RONC-10. OUTCOMES OF STEREOTACTIC RADIOSURGERY FOR PILOCYTIC ASTROCYTOMA: AN INTERNATIONAL MULTICENTER STUDY
Bibliographic record
Abstract
The utility of radiosurgery is not well documented for pilocytic astrocytoma. We analyzed the efficacy and prognostic factors associated with Gamma Knife radiosurgery (GKRS) for pilocytic astrocytoma in an international multicenter trial. Nine medical centers from the International Gamma Knife Research Foundation provided data. Patients treated with single session GKRS with histologic diagnosis of pilocytic astrocytoma were eligible. Patient, tumor, and treatment variables were analyzed. 141 patients with a median age 13.9 years (range: 2-84) were included. Median follow up was 67.3 months. Twenty-one (15%) had radiotherapy (RT) and 11 (8%) had chemotherapy prior to GKRS. Median margin dose: 14 Gy (range: 4-22.5). Median tumor volume:3.45cc (range: 0.17-33.7). Overall survival at 3, 5 and 10 years from GKRS was 96.8%, 95.7% and 92.5%, respectively. Thirty-four patients progressed resulting in progression-free survival (PFS) at 3, 5, and 10 years of 80.8%, 74.0%, and 69.7%, respectively. For patients <18 years old, 3, 5, and 10 year PFS was 88.3%, 81.3%, and 77.0%, respectively. This was significantly improved (p=0.008) compared to patients ≥18 years old (3, 5, and 10 year PFS of 67.3%, 60.9%, and 56.8%, respectively). Similarly, patients without prior RT (p=0.001), or prior chemotherapy (p=0.003), and with tumor volume <4.5cc (p=0.012) had significantly better PFS. On multivariable analysis, only prior RT impacted PFS (p=0.001, HR=3.705, CI: 1.76-7.80). GKRS for pilocytic astrocytoma results in excellent long term survival and good local control. GKRS may be a particularly useful minimally invasive tool for younger patients with smaller tumor volumes.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".