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Record W2794244726 · doi:10.1002/hed.25075

Neutrophil‐to‐lymphocyte ratio in head and neck cancer prognosis: A systematic review and meta‐analysis

2018· review· en· W2794244726 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHead & Neck · 2018
Typereview
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineHazard ratioInternal medicineConfidence intervalHead and neck cancerMeta-analysisHead and neck squamous-cell carcinomaOncologyGastroenterologyNeutrophil to lymphocyte ratioLarynxCancerLymphocyteSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Hematologic markers, such as the neutrophil-to-lymphocyte ratio (NLR), characterize the inflammatory response to cancer and are associated with poorer survival in various malignancies. We evaluate the effect of pretreatment NLR on overall survival (OS) in patients with head and neck squamous cell carcinoma (HNSCC). METHODS: Using multiple databases, a systematic search for articles evaluating the effect of NLR on OS in patients with HNSCC was performed. An inverse variation, random-effects model was used to analyze the data. RESULTS: A total of 24 of 241 articles, including 6479 patients, were analyzed. The combined hazard ratio for OS in patients with an elevated NLR (range 2.04-5) was 1.78 (confidence interval [CI] 1.53-2.07; P < .0001). The hazard ratios for site-specific cancer: oral cavity 1.56 CI 1.23-1.98 (P < .001), nasopharynx 1.66 CI 1.35-2.04 (P < .001), larynx 1.55 CI 1.26-1.92 (P < .001), and hypopharynx 2.36 CI 1.54-3.61 (P < .001). CONCLUSION: An elevated NLR is predictive of poorer OS in patients with HNSCC.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.616
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0120.002
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)0.0000.000

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 head0.072
GPT teacher head0.380
Teacher spread0.308 · 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