 2012, to January 30, 2014. Eligible patients had stage IIIB or IV lung squamous cell carcinoma with progressive disease after 4 or more cycles of platinum-based chemotherapy. Tumor genetic analysis (TGA) was performed using next-generation sequencing in a cohort enriched for patients with progression-free survival (PFS) of more than 2 months. Epidermal growth factor receptor (EGFR) expression levels were assessed by immunohistochemistry in a separate cohort of patients from the LUX-Lung 8 population. Associations of PFS and overall survival (OS) with ERBB gene alterations and EGFR expression levels were assessed. This analysis was conducted from February 26, 2015, to June 12, 2017. Interventions: Patients were randomized 1:1 to treatment with afatinib dimaleate (40 mg/d; n = 398) or erlotinib hydrochloride (150 mg/d; n = 397). Main Outcomes and Measures: Overall survival, PFS, pooled and individual ERBB gene mutations, ERBB copy number alterations, and EGFR expression. Results: Tumor specimens from 245 patients were eligible for next-generation sequencing (TGA subset: 132 patients treated with afatinib; 113 patients treated with erlotinib). In this population, outcomes were improved with afatinib vs erlotinib treatment (PFS: median, 3.5 vs 2.5 months; hazard ratio [HR], 0.69; 95% CI, 0.51-0.92; P = .01; OS: median, 8.4 vs 6.6 months; HR, 0.81; 95% CI, 0.62-1.05; P = .12). Of 245 patients in the TGA subset, 53 (21.6%) had tumors with 1 or more ERBB mutations. Among afatinib-treated patients, PFS (median, 4.9 vs 3.0 months; HR, 0.62; 95% CI, 0.37-1.02; P = .06) and OS (median, 10.6 vs 8.1 months; HR, 0.75; 95% CI, 0.47-1.17; P = .21) were longer among those with ERBB mutation-positive disease than among those without. The presence of HER2 mutations was associated with favorable PFS and OS following afatinib vs erlotinib treatment. There was no apparent association between copy number alteration or EGFR expression level and outcome. Conclusions and Relevance: Next-generation sequencing may help identify patients with lung squamous cell carcinoma who would derive additional benefit from treatment with afatinib. The role of ERBB mutations, particularly HER2 mutations, as predictive biomarkers for afatinib treatment in this setting warrants further evaluation. Trial Registration: ClinicalTrials.gov Identifier: NCT01523587.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.376

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.016
GPT teacher head0.358
Teacher spread0.342 · 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

Citations54
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJAMA OncologySame topicLung Cancer Treatments and MutationsFrench-language works237,207