MétaCan
Menu
← Back to cohort

Resource utilization in patients with head and neck cancer: Analysis of CCTG HN6 (NCT00820248).

2017· article· en· W2890829740 on OpenAlexaffabout
Ketan Ghate, Wendy R. Parulekar, Bingshu E. Chen, Alexander Montenegro, Nader Khaouam, Joy McCarthy, John Walker, John Waldron, Lillian L. Siu, Ana Johnson

Bibliographic record

VenueJournal of Clinical Oncology · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsPrincess Margaret Cancer CentreDr. H. Bliss Murphy Cancer CentreHôpital Maisonneuve-RosemontQueen's University
Fundersnot available
KeywordsMedicineHead and neck cancerHead and neck squamous-cell carcinomaInternal medicineCancer

Abstract

fetched live from OpenAlex

6067 Background: As new treatments for head and neck cancer arise, further information is required regarding resource utilization. The Canadian Cancer Trials Group HN.6 study included collected resource utilization data prospectively on patients with locally advanced squamous cell carcinoma of the head and neck treated with cisplatin or panitumumab plus radiotherapy (RT). Methods: The HN.6 phase III trial enrolled 320 patients across Canada between 2008-2011. The economic analysis was conducted from the societal perspective. Resource utilization was collected prospectively for 3 categories: outpatient, hospitalization and institutionalization (end of life care) at baseline, 8 weeks, every 3 months(mo) for 2 years and every 4 mo until 3 years. Lost productivity questionnaires were collected in the last week of RT. Descriptive statistics were used to summarize the outcomes. Categorical variables were reported by percentage and continuous variables were reported by mean and standard deviation. Results: Of 320 pts randomized, resource utilization and lost productivity data were available for 317 (99%) and 285 (89%) pts, respectively. Eighty nine pts required 130 emergency room visits (mean 1.46±0.85). There were 696 (mean 3.74±3.22) office visits among 186 pts and 367 (mean 3.95±6.43) outpatient visits among 93 pts. Surgeons, radiation oncologists and emergency room physicians were the top three providers of outpatient care with 234 (mean 2.05±1.54), 137 (mean 1.67±1.19) and 118 (mean 1.4±0.78) visits for 114, 82 and 84 pts, respectively. CT scans (286), lab tests (418), x-rays (182) and other tests (400) were conducted in 136, 180, 120 and 194 pts, respectively. Three pts were institutionalized for end of life care (mean 28 days±26.06), and 214 pts were hospitalized (mean 14.5 days±28.8). One hundred and thirteen (41%) pts reported a change in work status at the end of RT. Conclusions: Radical treatment for locally advanced SCCHN is resource intensive. Tracking resources utilized prospectively in clinical trial settings and reporting this information consists of an efficient way to inform health resource allocation decisions. Clinical trial information: NCT00820248.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.253
Threshold uncertainty score0.504

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.632
GPT teacher head0.588
Teacher spread0.045 · 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 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

Citations0
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Clinical Oncology→Same topicHealth Systems, Economic Evaluations, Quality of Life→French-language works237,207→