High Dose Rate Brachytherapy as a Treatment Option in Endobronchial Tumors
Bibliographic record
Abstract
Purpose. To report our experience with high dose rate endobronchial brachytherapy (HDR-EBBT) and to assess its efficacy and tolerability with possibility of its use in selected cases with curative intent. Method. Retrospective review of patients with endobronchial tumors treated at our institution in 2007-2013 with HDR-EBBT. Subjective response and treatment related toxicity were extracted from patients' records. Clinical response was evaluated by chest CT +/- bronchoscopy 2-3 months after treatment. Local control (LC) and overall survival (OS) were analyzed. Results. Overall 23 patients were identified. Ten patients were treated with curative intent, in 8 of them HDR-EBBT was combined with external beam radiotherapy. Short term palliation was as follows: dyspnea (13/15), cough (12/14), and hemoptysis (3/3). Seventeen patients were evaluated, of whom 9 (53%) showed complete response. Four patients developed local failure (only 1 of them treated with curative intent) and were salvaged with HDR-EBBT (n = 1), chemotherapy (n = 2), and laser (n = 1). Among patients treated with curative intent, the 2-year LC and OS were 89% and 67%, respectively, and 2 out of 4 deaths were cancer-related. Late toxicity included bronchial stenosis (n = 1). Only 1 patient had fatal hemoptysis and postmortem examination indicated local recurrence. Conclusion. HDR-EBBT is promising treatment with tolerable complication if used in properly selected patients.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".