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Markers of neck failure in oral cavity and oropharyngeal carcinomas treated with radiotherapy

2001· article· en· W1988672799 on OpenAlexaff
Andr� Fortin, H�l�ne Raybaud-Diog�ne, Bernard T�tu, Jacques Huot, Lucie Blondeau, Jacques Landry

Bibliographic record

VenueHead & Neck · 2001
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsUniversité LavalHôtel-Dieu de Québec
Fundersnot available
KeywordsMedicineRadiation therapyNeck dissectionImmunohistochemistryOral cavityInternal medicineOncologyNODALPositive stainingGastroenterologyPathologyCarcinoma

Abstract

fetched live from OpenAlex

BACKGROUND: Neck management after radiotherapy remains controversial. It is not clear which patients may benefit from postradiotherapy neck dissection. Biologic markers may be useful in this setting. METHOD: This study includes 81 patients with oral cavity and oropharyngeal carcinomas. The primary tumor had been treated with radical radiotherapy. Immunohistochemical staining to p53, ki-67, NEU, HSP-27, and GST has been performed. RESULTS: There were 50 T1-2 and 31 T3-4 patients, as well as 36 NO and 45 N1-3. A total of 25 nodal failures was observed. With expressed HSP2, 23% of patients had neck failure compared with 51% when HSP-27 was absent (p = .02). With NEU overexpression, nodal control decreased from 72% to 34% (p = .008). In a Cox model, NEU (p = .01) and HSP-27 (p = .05) were associated with neck failure. CONCLUSIONS: HSP-27 and NEU expression may play a role in predicting nodal failure. This should be confirmed in a larger, prospective study.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0010.000

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 head0.019
GPT teacher head0.282
Teacher spread0.263 · 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 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

Citations15
Published2001
Admission routes1
Has abstractyes

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