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Record W2168982164 · doi:10.1177/0269216310384900

Variation in the use of palliative radiotherapy at end of life: Examining demographic, clinical, health service, and geographic factors in a population-based study

2010· article· en· W2168982164 on OpenAlexafffundabout
M. Ruth Lavergne, Grace Johnston, Jun Gao, Trevor Dummer, D. Rheaume

Bibliographic record

VenuePalliative Medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsCancer Care Nova ScotiaHealth CanadaDalhousie University
FundersCanadian Institutes of Health Research
KeywordsMedicinePalliative careLogistic regressionDemographyGerontologyGeographic variationRadiation therapyPopulationEnd-of-life careNova scotiaQuality of life (healthcare)Multivariate analysisFamily medicineEnvironmental healthNursingInternal medicine

Abstract

fetched live from OpenAlex

Palliative radiotherapy (PRT) can improve quality of life for people dying of cancer. Variation in the delivery of PRT by factors unrelated to need may indicate that not all patients who may benefit from PRT receive it. In this study, 13,494 adults who died of cancer between 2000 and 2005 in Nova Scotia, Canada, were linked to radiotherapy records. Multivariate logistic regression was used to examine the relationships among demographic, clinical, service, and geographic variables, and PRT consultation and treatment. Among the decedents, 4188 (31.0%) received PRT consultation and 3032 (22.3%) treatment. PRT declined with increased travel time and community deprivation. Females, older persons, and nursing home residents also had lower PRT rates. Variations were observed by cancer site and previous oncology care. Variations in PRT use should be discussed with referring physicians, and improved means of access to PRT considered. Benchmarks for optimal rates of PRT are needed.

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)0.003
metaresearch head score (Gemma)0.002
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 score0.009
Threshold uncertainty score0.848

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.121
GPT teacher head0.388
Teacher spread0.266 · 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

Citations65
Published2010
Admission routes3
Has abstractyes

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