Emergent radiotherapy for pelvic malignancies: a narrative review
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Patients with primary genitourinary (GU), gynecologic (GYN) and gastrointestinal (GI) cancers can develop life-threatening or critical function-threatening symptoms that necessitate emergent intervention with palliative radiotherapy (RT). Unfortunately, research describing the use of RT in this critical setting is lacking. We aimed to review literature describing emergent palliative RT for primary pelvic malignancies and provide a narrative synthesis of relevant studies. METHODS: A medical librarian searched Ovid MEDLINE, Embase Classic, and Embase databases for relevant English language references from 1946-2022. No restrictions were placed on study type, publication type or date. References for GU, GYN and GI cancers were grouped and synthesized separately. KEY CONTENT AND FINDINGS: The treatment of bleeding from primary pelvic tumors was the only indication for emergent RT identified, however, no references reported dedicated cohorts of patients treated for bleeding in the emergent setting. Most references were retrospective single institution studies describing various dose fractionation schemes for non-emergent palliative RT. Outcome measures and response assessment times varied. The latency to hemostasis after RT commencement was not well described; most studies reported outcomes captured weeks or months following treatment. In general, high rates of hemostasis for GU, GYN and GI tumors have been reported following RT schedules ranging from a single fraction to many weeks of fractionated treatments. Bleeding seems to respond more favorably than other symptoms including pain and obstruction. CONCLUSIONS: Managing bleeding was the only indication for emergent RT identified in our search. Scant data exist that describe the latency to a hemostatic response following RT. This is an important knowledge gap in the literature given how commonly patients are affected by this complication of primary pelvic malignancies.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".