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Record W4378549051 · doi:10.1080/01635581.2023.2212427

Associations between Human Papillomavirus Status, Weight Change, and Survival of Oropharyngeal Cancer Patients

2023· article· en· W4378549051 on OpenAlexaffabout
Sheilla de Oliveira Faria, Katrina Hueniken, Vijay Kunaratnam, Shao Hui Huang, David P. Goldstein, Joanne Pun, Andrew Hope, Anna Spreafico, Wei Xu, Doris Howell, Geoffrey Liu

Bibliographic record

VenueNutrition and Cancer · 2023
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineWeight lossHazard ratioInternal medicineBody mass indexWeight changeOncologyCancerOdds ratioConfidence intervalObesity

Abstract

fetched live from OpenAlex

This study examined associations between HPV status and weight change in oropharyngeal cancer (OPC). OPC patients receiving concurrent chemoradiotherapy in Toronto, Canada were included. Relationships were assessed between HPV status and weight loss grade (WLG, combining weight loss and current body mass index); weight change during treatment; and HPV status and WLG/weight change on overall (OS) and cancer-specific (CSS) survival. Of 717 patients, WLG pre-radiation was less severe among HPV-positive compared to HPV-negative, though weight loss during treatment was greater. The adjusted odds ratio for greater WLG among HPV-positive versus HPV-negative was 0.47 (95%CI 0.28-0.78). Grade-4 WLG (worst category) experienced poorer OS and CSS (OS adjusted hazard ratio (aHR) 4.08; 95%CI 1.48-11.2, compared to Grade-0); and was non-significant for HPV-negative (aHR 2.34; 95%CI 0.69-7.95). Relationships between weight change before/during treatment and survival had similar direction between HPV-positive and HPV-negative, but of greater magnitude in HPV-positive patients.

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 score0.060
Threshold uncertainty score0.319

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 head0.079
GPT teacher head0.360
Teacher spread0.281 · 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
Published2023
Admission routes2
Has abstractyes

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