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Record W2994867938 · doi:10.1002/cncr.32654

National treatment trends in human papillomavirus–positive oropharyngeal squamous cell carcinoma

2019· article· en· W2994867938 on OpenAlexaff
Kevin Y. Zhan, Sidharth V. Puram, Michael Li, Dustin A. Silverman, Amit Agrawal, Enver Özer, Matthew Old, Ricardo L. Carrau, James W. Rocco, Kevin Higgins, Danny Enepekides, Zain Husain, Stephen Y. Kang, Antoine Eskander

Bibliographic record

VenueCancer · 2019
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineQuartileIncidence (geometry)CancerInternal medicineHuman papillomavirusAdjuvant therapySurgeryOncologyConfidence interval

Abstract

fetched live from OpenAlex

BACKGROUND: Human papillomavirus (HPV)-mediated oropharyngeal cancer (OPC) is associated with dramatically improved survival in comparison with HPV-negative OPC and can be successfully treated with surgical and nonsurgical approaches. National treatment trends for OPC were investigated with the National Cancer Data Base (NCDB). METHODS: The NCDB was reviewed for primary HPV-mediated OPC in 2010-2014. Multivariable regression was used to identify predictors of both nonsurgical therapy and receipt of adjuvant chemoradiation (CRT). RESULTS: = 0.89). Hospitals in the top treatment volume quartile (quartile 1 [Q1]; n = 29) had a lower rate of positive margins (16.3%) than bottom-quartile centers (n = 741; rate of positive margins, 36.4%; P < .001); Q1 hospitals used surgical therapy significantly more. Independent predictors of nonsurgical therapy included older age, advanced disease, lower hospital volume, and living closer to the hospital or outside the Pacific United States. In surgically treated patients, younger age, lower hospital volume, nodal disease, positive surgical margins, and extranodal extension (ENE) also predicted more adjuvant CRT use. CONCLUSIONS: The use of upfront surgical treatment decreased from 2010 to 2014. Hospital volume shows a strong, inverse correlation with the rate of positive surgical margins. The upfront treatment strategy is predicted not only by staging but also by patient-, geographic-, and hospital-specific factors. Lower hospital volume remains independently associated with increased triple-modality therapy after adjustments for positive margins, ENE, and pathologic staging.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.000

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 head0.030
GPT teacher head0.331
Teacher spread0.301 · 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 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

Citations33
Published2019
Admission routes1
Has abstractyes

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