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Record W2916562315 · doi:10.14740/wjon1184

Gustave Roussy Immune Score Is a Prognostic Factor for Chemotherapy-Naive Pulmonary Adenocarcinoma With Wild-Type Epidermal Growth Factor Receptor

2019· article· en· W2916562315 on OpenAlexvenueno aff
Seigo Minami, Shouichi Ihara, Kiyoshi Komuta

Bibliographic record

VenueWorld Journal of Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInternal medicineHazard ratioOncologyEpidermal growth factor receptorProportional hazards modelProgression-free survivalChemotherapyAdenocarcinomaPerformance statusLung cancerLactate dehydrogenaseImmunotherapyCancerConfidence intervalBiology

Abstract

fetched live from OpenAlex

BACKGROUND: The Gustave Roussy Immune Score (GRIm-Score) was developed based on the Royal Marsden Hospital (RMH) prognostic score for the purpose of a better patient selection for immunotherapy phase I trials. This scoring system is simply calculated by neutrophil-to-lymphocyte ratio, lactate dehydrogenase (LDH), and serum albumin concentration. The aim of our study was to determine whether GRIm-Score is a practically useful prognostic biomarker for advanced non-small cell lung cancer (NSCLC) patients treated with cytotoxic chemotherapy or epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI). METHODS: This retrospective and single institutional study collected 185 adenocarcinomas without active EGFR mutation, 115 squamous cell carcinomas treated with first-line cytotoxic chemotherapy, and 140 NSCLCs with mutant EGFR treated with first- or second-generation EGFR-TKI monotherapy. These treatments were initiated between July 2007 and March 2018 at our hospital. We compared overall survival (OS) and progression-free survival (PFS) between high and low GRIm-Score groups. Using multivariate Cox proportional hazard analyses, we also found prognostic factors of survival times. RESULTS: The OS and PFS of low GRIm-Score group were significantly longer than those of high-score group in wild-type EGFR adenocarcinoma (low vs. high; median OS, 18.4 vs. 5.1 months, P < 0.01, and median PFS, 5.8 vs. 3.7 months, P = 0.01) and EGFR-mutant NSCLC (median OS, 38.9 vs. 10.4 months, P < 0.01, and median PFS, 15.9 vs. 5.0 months, P < 0.01). Subsequent multivariate analyses detected high GRIm-Score in wild-type EGFR adenocarcinoma as a poor prognostic factor of OS (hazard ratio (HR) 2.20, 95% CI 1.47 - 3.31, P < 0.01), and in the EGFR-mutant NSCLC as a poor prognostic factor of PFS (HR 1.89, 95% CI 1.00 - 3.55, P = 0.049). CONCLUSIONS: High GRIm-Score was an independent prognostic biomarker of OS of first-line cytotoxic chemotherapy for wild-type EGFR adenocarcinoma and of PFS of first- or second-generation EGFR-TKI for EGFR-mutant NSCLC. Therefore, GRIm-Score is not only a specific selection marker for experimental immunotherapy trials, but may also be a promising and useful pretreatment prognostic maker for specific NSCLC subsets in the real-world practice.

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 categoriesMeta-epidemiology (narrow), Insufficient 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 score0.051
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
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.282
Teacher spread0.260 · 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

Citations20
Published2019
Admission routes1
Has abstractyes

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