STEREOTACTIC BODY RADIOTHERAPY (SBRT) FOR SACRAL METASTASES: DEVIATION FROM RECOMMENDED TARGET VOLUME DELINEATION PREDICTS HIGHER RISK OF LOCAL FAILURE
Bibliographic record
Abstract
Abstract Report outcomes after sacrum SBRT, focusing on the impact of contouring deviation on local failure (LF) risk, with an aim to validate the contouring consensus guidelines. METHODS/MATERIALS: Patients who underwent sacral SBRT from 2010- 2021 were identified from a prospectively maintained institutional database. Primary outcomes were magnetic resonance-based LF and vertebral compression fracture (VCF). RESULTS: A total of 215 treated sacral segments in 112 patients were reviewed. Most segments were treated with 30 Gy/4 fractions (51%), 24 Gy/2 fractions (31%), or 30 Gy/5 fractions (10%). Thirty-one percent of segments were of radioresistant histology (gastrointestinal, kidney, melanoma, sarcoma, or thyroid primary), and 51% had extraosseous disease. Sixteen percent of segments were under-contoured per consensus guidelines. The cumulative incidence of LF was 18.4% (95% CI 13.5-24.0) at 12-months and 23.1% (95% CI 17.6-29.0) at 24-months. On multivariate analysis (MVA), under- contouring (HR 2.4, 95% CI 1.3-4.7, p=0.008), radioresistant histology (HR 2.4, 95% CI 1,4-4.1, p=0.001), and extraosseous extension (HR 2.5, 95% CI 1.3-4.7, p=0.005) were predictors of increased risk of LF. The LF rates at 12/24-months were 15.1%/18.8% for segments contoured per guideline versus 31.4%/40.0% for those under-contoured. The cumulative incidence of VCF was 7.1% (95% CI 4.1-11.1) at 12-months and 12.3% (95% CI 8.2-17.2) at 24-months. On MVA, female gender predicted increased VCF risk (HR 2.3, 95% CI 1.1-5.2, p=0.04). CONCLUSIONS: Sacral SBRT is associated with high rates of efficacy and an acceptable VCF risk. Adherence to target volume delineation consensus guidelines reduces the risk of LF.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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".