Clinical outcomes of multisite moderate to high dose radiotherapy for patients with metastatic melanoma
Bibliographic record
Abstract
Background and purpose: This study aimed to summarize the clinical outcomes of patients with metastatic melanoma who received high-dose radiation prior to or during systemic therapy at a single academic institution. Methods: We identified patients with metastatic melanoma who underwent high-dose radiation therapy (HDRT) for extracranial metastases prior to or during systemic therapy from 2010 to 2018. Treatment indications included oligometastases, oligoprogression, and local control. Using the Kaplan-Meier method, we plotted overall survival (OS), progression-free survival-1 (PFS1), and PFS2. Competing risk analysis determined the cumulative incidence of local failure (LF) and the time to start or change systemic therapy (SCST). Univariate and multivariable analyses were used to identify predictive factors. Results: We analyzed 34 patients with 79 lesions, with a median follow-up of 17.4 months. Sixty-eight percent of patients received systemic therapy after the first HDRT. The median OS was 22 months, with brain metastases before HDRT being a significant predictor in multivariable analysis. The median PFS1 for first-line HDRT was 4.1 months, and the median PFS2 was 3.9 months. Rates of LF were 10.3% at 12 months and 11.7% at 24 months. The incidence of SCST following HDRT was 59.8% at 12 months and 76.1% at 24 months, with radiation targeted at the lung associated with a lower incidence of SCST. Conclusion: HDRT for treating metastatic lesions in melanoma demonstrated excellent local control and may play a role in delaying SCST. Additional courses of HDRT may provide cumulative benefits.
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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 | 0.000 | 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) | 0.001 | 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".