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Record W2950848650 · doi:10.1002/hed.25842

High‐grade radiologic extra‐nodal extension predicts distant metastasis in stage II nasopharyngeal carcinoma

2019· article· en· W2950848650 on OpenAlexaff
Yujun Hu, Tianzhu Lu, Shao Hui Huang, Shaojun Lin, Yunbin Chen, Yanhong Fang, Han Zhou, Yiping Chen, Jingfeng Zong, Yu Zhang, Ying Chen, Youping Xiao, Qiaojuan Guo

Bibliographic record

VenueHead & Neck · 2019
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
FundersFujian Provincial Department of Science and TechnologyNatural Science Foundation of Fujian ProvinceNational Natural Science Foundation of China
KeywordsNasopharyngeal carcinomaStage (stratigraphy)NODALInfiltration (HVAC)MedicineMetastasisInternal medicineDistant metastasisOncologyT-stageOverall survivalRadiation therapyCancerBiologyPhysics

Abstract

fetched live from OpenAlex

BACKGROUND: To investigate the prognostic value of radiologic extra-nodal extension (rENE) in stage II nasopharyngeal carcinoma (NPC). METHODS: Stage II NPC patients with N1 category (n = 365) were enrolled and divided into three groups according to the situation of rENE: without rENE, suspected rENE, and confirmed rENE (grades: A, infiltration into surrounding fat; B, matted nodes; C, infiltration into adjacent structures). RESULTS: Only high-grade rENE (including matted nodes and infiltration into adjacent structures) could significantly influence the survival outcomes, patients with high-grade rENE had significantly poorer survival than those without, with the 7-year distant metastasis-free survival and overall survival demonstrated to be 78.5% vs 93.0% (P < .001) and 81.9% vs 89.9% (P = .05), respectively. High-grade rENE, as defined in our study, is a stable criterion, with high intra-rater and inter-rater consistency. CONCLUSION: High-grade rENE was an evaluable predictor that could help with the selection of stage II patients with high risk of distant metastasis.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score1.000

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 head0.038
GPT teacher head0.295
Teacher spread0.257 · 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

Citations39
Published2019
Admission routes1
Has abstractyes

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