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Record W2744038873 · doi:10.1002/hed.24889

Primary treatment for oropharyngeal squamous cell carcinoma in Alberta, Canada: A population‐based study

2017· article· en· W2744038873 on OpenAlexafffundabout
Amy Hobbs, Nigel T. Brockton, T. Wayne Matthews, Shamir Chandarana, Pinaki Bose, Kelly Guggisberg, Gordon H. Fick, Joseph C. Dort

Bibliographic record

VenueHead & Neck · 2017
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsCalgary Laboratory ServicesRockyview General HospitalAlberta Health ServicesInstitute of Cancer ResearchAlberta Cancer FoundationUniversity of Calgary
FundersAlberta Innovates - Health Solutions
KeywordsMedicineInternal medicineIncidence (geometry)CohortOncologyBasal cellImmunohistochemistryHuman papillomavirusCohort studyPopulation

Abstract

fetched live from OpenAlex

BACKGROUND: The incidence of human papillomavirus (HPV)-related oropharyngeal squamous cell carcinoma (SCC) is increasing and has better survival than non-HPV related oropharyngeal SCC. This study compared surgical to nonsurgical treatments and demographic, clinical, and survival differences in patients with oropharyngeal SCC, stratified by p16 status. METHODS: We assembled a cohort of adult patients with oropharyngeal SCC diagnosed between 2000 and 2008 in Alberta. The tumor p16 biomarker was measured using fluorescent immunohistochemistry. RESULTS: In this cohort, p16 data were available for 115 of 357 patients; and 66% (n = 76) were p16-positive. Patients with p16 data had comparable outcomes to those without. Surgically treated p16-negative patients had improved 5-year disease-specific survival (DSS) and overall survival (OS) compared with nonsurgical patients. There were no differences in survival outcomes between surgical and nonsurgical treatment for patients with p16-positive disease. CONCLUSION: Patients with p16-positive oropharyngeal SCC had similar outcomes regardless of treatment. Patients with p16-negative tumors may benefit from primary surgery with postoperative adjuvant therapy.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.669

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.037
GPT teacher head0.311
Teacher spread0.273 · 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

Citations12
Published2017
Admission routes3
Has abstractyes

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