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Record W1853613340 · doi:10.1002/hed.24210

Clinical parameters predicting development of pulmonary malignancies in patients treated for head and neck squamous cell carcinoma

2015· article· en· W1853613340 on OpenAlexaffabout
J. Madana, Grégoire B. Morand, Abdulaziz Al‐Rasheed, Nathalie Gabra, Frédérick Laliberté, Luz Barona–Lleó, Deeke Yolmo, Martin J. Black, Khalil Sultanem, Michael Hier

Bibliographic record

VenueHead & Neck · 2015
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsMedicineMalignancyInternal medicineHead and neck squamous-cell carcinomaMultivariate analysisOncologyProportional hazards modelHead and neckRetrospective cohort studyBasal cellCancerHead and neck cancerSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: As the locoregional control rates in head and neck squamous cell carcinoma (HNSCC) have increased, these patients may suffer distant metastasis in a higher proportion of cases. Clinicopathological characteristics allowing prediction of high-risk profile would allow adapting posttreatment surveillance to individual risk. METHODS: A retrospective review of all patients with HNSCC treated at the Jewish General Hospital, McGill University, Montreal, Quebec, Canada, between 1999 and 2008 was conducted for this study. RESULTS: The study included 428 patients with a mean follow-up of 65 months (±SEM 1.7). Eighty patients (18.6%) developed pulmonary malignancy during follow-up. In multivariate Cox-regression analysis, locoregional failure and current smoking were associated with higher risk of pulmonary malignancy (p < .001 and p = .008, respectively). CONCLUSION: Locoregional failure and smoking persistence are predictors of pulmonary malignancy in patients with HNSCC. © 2015 Wiley Periodicals, Inc. Head Neck 38: E1277-E1280, 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 score0.011
Threshold uncertainty score0.660

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 head0.073
GPT teacher head0.327
Teacher spread0.254 · 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

Citations7
Published2015
Admission routes2
Has abstractyes

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