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Record W2038602339 · doi:10.1016/j.jbo.2014.11.001

Quality of life after palliative radiotherapy in bone metastases: A literature review

2014· review· en· W2038602339 on OpenAlexafffund
Rachel McDonald, Edward Chow, Leigha Rowbottom, Gillian Bedard, Henry Lam, Erin Wong, Marko M. Popovic, Natalie Pulenzas, May Tsao

Bibliographic record

VenueJournal of bone oncology · 2014
Typereview
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsSunnybrook Health Science CentreHealth Sciences Centre
FundersOfelia Cancer Research FundMichael and Karyn Goldstein Cancer Research FundJoseph and Silvana Melara Cancer Research Fund
KeywordsMedicineQuality of life (healthcare)Radiation therapyPalliative careMEDLINEPhysical therapyProspective cohort studySurgeryNursing

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate the quality of life (QOL) following palliative radiotherapy for painful bone metastases. METHODS: A literature search was conducted in OvidSP Medline (1946-Jan Week 4 2014), Embase (1947-Week 5 2014), and the Cochrane Central Register of Controlled Trials (Dec 2013) databases. The search was limited to English. Subject headings and keywords included 'palliative radiation', 'cancer palliative therapy', 'bone metastases', 'quality of life', and 'pain'. All studies (prospective or retrospective) reporting change in QOL before and after palliative radiotherapy for painful bone metastases were included. RESULTS: Eighteen articles were selected from a total of 1730. The most commonly used tool to evaluate QOL was the Brief Pain Inventory. Seventeen studies collected data prospectively. An improvement in symptoms and functional interference scores following radiotherapy was observed in all studies. The difference in changes in QOL between responders and non responders was inconsistently reported. CONCLUSION: QOL improves in patients who respond to palliative radiotherapy for painful bone metastases.

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)0.010
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 score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0070.009
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.066
GPT teacher head0.447
Teacher spread0.381 · 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

Citations67
Published2014
Admission routes2
Has abstractyes

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