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Record W2339063315 · doi:10.1002/hed.24484

Adjuvant radiotherapy versus concurrent chemoradiotherapy for the management of high‐risk salivary gland carcinomas

2016· article· en· W2339063315 on OpenAlexaff
Matthew Mifsud, Tawee Tanvetyanon, Judith C. McCaffrey, Kristen J. Otto, Tapan Padhya, Julie A. Kish, Andy Trotti, Louis B. Harrison, Jimmy J. Caudell

Bibliographic record

VenueHead & Neck · 2016
Typearticle
Languageen
FieldMedicine
TopicSalivary Gland Tumors Diagnosis and Treatment
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsMedicineChemoradiotherapyOncologyPerineural invasionHazard ratioRadiation therapyInternal medicineProportional hazards modelPopulationLymph nodeAdjuvantMultivariate analysisHead and neck cancerConfidence intervalCancer

Abstract

fetched live from OpenAlex

BACKGROUND: Given the aggressive behavior of advanced salivary malignancies, the purpose of the current study was to explore the utility of adjuvant chemoradiotherapy (CRT) in this population. METHODS: A retrospective study of salivary carcinomas treated from 1998 to 2013 with postoperative CRT (37 patients) or radiotherapy (RT; 103 patients) was completed. RESULTS: The decision to utilize adjuvant CRT versus RT was influenced by tumor grade and histology, cervical lymph node status, surgical margins, and perineural invasion. In both treatment cohorts, high locoregional control rates were obtained (79% for CRT vs 91% for RT; p = .031). Multivariate Cox regression analysis did not identify a difference in 3-year progression-free survival (PFS) with the use of CRT versus RT (hazard ratio [HR] = 0.783; 95% confidence interval [CI] = 0.396-1.549; p = .482). CONCLUSION: Until prospective evidence is available, such as from Radiation Therapy Oncology Group 1008, the standard use of CRT for advanced salivary malignancies cannot be recommended. © 2016 Wiley Periodicals, Inc. Head Neck 38: 1708-1716, 2016.

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 score0.392
Threshold uncertainty score0.457

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 head0.032
GPT teacher head0.308
Teacher spread0.276 · 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

Citations70
Published2016
Admission routes1
Has abstractyes

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