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Record W4413743556 · doi:10.1002/hed.70022

Evaluation of a Novel Prognostic System for Surgically Resected Oral Cavity Carcinoma

2025· article· en· W4413743556 on OpenAlexaff
A. Rybkin, Victor Lee, Melissa R. Young, Antoine Eskander, Barbara Burtness, Henry S. M. Park, Zain Husain

Bibliographic record

VenueHead & Neck · 2025
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsOral cavityMedicineCarcinomaOncologySurgeryInternal medicineDentistry

Abstract

fetched live from OpenAlex

BACKGROUND: The Oral Cavity Predictive Score (OCCPS) is a point-based system including T/N stage, LVSI, and grade that has been validated for predicting distant metastasis. We tested its ability to predict overall survival (OS) in surgically managed oral cavity carcinoma (OCC). METHODS: Patients diagnosed 2010-2020 and treated with surgery were selected from the National Cancer Data Base (NCDB) and stratified into standard, intermediate, and high-risk categories using OCCPS. The Kaplan-Meier method compared OS in the whole cohort and select subgroups. RESULTS: Of 32 317 patients (median follow-up 38.4 months), 51.7%, 22.5%, and 25.8% were classified into standard, intermediate, and high-risk groups, respectively. Five-year OS was 73.4%, 58.6%, and 39.3% (log rank p < 0.001). The OCCPS stratified patients with negative margins and absent ENE, and stage IVA-B disease (log rank p < 0.001). CONCLUSION: In patients with OCC managed with at least definitive surgery, the OCCPS successfully stratifies patients into standard, intermediate, and high-risk groups for prediction of OS.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.200
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.103
GPT teacher head0.388
Teacher spread0.285 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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