Assessing the efficacy of palliative radiation treatment schemes for locally advanced squamous cell carcinoma of the head and neck: a meta-analysis
Bibliographic record
Abstract
Background: The objective to assess the outcomes from different palliative radiotherapy (RT) schedules in incurable head and neck cancer (HNC), to evaluate if there is a relationship between RT dose, technique, and fractionation with tumor response in contrast to the occurrence of adverse effects. Materials and methods: Eligible studies were identified on Medline, Embase, the Cochrane Library, and annual meetings proceedings through June 2020. Following PRISMA and MOOSE guidelines, a cumulative meta-analysis of studies for overall response rate (ORR), overall survival (OS), progression-free survival (PFS), pain/dysphagia relief, and toxicity was performed. A meta-regression analysis was done to assess if there is a connection between RT dose, schedule, and technique with ORR. Results: Twenty-eight studies with 1,986 patients treated with palliative RT due to incurable HNC were included. The median OS was 6.5 months [95% confidence interval (CI): 5.6-7.4], and PFS was 3.6 months (95% CI: 2.7-4.3). The ORR, pain and dysphagia relief rates were 72% (95% CI: 0.6-0.8), 83% (95% CI: 52-100%), and 75% (95% CI: 52-100%), respectively. Conventional radiotherapy (2D-RT) or conformational radiotherapy (3D-RT) use were significantly associated with a higher acute toxicity rate (grade ≥ 3) than intensity-modulated radiation therapy (IMRT) or stereotactic body radiation therapy (SBRT). On meta-regression analyses, the total biological effective doses (BED) of RT (p = 0.001), BED > 60 Gy10 (p = 0.001), short course (p = 0.01) and SBRT (p = 0.02) were associated with a superior ORR. Conclusions: Palliative RT achieves tumor response and symptom relief in incurable HNC patients. Short course RT of BED > 60 Gy using IMRT could improve its therapeutic ratio. SBRT should be considered when available.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".