Outcome of Hypofractionated Palliative Radiotherapy Regimens for Patients With Advanced Head and Neck Cancer in Tikur Anbessa Hospital, Ethiopia: A Prospective Cohort Study
Bibliographic record
Abstract
PURPOSE: Head and neck cancers (HNCs) are the third most commonly treated cancer with radiation in Ethiopia. Most patients present with advanced stage and are not candidates for curative treatment. The objective of our study is to assess the outcome of hypofractionated palliative radiotherapy (RT) for advanced HNCs in a resource-limited setting. MATERIALS AND METHODS: Patients with histology-proven advanced HNC candidates for hypofractionated palliative RT were enrolled. Three regimens were allowed: 44.4 Gy in 12 fractions, 30 Gy in 10 fractions, and 20 Gy in five fractions. Response to treatment was assessed at baseline and at 4 weeks after treatment completion. The Kaplan-Meier curve was used to measure the survival. RESULTS: Between January 2022 and January 2023, 52 patients were enrolled and 25 patients were eligible for outcome assessment. Index symptoms include pain, bleeding, dysphagia, respiratory distress, and others in 25, 13, 10, 6, and 17 patients, respectively. Complete relief of the top three symptoms include pain in 52% of patients, hemostasis in 84% of patients, and dysphagia in 30% of patients. Objectively, 64% of patients attained partial response. For 48% of patients, their quality of life (QoL) improved in one parameter of the physical scores. Moreover, 64% of patients showed improvement in three parameters. The global functional score improved in 80% of patients. One patient had grade 3 xerostomia. At the end of the study period, 44% of patients died. The median survival after radiation was 9 months (95% CI, 7.2 to 10.8). CONCLUSION: All palliative hypofractionated regimens used were effective in terms of symptom control, tumor response rate, and QoL, and were well tolerated. This makes it appropriate for our setup because the majority of patients require palliation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".