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Head and neck squamous cell carcinoma in the young patient

2005· review· en· W2072202397 on OpenAlexaff
David P. Goldstein, Jonathan C. Irish

Bibliographic record

VenueCurrent Opinion in Otolaryngology & Head & Neck Surgery · 2005
Typereview
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsUniversity of TorontoCanadian Cancer SocietyPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineEtiologyHead and neck squamous-cell carcinomaHead and neck cancerCarcinomaOncologyCancerHead and neckInternal medicineEpidermoid carcinomaTongueYoung adultBasal cellSurgeryPathology

Abstract

fetched live from OpenAlex

PURPOSE OF THE REVIEW: Squamous cell carcinoma of the upper aerodigestive tract most commonly develops in the sixth or seventh decade of life, usually in patients who have significant risk factors from smoking or alcohol use. A subgroup of patients less than 45 years old, however, develops squamous cell carcinoma of the head and neck in whom the role of tobacco or alcohol use is less clear in the etiology of their cancer. Furthermore, there has been considerable debate regarding the tumor biology in this group of patients and its effects on prognosis and overall survival. This paper reviews the current literature and controversies on the etiology and management of squamous cell carcinoma of the head and neck in young patients. RECENT FINDINGS: Young patients with head and neck squamous cell carcinoma do not have a poorer prognosis or disease-specific survival. SUMMARY: Young patients with squamous cell carcinoma of the head and neck have a similar prognosis to older patients. There is a trend, however, towards a higher regional recurrence in young patients with head and neck squamous cell carcinoma, suggesting that prophylactic neck treatment should be considered. Further research is needed to determine whether a subgroup of patients (young nonsmoking women with tongue cancer) have a worse prognosis and warrant more aggressive treatment.

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)0.000
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 score0.840
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.086
GPT teacher head0.371
Teacher spread0.286 · 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

Citations61
Published2005
Admission routes1
Has abstractyes

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