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Evaluation of VeriStrat, a serum proteomic test, in the randomized, open-label, phase 3 LUX-Lung 8 (LL8) trial of afatinib (A) versus erlotinib (E) for the second-line treatment of advanced squamous cell carcinoma (SCC) of the lung.

2016· article· en· W2654683002 on OpenAlexaff
Glenwood Goss, Ki Hyeong Lee, Enriqueta Felip, Manuel Cobo, Konstantinos N. Syrigos, Erdem Göker, Vassilis Georgoulias, Salih Zeki Güçlü, Dolores Isla, Young Joo Min, Alessandro Morabito, Sandra Close, Nicholas Dupuis, Vikram K. Chand, Flavio Solca, Nicole Krämer, Neil Gibson, E. Ehrnrooth, Jean‐Charles Soria

Bibliographic record

VenueJournal of Clinical Oncology · 2016
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineInternal medicineAfatinibErlotinibGastroenterologyPopulationLung cancerClinical trialOncologyCancerEpidermal growth factor receptor

Abstract

fetched live from OpenAlex

e20510 Background: Treatment (tx) options for patients (pts) with advanced SCC of the lung after progression on platinum-based chemotherapy are limited. In LL8, the irreversible ErbB family blocker, A, significantly improved OS, PFS and disease control rate vs E, a reversible EGFR TKI, in 795 pts with SCC of the lung. VeriStrat is a serum protein test that utilizes MALDI-TOF mass spectrometry to assign a ‘GOOD' (VS-G) or ‘POOR' (VS-P) classification and has demonstrated prognostic and predictive utility for EGFR targeted therapies in NSCLC.1 Here, the predictive ability of VeriStrat was tested in LL8; OS was the primary efficacy variable. Methods: Pre-tx serum samples, blinded to clinical outcome, were classified as VS-G or VS-P based on predefined reference groups. Clinical outcomes were analyzed with respect to VeriStrat status in the overall population (all pts with both clinical and VeriStrat data) and in predefined subgroups. Results: 675 pts were classified (VS-G: 412; VS-P: 263). In the VS-G group, median OS was 11.5 mo for A and 8.9 mo for E (HR [95% CI] 0.79 [0.63–0.98]; p = 0.03); median PFS was 3.3 mo for A and 2.0 mo for E (HR [95% CI] 0.73 [0.59–0.92]; p = 0.005). In the VS-P group, median OS was 4.7 mo for A and 4.8 mo for E (HR [95% CI] 0.90 [0.70–1.16]; p = n.s.); median PFS was 1.9 mo for both A and E (HR [95% CI] 0.96 [0.73–1.27]; p = n.s.). In pts treated with A, both OS (HR [95% CI] 0.40 [0.31–0.51]; p < 0.0001) and PFS (HR [95% CI] 0.56 [0.43–0.72]; p < 0.0001) were longer in the VS-G group vs the VS-P group. Multivariate analysis showed that VeriStrat was an independent predictor of OS and PFS in pts treated with A, regardless of ECOG PS, best response to first-line therapy, age and race. However, there was no interaction between VeriStrat classification and tx group for OS (pint = 0.53) or PFS (pint = 0.12). Conclusions: In LL8, VeriStrat has a strong independent stratification effect in pts with relapsed/refractory SCC of the lung treated with A. In these difficult to treat pts, A conferred significantly better OS and PFS than E in the VS-G group, with a median OS of 11.5 mo. 1. Gregorc V, et al. Lancet Oncol 2014;15:713‒21 Clinical trial information: 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 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)0.005
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.170
GPT teacher head0.531
Teacher spread0.361 · 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 designRandomized trial
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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Citations2
Published2016
Admission routes1
Has abstractyes

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