Palliative radiation therapy for children with cancer
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".