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Record W2916339782 · doi:10.14740/wjon1179

Pretreatment Lung Immune Prognostic Index Is a Prognostic Marker of Chemotherapy and Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitor

2019· article· en· W2916339782 on OpenAlex
Seigo Minami, Shouichi Ihara, Kiyoshi Komuta

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueWorld Journal of Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEpidermal growth factor receptorAdenocarcinomaHazard ratioInternal medicineLung cancerOncologyChemotherapyTyrosine-kinase inhibitorBiomarkerCancer researchCancerConfidence intervalBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Lung immune prognostic index (LIPI) was recently developed on the basis of the combination of baseline derived neutrophil to lymphocyte ratio (dNLR) and lactate dehydrogenase (LDH). This index was demonstrated as a specific biomarker of immune checkpoint inhibitors for non-small cell lung cancer (NSCLC). We aimed to show that LIPI may be a useful biomarker of cytotoxic chemotherapy and epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) for NSCLC. METHODS: We retrospectively collected 175 wild-type EGFR adenocarcinomas, 131 NSCLCs harboring mutant EGFR and 110 squamous cell carcinomas. All patients initiated first-line cytotoxic chemotherapy or EGFR-TKI monotherapy between July 2007 and August 2017 at our hospital. These patients were divided into good, intermediate and poor LIPI groups. We compared their overall survival (OS) and progression-free survival (PFS). Multivariate analyses detected prognostic and predictive factors of OS and PFS. RESULTS: The good LIPI group survived longer than the intermediate and poor LIPI groups in wild-type EGFR adenocarcinoma (good, intermediate and poor LIPI groups: median 19.6, 11.5 and 3.3 months, P < 0.01, respectively) and mutant EGFR NSCLC (45.4, 25.6 and 15.7 months, P < 0.01). The PFS of good LIPI group was significantly longer that those of the other two groups in mutant EGFR NSCLC (16.6, 12.6 and 8.3 months, P < 0.01). The intermediate group (hazard ratio (HR) 1.49, 95% confidential interval (CI) 1.03 - 2.15, P = 0.04) of wild-type EGFR adenocarcinoma, intermediate (HR 2.30, 95% CI 1.33 - 3.99, P < 0.01) and poor (HR 2.76, 95% CI 1.03 - 7.42, P = 0.04) groups of mutant EGFR NSCLC were independent prognostic factors of poor OS. The intermediate (HR 1.57, 95% CI 1.01 - 2.44, P = 0.04) and poor (HR 2.63, 95% CI 1.14 - 6.07, P = 0.02) groups were significant prognostic factors of PFS of mutant EGFR NSCLC. CONCLUSIONS: LIPI was an independent prognostic factor of chemotherapy for adenocarcinoma with wild-type EGFR and of EGFR-TKI for NSCLC harboring mutant EGFR. Thus, LIPI was not a specific biomarker for ICI therapy, but a useful biomarker for chemotherapy and EGFR-TKI therapy in specific subsets of NSCLC.

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.

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)0.001
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 score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.009
GPT teacher head0.275
Teacher spread0.265 · 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