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Record W3147209506 · doi:10.1002/pbc.28292

Palliative radiation therapy for children with cancer

2021· review· en· W3147209506 on OpenAlexaff
Derek S. Tsang, John A. Vargo, Karen Goddard, John C. Breneman, John A. Kalapurakal, Karen J. Marcus

Bibliographic record

VenuePediatric Blood & Cancer · 2021
Typereview
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsUniversity of British ColumbiaPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicinePalliative careLung cancerRadiation therapyGuidelineRadiosurgerySpinal cord compressionDose fractionationOncologySurgerySpinal cordPathology

Abstract

fetched live from OpenAlex

Radiation therapy (RT) is often used as a palliative treatment for children with recurrent malignant disease to ameliorate or prevent symptoms. However, no guidelines exist regarding the clinical indications or dose fractionation for palliative RT. The goal of this report is to provide guidelines for the use of palliative RT in children with cancer. In this guideline, appropriate indications for palliative RT, recommended dose-fractionation schedules, relevant toxicities, and avenues for future research are explored. RT is an effective palliative treatment for bone, brain, liver, lung, abdominopelvic and head-and-neck metastases, spinal cord compression, superior vena cava syndrome, and bleeding. Single-fraction regimens (8 Gy in one fraction) for children with short life expectancy are recommended for simple, uncomplicated bone metastases and can be considered for some patients with lung or liver metastases. A short, hypofractionated regimen (20 Gy in five fractions) may be used for other indications to minimize overall burden of therapy. There are little data supporting use of more prolonged fractionation regimens, though they may be considered for patients with very good performance status. Future research should focus on response and outcomes data collection, and to rigorously evaluate the role of stereotactic body RT in well-designed, prospective studies.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.949
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.047
GPT teacher head0.373
Teacher spread0.327 · 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.

Study designNot applicable
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

Citations16
Published2021
Admission routes1
Has abstractyes

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