Imaging-Based Outcomes for 24 Gy in 2 Daily Fractions for Patients with de Novo Spinal Metastases Treated With Spine Stereotactic Body Radiation Therapy (SBRT)
Bibliographic record
Abstract
PURPOSE: We report mature outcomes for a cohort of patients with no prior radiation (de novo) to the spine treated with 24 Gy in 2 daily fractions for metastases, which represents the same stereotactic body radiation therapy (SBRT) regimen under evaluation in the current Symptom Control-24 phase 3 randomized trial (NCT02512965). METHODS AND MATERIALS: The cohort consisted of 279 de novo spinal metastases in 145 consecutive patients treated with 24 Gy in 2 SBRT fractions, identified from a prospective single-institution database. The endpoints were overall survival (OS), imaging-based local failure (LF), and cumulative risk of vertebral compression fractures (VCF). RESULTS: The median follow-up per treated metastasis was 15.0 months (range, 0.1-71.6). The 1-year and 2-year OS rates were 73.1% and 60.7%, respectively. Presence of epidural disease (P < .0001), lung (P = .0415), and renal cell (P < .0001) primary histologies and baseline diffuse metastases (P = .0034) were significant prognostic factors for OS. The 1-year and 2-year LF rates were 9.7% and 17.6%, respectively, and the median time to LF was 9.2 month (range, 0.4-31.3 months). Only the presence of epidural disease predicted for LF (P < .0001). The cumulative risk of VCF at 1 and 2 years was 8.5% and 13.8%, respectively. Lytic (P = .0143) or mixed lytic/blastic (P = .0214) lesions, spinal malalignment (P = .0121), and the dose to 90% of the planning target volume (P = .0085) were significant predictors for VCF. CONCLUSIONS: Twenty-four Gray in 2 daily fractions is safe and effective in achieving high tumor control rates for de novo spinal metastases. These outcomes will serve as a benchmark for the ongoing Symptom Control-24 randomized trial comparing 24 Gy in 2 SBRT fractions to 20 Gy delivered in 5 daily conventional fractions.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".