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Surgical margins after open versus transoral surgery for oropharyngeal cancer and their impact on the need for multimodal treatments

2025· review· en· W4410445203 on OpenAlexaboutno aff
Pietro Canzi, Maria Vittoria Veneroni, Erika Crosetti, Simone Mauramati, Giulia Bertino, Ottavia Eleonora Ferraro, Giovanni Succo, Marco Benazzo

Bibliographic record

VenueActa Otorhinolaryngologica Italica · 2025
Typereview
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTransoral robotic surgeryCancer surgeryCancerSurgeryGeneral surgeryOtologyInternal medicine

Abstract

fetched live from OpenAlex

Objective: transoral) and the subsequent risk of additional treatments. Methods: Medical databases were searched including PubMed, Scopus, EMBASE, and Cochrane Library from January 2000 to August 2024. Data analysis was carried out in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis, and the quality of studies was evaluated using the Newcastle-Ottawa Scale. Results: Four studies, including 305 patients (126 treated by an open approach, and 179 by transoral surgery), were qualitatively analysed. No significant difference was found in the rates of positive margins (p = 0.422) or need for adjuvant therapy (p = 0.368) between the two approaches. It was not feasible to conduct a meta-analysis due to significant inconsistencies in the reporting of data across the studies included. Conclusions: Transoral approach is recommended for early-stage OPSCC when adequate exposure is achievable, although its impact on positive surgical margins remains unclear. The management of close or positive margins remains debated due to the oropharyngeal unique anatomy and function, with no clear de-intensification protocol established.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.919
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.104
GPT teacher head0.403
Teacher spread0.299 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2025
Admission routes1
Has abstractyes

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