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Record W1553758888 · doi:10.1002/hed.23504

Role of endolaryngeal surgery (with or without laser) versus radiotherapy in the management of early (T1) glottic cancer: A systematic review

2013· review· en· W1553758888 on OpenAlexaff
John Yoo, Christina Lacchetti, J. Alex Hammond, Ralph Gilbert

Bibliographic record

VenueHead & Neck · 2013
Typereview
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkMcMaster UniversityCancer Care OntarioWestern University
Fundersnot available
KeywordsMedicineRadiation therapyCochrane LibraryTransoral laser microsurgeryModalitiesMEDLINELaser surgeryLaryngeal NeoplasmTreatment modalityQuality of life (healthcare)SurgeryLarynxHead and neck cancerRandomized controlled trialLaser

Abstract

fetched live from OpenAlex

BACKGROUND: Treatment options for early glottic cancer include transoral microsurgery or radiotherapy (RT). There is continuing debate about which is the superior treatment. METHODS: The literature was searched from 1996 to 2011 using MEDLINE, EMBASE, and Cochrane Library. A quality assessment of each included study was conducted and reported. RESULTS: There is no evidence in favor of 1 treatment modality when considering likelihood of local control or overall survival. There is a suggestion that RT may be associated with less measureable perturbation of voice as compared to surgery, but no significant differences were seen in patient perception. The likelihood of laryngeal preservation may be higher when surgery can be offered as initial treatment. CONCLUSION: For patients with early (T1) glottic cancer, treatment options include the equally effective endolaryngeal surgery, with or without laser, or radiation therapy. The choice between treatment modalities should be based on patient and clinician preferences and general medical condition.

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)0.005
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.006
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.080
GPT teacher head0.377
Teacher spread0.296 · 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 designSystematic review
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

Citations102
Published2013
Admission routes1
Has abstractyes

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