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Record W3184018436 · doi:10.1002/hed.26819

Ninety‐day mortality after radiotherapy for head and neck cancer: Population‐based comparison between rural and urban patients

2021· article· en· W3184018436 on OpenAlexaffabout
Roel Schlijper, Siske Bos, Sarah Hamilton, Eric Tran, Eric Berthelet, Jonn Wu, Robert Olson

Bibliographic record

VenueHead & Neck · 2021
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsBC Cancer AgencyPositive Living NorthUniversity of Northern British ColumbiaUniversity of British Columbia
Fundersnot available
KeywordsRuralityMedicineHead and neck cancerConfoundingDemographyRadiation therapyRural areaPopulationEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: This study assesses whether 90-day mortality differs between patients living in rural and urban areas, as lower access to supportive care services in rural areas could result in higher mortality. METHODS: All patients with head and neck cancer (HNC) treated between 1998 and 2014 with radiotherapy in British Columbia were included. Patients were divided into rurality areas according to the Modified Statistics Canada (mSC) definition, which classifies a population <30 000 as rural and ≥30 000 as urban. RESULTS: Five thousand five hundred and fifty-four patients were included in this study, of which 68% lived in urban centers. The 90-day mortality for rural versus urban patients were 3.0% and 3.9% (p = 0.09), respectively. Univariate and multivariate analyses showed no association with 90-day mortality and rurality. CONCLUSION: After controlling for potentially confounding factors, we did not find a significant association between 90-day mortality and rurality in patients who were treated with radiotherapy for HNC in British Columbia.

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 score0.020
Threshold uncertainty score0.785

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 head0.037
GPT teacher head0.357
Teacher spread0.320 · 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

Citations2
Published2021
Admission routes2
Has abstractyes

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