MétaCan
Menu
Back to cohort
Record W2912102542 · doi:10.1002/hed.25696

The role of age in treatment‐related adverse events in patients with head and neck cancer: A systematic review

2019· review· en· W2912102542 on OpenAlexaff
Andrés Coca‐Pelaz, György B. Halmos, Primož Strojan, Remco de Bree, Paolo Bossi, Carol R. Bradford, Alessandra Rinaldo, Vincent Vander Poorten, Álvaro Sanabria, Robert P. Takes, Alfio Ferlito

Bibliographic record

VenueHead & Neck · 2019
Typereview
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsSurgical Specialties (Canada)
Fundersnot available
KeywordsContraindicationMedicineAdverse effectHead and neck cancerComorbidityHead and neck squamous-cell carcinomaCancerStage (stratigraphy)Intensive care medicineOncologyInternal medicineAlternative medicinePathology

Abstract

fetched live from OpenAlex

Head and neck squamous cell carcinoma (HNSCC) is often diagnosed in advanced stage and therefore requires aggressive, multimodal treatment. Elderly patients are often excluded from standard therapy regimens purely based on age. This clinical review aims to collect all published data in the literature on treatment modality selection in elderly patients and on age-related adverse events following treatment of HNSCC. We performed a literature search for articles on the treatment of HNSCC in elderly patients. Most of the articles were retrospective studies with the consequent limitations. It can be concluded that age is not an absolute contraindication for intensive treatment and comorbidity is an important predictor of outcome, but not the only one. Despite the existence of multiple tools for pretreatment evaluation, there are not consistent data on their use.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0050.006
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.333
Teacher spread0.304 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Explore more

Same venueHead & NeckSame topicHead and Neck Cancer StudiesFrench-language works237,207