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Record W2949648744 · doi:10.1002/hed.25838

Primary organ preservation vs total laryngectomy for T4a larynx cancer

2019· article· en· W2949648744 on OpenAlexaff
Justin Oh, Eitan Prisman, Robert Olson, Eric Berthelet, Jonn Wu, Eric Tran, Brendan Bakos, Rojin Kaviani, Sarah Hamilton

Bibliographic record

VenueHead & Neck · 2019
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsPositive Living NorthUniversity of British ColumbiaBC Cancer Agency
Fundersnot available
KeywordsLaryngectomyMedicineLarynxChemoradiotherapyRadiation therapyCancerConfidence intervalSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: There is a lack of consensus regarding the management of T4a larynx cancer. We evaluated the outcomes of organ preservation and laryngectomy for T4a laryngeal cancer. METHODS: Retrospective analysis of patients with T4a larynx cancer at BC Cancer from 1984 to 2014 was performed. Outcomes in patients treated with surgery alone (Sx) (n = 47), surgery with adjuvant radiotherapy (Sx/RT) (n = 94), radiation alone (RT) (n = 152), and radiation with concurrent chemoradiotherapy (chemoRT) (n = 36) were compared. RESULTS: The 5-year overall survival (OS) was 40% for chemoRT, 34% for RT, 23% for Sx, and 45% for Sx/RT. On multivariate analysis (MVA), Sx/RT (hazard ratio [HR], 0.66; 95% confidence interval [CI], 0.48-0.91) and chemoRT (HR, 0.44; 95% CI, 0.26-0.72) were associated with better OS than RT alone (P = .001). Sx had similar OS compared to RT (HR, 1.17; 95% CI, 0.82-1.68). CONCLUSIONS: ChemoRT and Sx/RT were associated with better OS compared to single modality treatment. ChemoRT may be considered as an option for T4a larynx cancer.

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 score0.143
Threshold uncertainty score0.555

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)0.0000.000

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 head0.025
GPT teacher head0.316
Teacher spread0.290 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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