Effectiveness of palliative hemostatic radiotherapy for hemoptysis: a prospective single-arm observation study
Bibliographic record
Abstract
BACKGROUND: Palliative radiotherapy (RT) is commonly used for malignancy-associated hemoptysis. This study aims to determine RT control probability, durability, and influencing factors. METHODS: This single-institution prospective observational study included patients ≥18 years old with any lung malignancy and active hemoptysis. Hemoptysis severity was captured and monitored via Common Terminology Criteria for Adverse Events (CTCAE) and an in-house developed Patient-Reported Outcome Measure (PROM) tool. Patients were interviewed at enrollment, 2 weeks, 3 months, and 6 months post-treatment. Descriptive statistics, the Kaplan-Meier (KM) method, the Wilcoxon signed-rank test, and Cox regression models were used. RESULTS: From April 2016 to November 2018, 41 patients were enrolled. One patient withdrew consent and was excluded. The median age was 68 years. Most patients were male (67%) with stage 4 (87.5%), lung primary (85%) disease, and Eastern Cooperative Oncology Group (ECOG) performance status ≥2 (55%). The most common fractionation scheme (72.5%) was 2,000 cGy in 5 fractions. Eight patients (20%) passed away before 2-week assessment. Median follow-up was 6.1 months (range, 0.9-6.2 months). The 6-month overall survival (OS) rate was 26% [95% confidence interval (CI): 13-41%]. The 6-month bleeding-related survival (BRS) was 95% (95% CI: 80-99%), and the 6-month freedom from hemoptysis rate was 37% (95% CI: 18-57%). No patient received re-irradiation for their hemoptysis. On univariate analysis, ECOG status (P=0.01) and prior radiation (P=0.006) were strongly associated with freedom from hemoptysis survival. CONCLUSIONS: Hemostatic RT remains an effective modality for controlling hemoptysis. The short interval high mortality rate post-RT challenges whether fractionated palliative RT should be used for this patient population. Conducting a large clinical trial with a hemoptysis PROM tool is necessary to identify hemostatic durability and influencing factors properly.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".